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Advances in the management of chronic kidney disease

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• Peer review
• Teresa K Chen , assistant professor 1 ,
• Melanie P Hoenig , associate professor 2 ,
• Dorothea Nitsch , professor 3 ,
• Morgan E Grams , professor 4
• 1 Kidney Health Research Collaborative and Division of Nephrology, Department of Medicine, University of California San Francisco; and San Francisco VA Health Care System, San Francisco, CA, USA
• 2 Division of Nephrology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
• 3 Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
• 4 Department of Medicine, New York University Langone School of Medicine, New York, NY, USA
• Correspondence to: M E Grams Morgan.Grams{at}nyulangone.org

Chronic kidney disease (CKD) represents a global public health crisis, but awareness by patients and providers is poor. Defined as persistent abnormalities in kidney structure or function for more than three months, manifested as either low glomerular filtration rate or presence of a marker of kidney damage such as albuminuria, CKD can be identified through readily available blood and urine tests. Early recognition of CKD is crucial for harnessing major advances in staging, prognosis, and treatment. This review discusses the evidence behind the general principles of CKD management, such as blood pressure and glucose control, renin-angiotensin-aldosterone system blockade, statin therapy, and dietary management. It additionally describes individualized approaches to treatment based on risk of kidney failure and cause of CKD. Finally, it reviews novel classes of kidney protective agents including sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists, non-steroidal selective mineralocorticoid receptor antagonists, and endothelin receptor antagonists. Appropriate, widespread implementation of these highly effective therapies should improve the lives of people with CKD and decrease the worldwide incidence of kidney failure.

Introduction

Chronic kidney disease (CKD) affects approximately 10% of the world’s population and is associated with substantial morbidity and mortality. 1 Risks of kidney failure, acute kidney injury, heart failure, cardiovascular disease, and hospital admissions are all heightened in people with CKD. 2 The Global Burden of Disease Consortium projects that CKD will be in the top five conditions contributing to years of life lost by 2040. 3 However, CKD remains under-recognized by both patients and providers. 1 A diverse entity, CKD is most commonly attributed to diabetes or high blood pressure, but many other causes exist, from genetic causes to adverse effects of drugs to autoimmune processes. 2 In this review, we summarize the evidence for current paradigms of disease identification and classification, discuss new equations developed for estimating glomerular filtration rate (GFR) and harmonizing different measures of albuminuria, report major progress in individualized risk estimation of kidney failure and other adverse outcomes both for CKD in general and within specific disease entities, and describe longstanding and novel treatment strategies. Notable advances have been made in both general and cause specific therapies, including sodium-glucose cotransporter-2 (SGLT-2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, non-steroidal selective mineralocorticoid receptor antagonists (MRA), and endothelin receptor antagonists. Finally, we describe major guidelines in CKD and highlight common themes as well as differences in their recommendations.

Sources and selection criteria

We searched PubMed for peer reviewed articles in the English language from 1 January 2010 to 14 July 2023 using the keywords listed in the web appendix. We additionally reviewed reference lists of selected articles, prioritizing randomized controlled trials, systematic reviews, and meta-analyses when possible but also including observational studies and reviews that were of high quality. We included older articles if we deemed them to be of high importance. Finally, we reviewed guidelines from websites of professional societies and advisory committees (for example, the National Institute for Health and Care Excellence (NICE), Kidney Disease: Improving Global Outcomes (KDIGO), US Centers for Disease Control and Prevention, US Department of Health and Human Services, and International Society of Hypertension).

Epidemiology

CKD is a global public health crisis. Recent estimates suggest that more than 700 million people have CKD, with greater burdens in low income and middle income countries. 1 4 Determining the global, regional, and national burden of disease is challenging owing to inconsistent use of estimating equations for GFR, laboratory assay standardization, and albuminuria testing. Despite this, some important observations can still be made. The prevalence of CKD increases with age and is greatest in people over 70 years. 2 In the US, compared with White people, Black people have substantially higher rates of kidney failure, followed by Native Americans, people of Hispanic ethnicity, and people of Asian descent. 5

The most commonly reported risk factors for CKD are diabetes mellitus and hypertension. 6 7 Social determinants of health are also important and likely contribute to racial disparities in kidney disease. Specific genetic variants increase risk of CKD, including variants in the APOL1 and HBB genes that are present in far greater proportions among people of African ancestry. 8 9 10 11 In Central America, Sri Lanka, Egypt, and Central India, defined geographic areas exist where many cases of CKD of unknown cause have been identified. 12 Some experts postulate that heat stress or pesticides may contribute.

Whereas the incidence of CKD is difficult to estimate, reliant as it is on testing for GFR and albuminuria, the incidence of kidney failure with the receipt of replacement therapy (KFRT) is more readily captured. Many countries have developed national registries of patients with kidney failure, allowing comparison of incidence across ages and countries. 13 For example, the countries with the highest incidence of treated kidney failure in 2020 were Taiwan, the US, and Singapore, whereas the countries with the highest prevalence were Taiwan, the Republic of Korea, and Japan. 5

Definition and classification of CKD: cause, GFR, and albuminuria staging

CKD is defined as persistent abnormalities in kidney structure or function for more than three months, manifest as either low GFR or presence of a marker of kidney damage. 2 Specifically, diagnosis requires one or more of the following: albuminuria, defined as an albumin-to-creatinine ratio (ACR) ≥30 mg per gram of creatinine (approximately ≥3 mg/mmol) or albumin excretion of ≥30 mg/day; GFR <60 mL/min/1.73 m 2 ; abnormalities on urine sediment, histology, or imaging; electrolyte or other abnormalities attributed to tubular disorders; or history of kidney transplantation. The KDIGO heat map helps with understanding of overall risk (low, moderately increased, high, and very high) of patients according to level of albuminuria (A category), level of GFR (G category), and cause of disease ( fig 1 ), such that people with normal estimated GFR but higher albuminuria have a similar risk to people with moderately reduced estimated GFR and no albuminuria.

Kidney Disease: Improving Global Outcomes heat map with guidance on monitoring. 2 Numbers in boxes indicate recommended frequency of monitoring (number of times per year). Colors denote risk as follows: green (low risk), yellow (moderately increased risk), orange (high risk), and red (very high risk). CKD=chronic kidney disease; GFR=glomerular filtration rate

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Clinical manifestations of CKD

Albuminuria.

Albuminuria is often the first sign of kidney damage, and its detection drives many treatment decisions. 2 The prevalence of albuminuria in people with diabetes or hypertension is estimated to be 32% and 22%, respectively. 14 However, only a minority of patients receive urine screening tests. 14 15 For example, the mean albuminuria screening rates across health systems in the US were 35% among adults with diabetes and 4% among adults with hypertension. 14

The gold standard for assessing albuminuria is either a sample collected mid-stream from an early morning urine void or a 24 hour urine collection; however, in situations where this is not possible, a spot collection is reasonable. 2 Quantification of albumin is preferred over that of total protein. 2 16 This preference is because the sensitivity of the total protein assay to different protein components can vary by laboratory, as well as the fact that proteinuria assessments do not easily discriminate A1 and A2 categories. Both urine albumin and urine protein are typically indexed to urine creatinine to account for differences in dilution, as urine ACR or urine protein-to-creatinine ratio (PCR). Dipstick protein assessment is generally more economical than both methods; however, like PCR, dipstick assessment can be insensitive in A1 and A2 categories. Although conversion calculators exist to aid in the harmonization of ACR and PCR measures; they do not work well at lower ranges of albuminuria. 17 18

The second axis for CKD classification focuses on GFR. 2 The gold standard for assessing GFR is direct measurement from clearance of an exogenous filtration marker such as iohexol or iothalamate; however, this is relatively cumbersome and rarely done in clinical practice. Instead, GFR is usually estimated by using plasma or serum concentrations of endogenous filtration markers, such as creatinine and cystatin C, and demographic variables. Early equations for adults, such as Modification of Diet in Renal Disease (MDRD) and CKD Epidemiology Collaboration (CKD-EPI) 2009 equations, used filtration markers along with age, sex, and race (Black versus non-Black) to estimate GFR. 19 20 21 The newer European Kidney Function Consortium equation, which allows for seamless GFR evaluation from infancy to old age, uses a population specific divisor to adjust creatinine values (for example, separate values for Black European and White European populations). 22 However, the use of race in GFR estimation has faced strong criticism and, in 2021, the US based American Society of Nephrology-National Kidney Foundation Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease recommended immediate adoption of the race-free CKD-EPI 2021 estimating equations, which exist for creatinine alone (eGFRcr) as well as for creatinine and cystatin C (eGFRcr-cys). 23 24 25 Cystatin C has distinct confounders (non-GFR determinants) of its relation with GFR compared with creatinine ( fig 2 ). 2 26 Thus, eGFRcr-cys is a more accurate estimate of GFR than eGFRcr alone, irrespective of equation used, in most scenarios, including those in which large differences exist between eGFRcr and that estimated solely using cystatin C (eGFRcys). 25 27 28 However, the newest GFR estimating equations have not been tested extensively in Asian populations. 29 30

Common non-glomerular filtration rate (GFR) determinants of blood concentrations of creatinine and cystatin C. 2 26 eGFR=estimated glomerular filtration rate

The third axis for classification is cause of CKD, which is generally ascertained through imaging, assessment of extrarenal manifestations and biomarkers, or kidney biopsy. 2 Classification of cause typically hinges on the presence or absence of systemic disease (for example, obesity, diabetes, hypertension, systemic autoimmune disease) and the specific location of the kidney pathology (for example, glomeruli, tubulointerstitium, vasculature, or cystic/congenital abnormality). Unfortunately, the cause of CKD is often unknown, limiting its utility. Molecular phenotyping and genetic testing are increasingly being used to assign cause of disease. Targeted gene panels offered commercially may have high diagnostic yields in select populations, such as patients with glomerular disease, nephrotic syndrome, or congenital anomalies of the kidney and urinary tract. 31 One study suggested that for appropriately selected patients, 34% had disease either reclassified or assigned on the basis of genetic testing, thus changing clinical management. 32 The European Renal Association and the European Rare Kidney Disease Reference Network have issued a joint statement providing recommendations for how to provide genetic testing, including specific settings in which it may be considered ( box 1 ). 33

European Renal Association and European Rare Kidney Disease Reference Network recommendations for settings in which genetic testing might be considered 33

Most tubulopathies

Glomerulopathies:

Congenital nephrotic syndrome

Nephrotic syndrome refractory to standard steroid therapy

Multi-organ phenotypes suggestive of syndromic steroid resistant nephrotic syndrome

Complement disorders:

Immune complex mediated membranoproliferative glomerulonephritis

C3 glomerulopathy

Atypical hemolytic uremic syndrome

Renal ciliopathies

Congenital anomalies of the kidney and urinary tract

Patients aged <50 years with severe CKD of unknown cause

Patients aged >50 years with adult onset CKD and family history of CKD

CKD=chronic kidney disease

Individualized prognosis and treatment

Identifying the cause of CKD is critical as different causes of CKD carry different prognoses and can have distinct treatments. 2 For example, autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic cause of CKD and is typically associated with faster progression than other disease entities. 32 34 Individualized prognosis is often determined by using disease specific risk classification or calculators (for example, the Mayo classification or the ADPKD Prognostic Tool), and screening and treatment recommendations such as increased fluid intake and tolvaptan are unique to this entity. 35 36 37 38 IgA nephropathy, the most common type of glomerulonephritis worldwide, particularly in East Asian and Pacific Asian countries, 39 has its own prognostic aids, such as the International IgA Nephropathy Prediction Tool, 40 41 and treatments specific to IgA nephropathy are in various stages of development. 42 The APOL1 high risk genotypes confer about twofold higher risk of kidney failure in the general population and are common in people of African ancestry. 8 43 44 45 A recently published phase 2A study of targeted therapy for APOL1 related disease showed promising reductions in albuminuria; the phase 3 study is ongoing. 46 Other disease specific therapies are increasingly available, such as belimumab in lupus nephritis and lumasiran for primary hyperoxaluria type 1. 47 48

Individualized risk prediction is also available for more general populations of patients with CKD. The most widely known and validated is the kidney failure risk equation (KFRE), which is used in patients with GFR <60 mL/min/1.73 m 2 . 49 Tested in more than 30 countries and 700 000 people, the tool provides probabilities of kidney failure at two years and five years based on age, sex, and estimated GFR and albuminuria levels. 50 Like all risk equations, the KFRE may perform better with recalibration to absolute risk levels of local populations, but the discriminatory ability (that is, distinguishing people at high risk from those at low risk) has been extremely consistent across all studies. The KFRE has also been validated in recipients of kidney transplants. 51 52 Although the KFRE does not explicitly take into account the competing risk of death, estimates are quite accurate except among the members of the oldest segments of the population at the highest risk. 53 One study suggested that the KFRE provides more accurate prediction of kidney failure than both patients and providers. 54 Even within categories of GFR and urine ACR, the KFRE provides a wide estimate of risk prediction, which can be helpful in the counseling and referral of patients ( fig 3 ). Some centers will refer patients with a two year risk of kidney failure greater than 20-40% for vascular access and kidney transplantation evaluation, on the basis that tools that incorporate albuminuria provide more accurate and unbiased time to kidney failure than does estimated GFR alone. 55 Studies suggest that the KFRE is robust to different GFR equations (specifically, CKD-EPI 2009 and CKD-EPI 2021) and that many patients value being counseled using this information. 53 56

Range of predicted risk of kidney failure using the kidney failure risk equation (KFRE) within G and A categories of chronic kidney disease (CKD). The KFRE ( ckdpcrisk.org/kidneyfailurerisk ) was used to estimate two year risk of kidney failure in 350 232 patients with estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m 2 from the Optum Laboratories Data Warehouse (OLDW). OLDW is a longitudinal, real world data asset with deidentified administrative claims and electronic health record data. Patients with eGFR and albuminuria (urine albumin-to-creatinine ratio (ACR), protein-to-creatinine ratio, or dipstick protein) within a two year window were included in this analysis. Different measures of albuminuria were harmonized to ACR levels for A categories ( ckdpcrisk.org/pcr2acr )

Other risk equations exist to predict the risk of cardiovascular disease and death in CKD; some of these do consider the competing risk of death ( www.ckdpcrisk.org ). For example, the advanced CKD risk tool provides simultaneous estimates of kidney failure, cardiovascular disease, and death for patients with estimated GFR <30 mL/min/1.73 m 2 , which can inform decisions on access placement and reinforce the importance of cardiovascular risk reduction. 57 Estimating risks of cardiovascular disease is particularly relevant given that many more patients with CKD have cardiovascular disease events than need KFRT. 58 Other efforts incorporate estimated GFR and albuminuria into existing tools, such as SCORE2 and the pooled cohort equation for the prediction of cardiovascular disease. 59 60

Patient specific prognostic clues may stem from discrepant estimated GFR values between eGFRcr and eGFRcys. 61 62 63 When eGFRcys is substantially lower than eGFRcr, the risk for kidney related laboratory abnormalities (for example, anemia, hyperuricemia, and hyperphosphatemia) and subsequent adverse outcomes (for example, kidney failure, heart failure, and mortality) is higher. 61 64 65 By contrast, having a lower eGFRcr than eGFRcys is associated with lower risk of adverse outcomes. 66 Risk factors for having a discrepancy between eGFRcr and eGFRcys include older age, female sex, higher body mass index, recent weight loss, and smoking.

General principles of management

The mainstays of therapy for patients with CKD include treating the underlying cause if known, and correcting risk factors (for example, albuminuria) for CKD progression and other CKD related complications ( fig 4 ). 2

Comprehensive care of patients with chronic kidney disease (CKD), irrespective of cause

Blood pressure targets

The three major studies for evaluating the optimal blood pressure target in CKD were the Modification of Diet in Renal Disease Study (MDRD), African American Study of Kidney Disease and Hypertension (AASK), and Systolic Blood Pressure Intervention Trial (SPRINT). 67 68 69 In both MDRD and AASK, intensive blood pressure control did not slow GFR decline overall. 67 68 However, in MDRD, participants with baseline proteinuria of ≥3 g/day seemed to benefit from intensive blood pressure control, with slower mean rates of GFR decline compared with their counterparts in the usual blood pressure control group. 67 Among SPRINT participants with baseline CKD (n=2646), aiming for a systolic blood pressure goal of <120 mm Hg versus <140 mm Hg did not significantly reduce the risk for a composite kidney outcome that included a ≥50% reduction in estimated GFR, long term dialysis, or kidney transplant. 69 70 However, benefits of intensive blood pressure control were seen with respect to prevention of the composite cardiovascular outcome (defined as myocardial infarction, acute coronary syndrome, stroke, heart failure, or death from cardiovascular causes—hazard ratio 0.75, 95% confidence interval 0.64 to 0.89) and all cause mortality (hazard ratio 0.73, 0.60 to 0.90), regardless of CKD status. 69 Blood pressure control can also reduce albuminuria, as shown in the Chlorthalidone in Chronic Kidney Disease (CLICK) trial of chlorthalidone in advanced CKD. 71

Glycemic targets

Among patients with diabetes and CKD, glycemic control is an important component of comprehensive care. 72 The Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) was the largest trial of intensive glucose control to enroll patients with CKD. 73 Among the 11 140 trial participants, 19% had an estimated GFR <60 mL/min/1.73 m 2 and 31% had albuminuria at baseline. 74 Compared with standard glucose control, intensive glucose control was associated with 9% (hazard ratio 0.91, 0.85 to 0.98), 30% (0.70, 0.57 to 0.85), and 65% (0.35, 0.15 to 0.83) lower risks of developing new onset ACR 30-300 mg/g, ACR >300 mg/g, and end stage kidney disease (ESKD), respectively.

Specific classes of therapy

Angiotensin converting enzyme inhibitors and angiotensin receptor blockers.

When choosing antihypertensive agents, those that act by inhibiting the renin-angiotensin-aldosterone system (RAAS) have particular relevance in CKD. A 2001 meta-analysis of 11 studies suggested that, for non-diabetic CKD, the use of angiotensin converting enzyme (ACE) inhibitors resulted in a 30% reduction in risk of KFRT or doubling of serum creatinine. 75 Clinical trials in populations with CKD and diabetes (for example, IDNT, RENAAL) have also shown benefit of angiotensin receptor blockers (ARB) in preventing CKD progression ( table 1 ). 77 78 RAAS inhibition also plays a role in prevention of cardiovascular disease. The Heart Outcomes Prevention Evaluation (HOPE) study showed that ACE inhibitors reduced the risks of myocardial infarction, stroke, and cardiovascular death in populations at high risk for cardiovascular disease, including those with diabetes and albuminuria. 80 The Ongoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial (ONTARGET) showed that ACE inhibitors and ARB were generally equivalent in the prevention of cardiovascular events. 81 Because of the increased risk of hyperkalemia and acute kidney injury, dual therapy with both an ACE inhibitor and an ARB is typically avoided. 82

Landmark randomized clinical trials on angiotensin converting enzyme inhibitors or angiotensin receptor blockers in chronic kidney disease

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When GFR declines, providers often grapple with whether RAAS inhibitors should be continued. The Benazepril in Advanced CKD study showed that benazepril reduced the risk of the primary composite kidney endpoint by 43% compared with placebo, thus suggesting that RAAS inhibitors are beneficial even in advanced CKD (baseline serum creatinine 3.1-5.0 mg/dL). 79 Three recent reports further explored this question, also examining the benefits in prevention of death and cardiovascular events associated with continuation of RAAS inhibitors. 83 84 85 A retrospective, propensity score matched study of patients with estimated GFR <30 mL/min/1.73 m 2 showed higher risk of all cause mortality and major adverse cardiovascular events in those who stopped RAAS inhibitors compared with those who continued them, 83 as did a Swedish trial emulation study. 84 The risk of kidney replacement therapy associated with cessation of RAAS inhibitors was not statistically significant in the first study and lower in the second study. 83 84 In an open label randomized trial, cessation of RAAS inhibitors did not show significant between group differences in long term decline in estimated GFR or initiation of kidney replacement therapy, providing reassurance that RAAS inhibitors can be safely continued as GFR declines. 85

SGLT-2 inhibitors

One of the biggest advancements in CKD management over the past decade was the discovery that SGLT-2 inhibitors have robust protective effects on the heart and kidneys in patients with and without diabetes. Recent trials showed an approximate 30% reduction in risk for diverse kidney outcomes among patients with baseline estimated GFR values as low as 20 mL/min/1.73 m 2 ( table 2 ). 86 88 89 91 Importantly, the three trials designed with primary kidney outcomes (Canagliflozin and Renal Events in Diabetes and Established Nephropathy Clinical Evaluation (CREDENCE), Dapagliflozin and Prevention of Adverse Outcomes in Chronic Kidney Disease (DAPA-CKD), and Study of Heart and Kidney Protection with Empagliflozin (EMPA-KIDNEY)) were terminated early because pre-specified efficacy criteria were met, with median follow-up times ranging from 2.0 to 2.6 years. 88 89 91 The overwhelming majority of trial participants were taking an ACE inhibitor or ARB before randomization, showing that the benefits of SGLT-2 inhibitors on slowing CKD progression are additive to those of RAAS inhibitors. One simulation study estimated that a 50 year old adult with non-diabetic albuminuric CKD would have seven extra years free from doubling of serum creatinine, kidney failure, or all cause mortality if treated with an SGLT-2 inhibitor and RAAS inhibitor. 92

Landmark randomized clinical trials on sodium-glucose co-transporter 2 inhibitors in chronic kidney disease (CKD)

Subgroup analyses of the DAPA-CKD and EMPA-KIDNEY trials have provided additional insights on the wide range of patients who are likely to benefit from SGLT-2 inhibitors. 89 91 In DAPA-CKD, dapagliflozin was favored over placebo in all pre-specified subgroups by baseline age, sex, race, diabetes status, systolic blood pressure, estimated GFR (<45 v ≥45 mL/min/1.73 m 2 ), and ACR (≤1000 v >1000 mg/g or ≤113 v >113 mg/mmol). 89 Similarly, in EMPA-KIDNEY, empagliflozin was associated with lower risk of the primary composite outcome compared with placebo regardless of baseline diabetes status or estimated GFR (<30 v ≥30 mL/min/1.73 m 2 to <45 v ≥45 mL/min/1.73 m 2 ). 91 The risk of the primary outcome was not lower among patients with ACR ≤300 mg/g (approximately ≤30 mg/mmol). In exploratory analyses, however, empagliflozin was associated with slower annual rates of decline in estimated GFR compared with placebo among participants with ACR between 30 and 300 mg/g (approximately 3-30 mg/mmol) and slower chronic slope (from two months to the final follow-up visit) among all ACR subgroups.

The DAPA-CKD trial also showed that the kidney protective effects of SGLT-2 inhibitors extend to patients with IgA nephropathy and perhaps also those with focal segmental glomerulosclerosis (FSGS). 93 94 Among 270 participants with IgA nephropathy (mean estimated GFR 44 mL/min/1.73 m 2 ; median ACR 900 mg/g (102 mg/mmol)), dapagliflozin was associated with a 71% lower risk of developing the primary outcome and a 70% lower risk of ESKD compared with placebo. 93 Among the 104 participants with FSGS (mean estimated GFR 42 mL/min/1.73 m 2 ; median ACR 1248 mg/g (141 mg/mmol)), dapagliflozin was not associated with a lower risk of the primary composite outcome, although this analysis was limited in power (only 11 events). 94 In exploratory analyses, dapagliflozin was associated with slower chronic decline in estimated GFR in the FSGS population. Investigations on the use of SGLT-2 inhibitors in other patient populations, such as those with polycystic kidney disease and kidney transplant recipients, are ongoing (clinicaltrials.gov).

SGLT-2 inhibitors, which act at the level of the proximal tubule to block the reabsorption of glucose and sodium, 95 are generally safe to use in patients with CKD. Early signals of heightened risks of volume depletion, serious genital infections, bone fractures, and need for limb amputation in the Canagliflozin Cardiovascular Assessment Study (CANVAS) were not observed in subsequent studies—CREDENCE, DAPA-CKD, and EMPA-KIDNEY—thus assuaging these concerns ( table 3 ). 86 88 89 91 A pooled analysis of 15 081 participants with type 2 diabetes and CKD G3-4 showed similar rates of serious adverse events for empagliflozin versus placebo, with a higher rate only of mild genital infections with the SGLT-2 inhibitor. 96 A real world study of patients receiving SGLT-2 inhibitors compared with dipeptidyl peptidase-4 (DPP-4) inhibitors found no increased risk of outpatient urinary tract infections or severe urinary tract infection events requiring hospital admission. 97

Adverse effects of SGLT-2 inhibitors * in CANVAS, CREDENCE, DAPA-CKD, and EMPA-KIDNEY trials

GLP-1 receptor agonists

GLP-1 receptor agonists have also been shown to improve kidney outcomes among patients with type 2 diabetes, albeit in trials that were designed for primary cardiac outcomes ( table 4 ). 98 99 100 101 102 103 104 105 106 107 108 109 The reduction in risk of kidney outcomes, which included albuminuria, ranged from 15% to 36%. A large meta-analysis of approximately 44 000 participants from the six trials in table 4 reported that use of GLP-1 receptor agonists was associated with a 21% lower risk of developing the composite kidney outcome, defined as new onset albuminuria >300 mg/g, doubling of serum creatinine, ≥40% decline in estimated GFR, kidney replacement therapy, or death due to kidney causes, compared with placebo. 100 This risk reduction seemed to be driven by the reduction in incident albuminuria >300 mg/g; associations between GLP-1 receptor agonists and CKD progression and kidney failure were not statistically significant. However, results were more promising in A Study Comparing Dulaglutide with Insulin Glargine on Glycemic Control in Participants with Type 2 Diabetes and Moderate or Severe Chronic Kidney Disease (AWARD-7), a clinical trial designed to evaluate change in glycated hemoglobin. 110 Among 577 adults with type 2 diabetes and CKD G3-4 randomized to open label dulaglutide 1.5 mg once weekly, dulaglutide 0.75 mg once weekly, or insulin glargine daily, both dulaglutide groups had slower estimated GFR declines compared with the insulin glargine group; among participants with baseline albuminuria >300 mg/g, dulaglutide was associated with greater ACR reductions in a dose dependent manner over the one year follow-up.

Landmark randomized clinical trials on associations of glucagon-like peptide-1 (GLP-1) receptor agonists with secondary kidney outcomes among patients with type 2 diabetes mellitus

Exact mechanisms by which the GLP-1 receptor agonists slow decline in estimated GFR and/or reduce albuminuria are not entirely clear, but proposed mechanisms include improved glycemic control, weight loss, increased natriuresis, and reduced inflammation and oxidative stress. 111 112 113 Adverse effects observed with this class of drugs have included diarrhea, nausea, and vomiting. 103 104 107 109 110

Mineralocorticoid receptor antagonists

Several MRAs are available and can be useful adjuncts to RAAS inhibitors, particularly among populations with albuminuria and/or diabetes. Two common steroidal non-selective MRAs, spironolactone and eplerenone, both lower albuminuria. 72 In a meta-analysis of 372 participants from seven trials, combination therapy with a non-selective MRA and an ACE inhibitor and/or ARB was associated with a significant reduction in proteinuria, albeit with a higher risk of hyperkalemia. 114 Finerenone, a non-steroidal selective MRA, was also recently approved. 115 Compared with the steroidal non-selective MRAs, finerenone has a stronger selectivity for the mineralocorticoid receptor, a shorter half life, less of a blood pressure lowering effect, and a more favorable side effect profile, as well as potentially greater anti-inflammatory and antifibrotic effects. 115 116 117 The Finerenone in Reducing Kidney Failure and Disease Progression in Diabetic Kidney Disease (FIDELIO-DKD) trial and the Finerenone in Reducing Cardiovascular Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial were two complementary phase 3 clinical trials designed to investigate the kidney and cardiovascular benefits of finerenone, respectively, in people with albuminuria levels ≥30 mg/g and type 2 diabetes ( table 5 ). 116 118 Both trials included patients taking maximally tolerated ACE inhibitor or ARB, with participants in FIDELIO-DKD generally having more severe baseline CKD. In a pooled analysis of the two trials, finerenone was associated with a 15-23% lower risk of developing the kidney composite outcomes and a 32% lower mean change in ACR from baseline to four months. 119 Hyperkalemia was more frequent among patients randomized to finerenone (14%) compared with placebo (7%). In pre-specified analyses, baseline SGLT-2 inhibitor use (n=877) or GLP-1 receptor agonist use (n=944) did not modify the beneficial effect of finerenone on the kidney composite outcome, thus suggesting a potential role for dual therapy (for example, finerenone plus SGLT-2 inhibitor or GLP-1 receptor agonist) among patients with type 2 diabetes and CKD.

Landmark randomized clinical trials on finerenone in chronic kidney disease

Endothelin receptor antagonists

Endothelin receptor antagonists have emerged as novel treatments for a variety of kidney diseases. The Study of Diabetic Nephropathy with Atrasentan (SONAR) evaluated the effect of atrasentan on a composite kidney outcome (defined as a doubling of serum creatinine or ESKD) among adults with type 2 diabetes, estimated GFR 25-75 mL/min/1.73 m 2 , and urine ACR 300-5000 mg/g taking a stable dose of ACE inhibitor or ARB. 120 After a six week enrichment period during which all participants received atrasentan 0.75 mg daily (n=5517), those who responded (defined as a ≥30% reduction in urine ACR without the development of substantial fluid retention or increase in serum creatinine by >0.5 mg/dL and 20% from baseline; n=2648) were randomized to receive atrasentan or placebo. Over a median follow-up of 2.2 years, the atrasentan group had a 35% lower risk of developing the composite kidney outcome compared with the placebo group, although fluid retention and anemia were more frequent in the former. Of note, the frequency of hyperkalemia was low (1%) in both treatment groups. Sparsentan, a dual endothelin and angiotensin II receptor antagonist, is also being investigated as a treatment for FSGS and IgA nephropathy. 121 122 In a phase 2, randomized, double blind, active control trial, 109 adults with biopsy proven FSGS (estimated GFR >30 mL/min/1.73 m 2 and urine PCR ≥1 g/g) received varying doses of sparsentan (200, 400, or 800 mg daily) or irbesartan 300 mg daily. 121 At eight weeks, participants receiving sparsentan had greater reductions in urine PCR compared with those receiving irbesartan. In an interim analysis of the PROTECT phase 3 trial, adults with biopsy proven IgA nephropathy (urine PCR ≥1 g/day) randomized to sparsentan 400 mg daily had a 41% greater reduction in urine PCR over 36 weeks and threefold higher odds of achieving complete remission of proteinuria at any point compared with their counterparts who were randomized to irbesartan 300 mg daily. 122 Based in part on the results of this study, the US Food and Drug Administration (FDA) granted accelerated approval for the use of this drug in adults with primary IgA nephropathy considered to be at risk of rapid disease progression. 123

Endothelin 1 has been implicated in the pathogenesis of kidney disease via various mechanisms including vasoconstriction, vascular hypertrophy, endothelial and podocyte injury, inflammation, cell proliferation, extracellular matrix accumulation, and fibrosis. 124 Systemic and local kidney production of endothelin 1 is augmented in CKD.

Other nephroprotective and cardiovascular risk reduction strategies

A bidirectional association exists between CKD and cardiovascular disease: cardiovascular disease is both a risk factor for CKD and a common outcome in patients with CKD. 125 126 Thus, patients with CKD are likely to benefit from efforts at cardiovascular risk reduction including administration of a statin as well as the gamut of lifestyle changes. 2 127

Lipid management

The Study of Heart and Renal Protection (SHARP) trial evaluated the efficacy of ezetimibe and simvastatin combination therapy in patients with moderate to severe CKD (33% on dialysis; 67% not on dialysis with mean estimated GFR of 27 mL/min/1.73 m 2 ). 128 Treatment with these low density lipoprotein (LDL) cholesterol lowering agents led to a 17% risk reduction for development of a first major atherosclerotic event compared with placebo, although this benefit was seen only in the patients not requiring maintenance dialysis. Those at very high risk (for example, with previous major atherosclerotic cardiovascular disease events) may benefit from additional therapies to lower LDL cholesterol, including evolocumab. 129 Evolocumab is a monoclonal antibody for proprotein convertase subtilisin/kexin type 9, which increases LDL cholesterol receptors and hence clearance of LDL; this novel therapy also seems to be safe and efficacious in patients with CKD. 129 130

Physical activity

Exercise has been shown to benefit patients with CKD. Several small, randomized trials have reported that exercise training programs in patients with moderate to severe CKD are safe, feasible, and effective in improving physical activity levels, cardiorespiratory fitness, and quality of life. 131 132 133 134 135 Whether these interventions also slow CKD progression remains to be determined, as many of these studies were underpowered for this outcome.

For patients with obesity, weight loss may reduce the risk of CKD progression, whether it comes from intensive lifestyle intervention such as in the Look AHEAD (Action for Health in Diabetes) trial or, as in observational studies, from bariatric surgery. 136 137 138 Micronutrient and macronutrient composition of diets may also matter. 139

Traditional recommendations about diet in the setting of CKD have focused on limiting protein and dietary acid intake. Experimental evidence suggests that protein intake can increase intraglomerular pressure and cause glomerular hyperfiltration. 140 141 142 Observational data from large cohort studies suggest that the type of protein may be important; a diet high in animal protein may increase risk, whereas protein from plant sources may be better tolerated. 143 144 For example, an observational study in Singapore found a strong correlation between red meat intake and risk of ESKD. 145 Little clinical trial evidence for protein restriction exists. The MDRD study randomized patients to different levels of protein restriction but found no statistically significant difference in the rate of GFR decline. 67

A second line of investigation has been into the benefits of increasing nutritional alkali intake, with a body of open label trials suggesting benefits on kidney function and prevention of starting dialysis. 146 A phase 3 double blinded, placebo controlled trial reported that veverimer (a potent acid binder that acts in the intestine) was effective in raising or normalizing serum bicarbonate among patients with CKD and chronic metabolic acidosis. 147 Other double blinded studies using veverimer suggested that treating acidosis in CKD improves quality of life and overall physical function. 148 However, a recent trial evaluating veverimer in slowing progression of CKD was negative. 149

Although patients with CKD are prone to hyperkalemia, potassium intake has a beneficial effect on blood pressure, cardiovascular disease, and death independent of and opposite to that of sodium intake. 150 151 152 153 One large randomized controlled trial suggested that substituting 25% of sodium chloride intake with potassium chloride reduced the risk of major adverse cardiovascular events by 13% in the general population. 154 Similarly, small studies suggest that diets rich in potassium may be beneficial in CKD. A feeding trial in people with CKD G3 observed that 100 mmol compared with 40 mmol of dietary potassium per day increased serum potassium by 0.21 mmol/L, 155 similar to the increase seen with finerenone. 156 Many dietary studies have evaluated patterns of diet rather than potassium alone: for example, plant based diets tend to be rich in not only potassium but also alkali and fiber. Observational data from prospective cohorts suggest that plant based diets are associated with less CKD progression. 143 157 158 Evidence is also emerging to suggest that increasing fiber intake benefits the gut microbiome, decreases inflammation, and possibly slows CKD progression. 159

Appropriate drug dosing and nephrotoxin avoidance

An important component of care for patients with CKD is avoidance of additional insults. Many drugs are cleared by glomerular filtration or tubular secretion by the kidney, and reduced GFR can lead to accumulation of the drug or its metabolites resulting in adverse effects. 160 Careful estimation of GFR is generally a first step in determining dosage for renally excreted drugs. 161 The US FDA guidance to industry suggests that estimated GFR based on serum creatinine may be used in pharmacokinetic studies. 162 If drugs are dosed on the basis of estimated GFR (rather than estimated creatinine clearance from the Cockcroft-Gault equation, an equation that is known to be flawed), estimated GFR must be “de-indexed” by multiplying the standardized estimated GFR by the individual’s calculated body surface area and dividing by 1.73 m 2 . 163 164 165 This is because drug clearance is thought to be proportional to a person’s GFR and not the GFR standardized to body surface area. Antibiotics and antiviral agents, direct oral anticoagulants, drugs for diabetes mellitus, and chemotherapeutic agents are the most common drugs that require attention to dosing in CKD. 2 160 164

Some drugs should be avoided or minimized in CKD because of their potential to worsen kidney function. For example, non-steroidal anti-inflammatory drugs (NSAIDs) can exacerbate hypertension, cause fluid retention, and contribute to the risk of acute kidney injury. 166 Particularly when used with RAAS inhibitors and diuretics, NSAIDs are ideally avoided. 167 In select patients with CKD, however, some clinicians will prescribe an abbreviated course of NSAIDs given that the most common alternative, opioids, also have significant adverse effects. 168 Proton pump inhibitors can lead to acute or chronic interstitial nephritis and have been associated with incident CKD, progression of CKD, and ESKD. 169 170 Although the mechanism by which proton pump inhibitors contribute to CKD remains unclear, most experts agree that these agents should be used judiciously.

Emerging treatments

Many phase 3-4 clinical trials are ongoing to evaluate emerging treatments for kidney disease (clinicaltrials.gov). These include, but are not limited to, investigations on the use of dapagliflozin in advanced CKD (for example, estimated GFR <25 mL/min/1.73 m 2 , on maintenance dialysis with residual daily urine output of >500 mL, and kidney transplant recipients with estimated GFR ≤45 mL/min/1.73 m 2 ; NCT05374291 ); finerenone in non-diabetic CKD ( NCT05047263 ); and monteluklast ( NCT05362474 ) and pentoxyifylline ( NCT03625648 ) in diabetic CKD. Several therapies are also being tested for rarer causes of kidney disease: obinutuzumab ( NCT04629248 ), zanubrutinib ( NCT05707377 ), and SNP-ACTH (1-39) gel ( NCT05696613 ) in membranous nephropathy; voclosporin ( NCT05288855 ), atacicept ( NCT05609812 ), anifrolumab ( NCT05138133 ), inanalumab ( NCT05126277 ), secukinumab ( NCT04181762 ), obinutuzumab ( NCT04221477 ), and ACTHar gel ( NCT02226341 ) in lupus nephritis; VX-147 in APOL1 related kidney disease ( NCT05312879 ); imlifidase in antiglomerular basement membrane disease ( NCT05679401 ); sparsentan in focal segmental glomerulosclerosis ( NCT03493685 ); and pegcetacoplan ( NCT05067127 ) in immune complex glomerulonephritis. IgA nephropathy, in particular, is an area of high interest, as recent work suggests that disease activity may be driven by the overproduction of galactose deficient IgA antibodies that are recognized as autoantigens, triggering glomerular deposition of immune complexes. 171 Monoclonal antibodies to signaling molecules that enhance IgA production are in phase 3 trials, as are immunosuppressive and non-immunosuppressive agents (for example, those acting on the endothelin-1 and angiotensin II pathways): budesonide ( NCT03643965 ), sparsentan ( NCT03762850 ), atrasentan ( NCT04573478 ), LNP023 ( NCT04578834 ), RO7434656 ( NCT05797610 ), atacicept ( NCT04716231 ), and sibeprenlimab ( NCT05248646 ; NCT05248659 ).

Major guidelines in CKD are issued by the international KDIGO group ( https://kdigo.org/ ), and locally in the UK by NICE ( www.nice.org.uk/guidance/ng28/chapter/Recommendations#chronic-kidney-disease ), with the most recent issuances primarily from 2023 (currently in public review) and 2021, respectively. KDIGO publishes guidelines on the evaluation and management of patients with CKD in general, as well as myriad other aspects (for example, diabetes, blood pressure, lipids, anemia, mineral and bone disease, hepatitis C, ADPKD, glomerular diseases). With the expansion of therapeutic options, both organizations are updating recommendations frequently. Other guideline producing organizations such as the American College of Cardiology, the American Heart Association, the European Society of Cardiology, the European Society of Hypertension, the International Society of Hypertension, and the American Diabetes Association (ADA) provide more limited statements of recommendation for the specific aspects of the management of patients with CKD. 172 173 174 175

Annual screening for CKD (including testing for albuminuria) is widely recommended in people with diabetes. 72 174 175 176 177 Guidelines in hypertension are less clear. 178 The 2020 Global Hypertension Practice Guideline from the International Society of Hypertension is a notable exception and now recommends routine assessment of albuminuria in addition to estimated GFR in people with hypertension. 173 KDIGO and NICE also recommend testing anyone who is at risk for CKD, which includes those with hypertension, cardiovascular disease, diabetes, and previous acute kidney injury, along with multiple other, less common conditions. 179 For CKD, the KDIGO guidelines recommend at least annual albuminuria testing with greater frequency in higher risk categories ( fig 1 ). 2 The NICE guidelines, on the other hand, recommend annual ACR testing with individualization based on clinical characteristics, risk of progression, and whether a change in ACR would lead to a change in management. 16

KDIGO guidelines and those from NICE differ slightly on staging CKD. KDIGO recommends using a validated equation for GFR estimation and suggests that using “race as a distinct variable in the computation of GFR” is not appropriate. 179 NICE recommends using the CKD-EPI 2009 equation, which did include race, but using the computed value for non-Black people for everyone, a position that is also endorsed by other European groups. 16 180 181 The KDIGO guidelines recommend staging CKD by eGFRcr-cys when cystatin C is available, as well as when precise estimates of GFR are needed for clinical decision making. 2 179 The NICE guidelines recommend direct measurement of GFR rather than the use of cystatin C in clinical situations requiring additional precision. 16

Both KDIGO and NICE emphasize the importance of risk assessment in patients with CKD. The NICE guidelines suggest that primary care providers should counsel patients using the KFRE five year risk estimate, with referral to a specialist if risk is greater than 5%. 16 KDIGO 2023 additionally suggests that the two year risk estimate can drive referral for multidisciplinary care (>10%) and preparation for kidney replacement therapy, including vascular access planning and referral for transplantation (>40%). 179 The KDIGO 2023 guidelines also emphasize the importance of cardiovascular risk assessment using equations developed in people with CKD or that encompasses estimated GFR and albuminuria and the use of disease specific tools in IgA nephropathy and ADPKD. 179

Multiple guidelines comment on target blood pressures in the setting of CKD. The NICE guidelines recommend a target of <140/90 mm Hg, or <130/80 mm Hg if ACR is ≥70 mg/mmol (approximately 700 mg/g). 16 Guidelines from the American College of Cardiology, American Heart Association, European Society of Cardiology, and European Society of Hypertension recommend a systolic blood pressure target of <130 mm Hg as a best practice target, with the European Society of Cardiology and European Society of Hypertension specifically advising against lower targets. 172 The KDIGO guidelines on hypertension in CKD advocate for a systolic blood pressure goal of <120 mm Hg, as assessed using standardized office measurements. 182 This recommendation is based largely on data from SPRINT and the observed benefits in cardiovascular endpoints and survival rather than benefits in kidney endpoints. 70

Of note, disparate guideline recommendations may reflect different emphasis on standardized blood pressure measurement techniques, which can result in measured blood pressure that is substantially lower than measurement in an uncontrolled setting. 183 Joint statements from several international groups including KDIGO stress the importance of proper technique when assessing blood pressure. 184 Both NICE and KDIGO recommend RAAS inhibitors (either ACE inhibitor or ARB) as first line antihypertensive treatment for people without diabetes but with albuminuria (NICE: urine ACR >70 mg/mmol; KDIGO: A3) as well as those with diabetes and CKD G1-G4, A2-A3. 16 182 KDIGO 2023 suggests continuation of RAAS inhibitors even when estimated GFR is <30 mL/min/1.73 m 2 . 179

For patients with diabetes and CKD not treated with dialysis, KDIGO recommends a hemoglobin A 1c target ranging from <6.5% to <8%. 72 NICE does not provide specific recommendations for people with CKD, instead emphasizing shared decision making but a general goal of hemoglobin A 1c <7% for people with diabetes treated with drugs associated with hypoglycemia and <6.5% for people with diabetes managed by lifestyle or a single drug not associated with hypoglycemia. 185

KDIGO and ADA guidelines recommend SGLT-2 inhibitors as first line drug therapy for all people with type 2 diabetes, CKD, and an estimated GFR ≥20 mL/min/1.73 m 2 ( fig 5 ). 72 174 175 179 The NICE guidelines recommend that an SGLT-2 inhibitor should be offered when ACR is >30 mg/mmol (approximately >300 mg/g) and considered when ACR is between 3 and 30 mg/mmol (approximately 30 to 300 mg/g) in patients with type 2 diabetes and CKD who are already taking an ACE inhibitor or ARB and meet estimated GFR thresholds. 185 The NICE guidelines further specify that dapagliflozin should also be considered in people with estimated GFR 25-75 mL/min/1.73 m 2 and ACR ≥22.6 mg/mmol (approximately 200 mg/g) regardless of diabetes status 186 ; KDIGO is broader and recommends SGLT-2 inhibitors in general in people with ACR ≥200 mg/g and estimated GFR ≥20 mL/min/1.73 m 2 , as well as in those with CKD and heart failure. 179 KDIGO further specifies that once started, a SGLT-2 inhibitor can be continued even if the estimated GFR drops below 20 mL/min/1.73 m 2 , as long as it is tolerated and kidney replacement therapy has not yet been started. 72 179 The KDIGO and ADA guidelines recommend the use of GLP-1 receptor agonists in patients with type 2 diabetes and CKD who are unable to tolerate metformin or an SGLT-2 inhibitor or do not meet their individualized glycemic target with these drugs. 72 174 175 179

Kidney Disease: Improving Global Outcomes/American Diabetes Association recommendations on the management of diabetes in populations with chronic kidney disease. 72 174 ACR=albumin-to-creatinine ratio; ASCVD=atherosclerotic cardiovascular disease; BP=blood pressure; CCB=calcium channel blocker; CVD=cardiovascular disease; eGFR=estimated glomerular filtration rate; GLP-1 RA=glucagon-like peptide-1 receptor agonist; HTN=hypertension; MRA=mineralocorticoid receptor antagonist; PCSK9i=proprotein convertase subtilisin/kexin type 9 inhibitor; RAS=renin-angiotensin system; SGLT2i=sodium-glucose cotransporter-2 inhibitor

In patients with diabetes and CKD, the KDIGO and ADA guidelines recommend that finerenone should be used as add-on therapy to maximally tolerated ACE inhibitor or ARB if ACR is ≥30 mg/g (approximately ≥3 mg/mmol) and potassium is within normal limits (that is, ≤4.8 mmol/L based on trial and ≤5.0 mmol/L as per FDA). 72 174 175 179 More specifically, the starting dose should be 10 mg daily when estimated GFR is 25-59 mL/min/1.73 m 2 and 20 mg daily when it is ≥60 mL/min/1.73 m 2 . The guidelines also recommend that potassium concentration should be checked at four weeks after starting treatment, with each dose change, and routinely during treatment. If potassium is >5.5 mmol/L, the drug should be stopped and restarted at the lower dose of 10 mg daily when potassium is ≤5.0 mmol/L. Additionally, finerenone need not be stopped when estimated GFR falls below 25 mL/min/1.73 m 2 as long as the patient is normokalemic. 174 175

With respect to cardiovascular risk reduction, the KDIGO guidelines suggest that all patients aged over 50 with CKD G3-G5 but not treated with chronic dialysis or kidney transplantation should be treated with a statin, irrespective of cholesterol concentrations or a statin/ezetimide combination. 179 187 The NICE recommendation is broader, recommending starting atorvastatin 20 mg for all people with CKD. 188 KDIGO recommends regular physical activity for people with CKD, for at least 150 minutes a week of moderate intensity exercise. 179 NICE simply suggests providing lifestyle advice, including encouragement of exercise, maintenance of healthy weight, and smoking cessation, and specifically recommends against offering low protein diets (defined as dietary protein intake <0.8 g/kg/day). 16 KDIGO recommends maintaining sodium intake <2 g/day and a protein intake of 0.8 g/kg/day but no higher than 1.3 g/kg/day. 179

People with CKD face high risks of many adverse outcomes, including requirement for kidney replacement therapy, cardiovascular events, and death. Fortunately, major advances have been made in the field of CKD over the past decade. Estimating equations for GFR and ACR have evolved for more precise classification of disease. Individualized risk prediction tools exist to assist in the counseling, referral, and treatment of patients. Novel therapies build on the fundamentals—a healthy lifestyle, blood pressure and glucose control, and statin therapy and RAAS blockade—to provide effective preventive strategies for CKD progression and cardiovascular events.

Glossary of abbreviations

ACE—angiotensin converting enzyme

ACR—albumin-to-creatinine ratio

ADA—American Diabetes Association

ADPKD—autosomal dominant polycystic kidney disease

ARB—angiotensin receptor blockers

CKD—chronic kidney disease

CKD-EPI—CKD Epidemiology Collaboration

DPP-4—dipeptidyl peptidase-4

eGFRcr—estimated glomerular filtration rate using creatinine

eGFRcr-cys—estimated glomerular filtration rate using creatinine and cystatin C

eGFRcys—estimated glomerular filtration rate using cystatin C

ESKD—end stage kidney disease

FDA—Food and Drug Administration

FSGS—focal segmental glomerulosclerosis

GFR—glomerular filtration rate

GLP-1—glucagon-like peptide-1

KDIGO—Kidney Disease: Improving Global Outcomes

KFRE—kidney failure risk equation

KFRT—kidney failure with replacement therapy

LDL—low density lipoprotein

MDRD—Modification of Diet in Renal Disease

MRA—mineralocorticoid receptor antagonists

NICE—National Institute for Health and Care Excellence

NSAID—non-steroidal anti-inflammatory drug

PCR—protein-to-creatinine ratio

RAAS—renin-angiotensin-aldosterone system

SGLT-2—sodium-glucose cotransporter-2

Questions for future research

How do the race-free estimating equations perform in global populations?

Where can genetic testing add value in patient care?

Can cause of chronic kidney disease be incorporated into risk prediction tools?

How can medical therapy be best tailored for the individual patient with chronic kidney disease?

Patient perspective

Increasing awareness of chronic kidney disease is key to empowering patients to make lifestyle changes and seek treatments to improve their health outcomes. We are pleased to offer our perspective as husband and wife, and as physicians, who have been affected by kidney disease. Roberta M Falke is a patient with autosomal dominant polycystic kidney disease (ADPKD), a kidney transplant recipient, and a retired hematologist-oncologist. Andrew S Levey is a kidney donor and a nephrologist. Our knowledge of Roberta’s family history enabled early diagnosis and treatment. 189 Although we have benefited from our training and positions in the healthcare system, all patients can benefit from early diagnosis.

RMF —My ADPKD was diagnosed when I developed pyelonephritis at age 22 years. Thereafter, I had prophylaxis and prompt treatment of recurrent urinary tract infections and, as the disease progressed, complications of kidney and liver cysts, hypertension, hyperparathyroidism, vitamin D deficiency, acidosis, hyperkalemia, and ultimately kidney failure, with fatigue, dietary restrictions, and a long list of medications to take every day. I had always known that living donor kidney transplantation would be the best treatment for my kidney failure. Over time, family members without ADPKD donated to others, and when I was ready at age 60 years no family members were available. Fortunately, Andy stepped up. I felt better immediately after the transplant, and in the 13 years since then I have continued to take medications daily but have had few complications. I am grateful to all those who have cared for me for many years and enabled me to make the best choices I could to help myself, and I’m especially grateful to Andy who gave me the gift of life.

ASL —I knew that Roberta would develop kidney failure and hoped that a living kidney donor would be available for her. I wanted to donate, but our blood group incompatibility was an obstacle, so it was exciting when paired donor exchange was conceived and implemented in our region. I believe that kidney donors benefit from donation, not only by fulfilling their spirit of altruism but by improving their own lives. In my case, donating has been life changing. Roberta and I have been able to have an active, fulfilling life for more than a decade after the transplant, without the demands and complications of kidney failure or dialysis. I hope that we will have many more years together. I am also grateful to all those who enabled me to achieve my goal and to Roberta, who always takes full responsibility for caring for her kidney disease.

Acknowledgments

We thank Andrew S Levey and Roberta M Falke for providing both their perspective as patients affected by kidney disease and their input on the manuscript itself. We also acknowledge Alix Rosenberg and Yingying Sang for their help with the boxes and figures.

Series explanation: State of the Art Reviews are commissioned on the basis of their relevance to academics and specialists in the US and internationally. For this reason they are written predominantly by US authors

Contributors: All authors were involved in the conception, writing, and revision of the manuscript. MEG is the guarantor.

Funding: TKC is supported by NIH/NIDDK K08DK117068; MEG is supported by NIH/NIDDK R01DK108803, R01DK100446, R01DK115534, R01DK124399, and NIH/NHLBI K24HL155861.

Competing interests: We have read and understood the BMJ policy on declaration of interests and declare the following interests: TKC and MEG received an honorarium from the American Society of Nephrology (nephSAP).

Patient involvement: We invited a husband and wife, Andrew S Levey and Roberta M Falke, who are affected by chronic kidney disease, to write a patient perspective together. They also reviewed and provided input on the penultimate draft of the paper.

Provenance and peer review: Commissioned; externally peer reviewed.

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• Kidney Disease: Improving Global Outcomes (KDIGO) Lipid Work Group
• ↵ National Institute for Health and Care Excellence. NICE guideline [CG181]: Cardiovascular disease: risk assessment and reduction, including lipid modification. 2023. https://www.nice.org.uk/guidance/cg181/chapter/Recommendations#lipid-modification-therapy-for-the-primary-and-secondary-prevention-of-cardiovascular-disease .

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• Review Article
• Published: 30 July 2020

The current and future landscape of dialysis

• Jonathan Himmelfarb   ORCID: orcid.org/0000-0002-3319-1224 1 , 2 ,
• Raymond Vanholder   ORCID: orcid.org/0000-0003-2633-1636 3 ,
• Rajnish Mehrotra   ORCID: orcid.org/0000-0003-2833-067X 1 , 2 &
• Marcello Tonelli   ORCID: orcid.org/0000-0002-0846-3187 4  

Nature Reviews Nephrology volume  16 ,  pages 573–585 ( 2020 ) Cite this article

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• Haemodialysis
• Health care economics
• Health services
• Medical ethics

The development of dialysis by early pioneers such as Willem Kolff and Belding Scribner set in motion several dramatic changes in the epidemiology, economics and ethical frameworks for the treatment of kidney failure. However, despite a rapid expansion in the provision of dialysis — particularly haemodialysis and most notably in high-income countries (HICs) — the rate of true patient-centred innovation has slowed. Current trends are particularly concerning from a global perspective: current costs are not sustainable, even for HICs, and globally, most people who develop kidney failure forego treatment, resulting in millions of deaths every year. Thus, there is an urgent need to develop new approaches and dialysis modalities that are cost-effective, accessible and offer improved patient outcomes. Nephrology researchers are increasingly engaging with patients to determine their priorities for meaningful outcomes that should be used to measure progress. The overarching message from this engagement is that while patients value longevity, reducing symptom burden and achieving maximal functional and social rehabilitation are prioritized more highly. In response, patients, payors, regulators and health-care systems are increasingly demanding improved value, which can only come about through true patient-centred innovation that supports high-quality, high-value care. Substantial efforts are now underway to support requisite transformative changes. These efforts need to be catalysed, promoted and fostered through international collaboration and harmonization.

The global dialysis population is growing rapidly, especially in low-income and middle-income countries; however, worldwide, a substantial number of people lack access to kidney replacement therapy, and millions of people die of kidney failure each year, often without supportive care.

The costs of dialysis care are high and will likely continue to rise as a result of increased life expectancy and improved therapies for causes of kidney failure such as diabetes mellitus and cardiovascular disease.

Patients on dialysis continue to bear a high burden of disease, shortened life expectancy and report a high symptom burden and a low health-related quality of life.

Patient-focused research has identified fatigue, insomnia, cramps, depression, anxiety and frustration as key symptoms contributing to unsatisfactory outcomes for patients on dialysis.

Initiatives to transform dialysis outcomes for patients require both top-down efforts (that is, efforts that promote incentives based on systems level policy, regulations, macroeconomic and organizational changes) and bottom-up efforts (that is, patient-led and patient-centred advocacy efforts as well as efforts led by individual teams of innovators).

Patients, payors, regulators and health-care systems increasingly demand improved value in dialysis care, which can only come about through true patient-centred innovation that supports high-quality, high-value care.

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Introduction.

Haemodialysis as a treatment for irreversible kidney failure arose from the pioneering efforts of Willem Kolff and Belding Scribner, who together received the 2002 Albert Lasker Clinical Medical Research Award for this accomplishment. Kolff treated his first patient with an artificial kidney in 1943 — a young woman who was dialysed 12 times successfully but ultimately died because of vascular access failure. By 1945, Kolff had dialysed 15 more patients who did not survive, when Sofia Schafstadt — a 67-year-old woman who had developed acute kidney injury — recovered, becoming the first long-term survivor after receipt of dialysis. In 1960, Belding Scribner, Wayne Quinton and colleagues at the University of Washington, WA, USA, designed shunted cannulas, which prevented the destruction of blood vessels and enabled repeated haemodialysis sessions. The first patient who received long-term treatment (named Clyde Shields) lived a further 11 years on haemodialysis. In their writings, both Kolff and Scribner eloquently described being motivated by their perception of helplessness as physicians who had little to offer for the care of young patients who were dying of uraemia and stated that the goal of dialysis was to achieve full rehabilitation to an enjoyable life 1 .

The potential to scale the use of dialysis to treat large numbers of patients with kidney failure created great excitement. At the 1960 meeting of the American Society for Artificial Internal Organs (ASAIO), Scribner introduced Clyde Shields to physicians interested in dialysis, and Quinton demonstrated fabrication of the shunt. The following decade saw rapid gains in our understanding of kidney failure, including the discovery of uraemia-associated atherogenesis and metabolic bone disease, and in virtually every aspect of haemodialysis, including improvements in dialyser technology, dialysate composition, materials for haemocompatibility and water purification systems. The Scribner–Quinton shunt rapidly became an historical artefact once Brescia and colleagues developed the endogenous arteriovenous fistula in 1966 (ref. 2 ), and prosthetic subcutaneous interpositional ‘bridge’ grafts were developed shortly thereafter. Concomitant with these pioneering efforts, in 1959, peritoneal dialysis (PD) was first used successfully to sustain life for 6 months. Within 2 years a long-term PD programme was established in Seattle, WA, USA, and within 3 years the first automated PD cycler was developed 3 .

In 1964, Scribner’s presidential address to the ASAIO described emerging ethical issues related to dialysis, including considerations for patient selection, patient self-termination of treatment as a form of suicide, approaches to ensure death with dignity and selection criteria for transplantation 4 . Indeed, the process of selecting who would receive dialysis contributed to the emergence of the field of bioethics. The early success of dialysis paradoxically created social tensions, as access to this life-sustaining therapy was rationed by its availability and the ‘suitability’ of patients. In the early 1970s, haemodialysis remained a highly specialized therapy, available to ~10,000 individuals, almost exclusively in North America and Europe, with a high frequency of patients on home haemodialysis. In a portentous moment, Shep Glazer, an unemployed salesman, was dialysed in a live demonstration in front of the US Congress House Ways and Means Committee. Soon thereafter, in October 1972, an amendment to the Social Security Act creating Medicare entitlement for end-stage renal disease (now known as kidney failure), for both dialysis and kidney transplantation, was passed by Congress and signed into law by President Nixon.

The resulting expansion of dialysis, previously described as “from miracle to mainstream” 5 , set in motion dramatic changes 6 , including the development of a for-profit outpatient dialysis provider industry; relaxation of stringent patient selection for dialysis eligibility in most HICs; a move away from home towards in-centre dialysis; efforts on the part of single payors such as Medicare in the USA to restrain per-patient costs through the introduction of bundled payments and the setting of composite rates; the development of quality indicators — such as adequate urea clearance per treatment — that were readily achievable but are primarily process rather than outcome measures; consolidation of the dialysis industry, particularly in the USA owing to economies of scale, eventually resulting in a duopoly of dialysis providers; the development of joint ventures and other forms of partnerships between dialysis providers and nephrologists; the globalization of dialysis, which is now available, albeit not necessarily accessible or affordable in many low-income and middle-income countries (LMICs); and finally, a dramatic slowing in the rate of true patient-centred innovation, with incremental gains in dialysis safety and efficiency replacing the pioneering spirit of the early innovators.

The population of patients receiving dialysis continues to grow rapidly, especially in LMICs, as a result of an increase in the availability of dialysis, population ageing, increased prevalence of hypertension and diabetes mellitus, and toxic environmental exposures. However, despite the global expansion of dialysis, notable regional differences exist in the prevalence of different dialysis modalities and in its accessibility. Worldwide, a substantial number of people do not have access to kidney replacement therapy (KRT), resulting in millions of deaths from kidney failure each year. Among populations with access to dialysis, mortality remains high and outcomes suboptimal, with high rates of comorbidities and poor health-related quality of life. These shortcomings highlight the urgent need for innovations in the dialysis space to increase accessibility and improve outcomes, with a focus on those that are a priority to patients. This Review describes the current landscape of dialysis therapy from an epidemiological, economic, ethical and patient-centred framework, and provides examples of initiatives that are aimed at stimulating innovations in dialysis and transform the field to one that supports high-quality, high-value care.

Epidemiology of dialysis

Kidney failure is defined by a glomerular filtration rate <15 ml/min/1.73 m 2 (ref. 7 ) and may be treated using KRT (which refers to either dialysis or transplantation) or with supportive care 8 . The global prevalence of kidney failure is uncertain, but was estimated to be 0.07%, or approximately 5.3 million people in 2017 (ref. 9 ), with other estimates ranging as high as 9.7 million. Worldwide, millions of people die of kidney failure each year owing to a lack of access to KRT 10 , often without supportive care. Haemodialysis is costly, and current recommendations therefore suggest that haemodialysis should be the lowest priority for LMICs seeking to establish kidney care programmes. Rather, these programmes should prioritize other approaches, including treatments to prevent or delay kidney failure, conservative care, living donor kidney transplantation and PD 11 . Nonetheless, haemodialysis is the most commonly offered form of KRT in LMICs, as well as in high-income countries (HICs) 12 , and continued increases in the uptake of haemodialysis are expected worldwide in the coming decades. Here, we review the basic epidemiology of kidney failure treated with long-term dialysis and discuss some of the key epidemiological challenges of the future (Fig.  1a ).

Growth is continuously outpacing the capacity of kidney replacement therapy (KRT), defined as maintenance dialysis or kidney transplant, especially in low-income and middle-income countries. a | Global prevalence of chronic dialysis. b | Estimated worldwide need and projected capacity for KRT by 2030. pmp, per million population. Adapted with permission from the ISN Global Kidney Health Atlas 2019.

Prevalence of dialysis use

Prevalence of haemodialysis.

Worldwide, approximately 89% of patients on dialysis receive haemodialysis; the majority (>90%) of patients on haemodialysis live in HICs or the so-called upper middle-income countries such as Brazil and South Africa 12 , 13 . The apparent prevalence of long-term dialysis varies widely by region but correlates strongly with national income 14 . This variation in prevalence in part reflects true differences in dialysis use 12 , 15 but also reflects the fact that wealthier countries are more likely than lower income countries to have comprehensive dialysis registries. Of note, the prevalence of haemodialysis is increasing more rapidly in Latin America (at a rate of ~4% per year) than in Europe or the USA (both ~2% per year), although considerable variation between territories exists in all three of these regions, which again correlates primarily (but not exclusively) with wealth 16 , 17 . The prevalence of haemodialysis varies widely across South Asia, with relatively high prevalence (and rapid growth) in India and lower prevalence in Afghanistan and Bangladesh 18 . Limited data are available on the prevalence of dialysis therapies in sub-Saharan Africa 19 . A 2017 report suggests that haemodialysis services were available in at least 34 African countries as of 2017, although haemodialysis was not affordable or accessible to the large majority of resident candidates 13 .

Prevalence of peritoneal dialysis

Worldwide, PD is less widely available than haemodialysis. In a 2017 survey of 125 countries, PD was reportedly available in 75% of countries whereas haemodialysis was available in 96% 20 . In 2018, an estimated 11% of patients receiving long-term dialysis worldwide were treated with PD; a little over half of these patients were living in China, Mexico, the USA and Thailand 21 .

Large variation exists between territories in the relative use of PD for treating kidney failure; in Hong Kong for example, >80% of patients on dialysis receive PD, whereas in Japan this proportion is <5% 22 . This variation is, in part, determined by governmental policies and the density of haemodialysis facilities 23 . In some countries such as the USA, rates of PD utilization also vary by ethnicity with African Americans and Hispanics being much less likely than white Americans to receive PD 24 . Disparate secular trends in PD use are also evident, with rapid growth in the use of PD in some regions such as the USA, China and Thailand and declining or unchanging levels of PD use in other regions, for example, within Western Europe 22 . As for haemodialysis, access to PD is poor in many LMICs for a variety of reasons, as comprehensively discussed elsewhere 25 .

Incidence of dialysis use

Following a rapid increase in dialysis use over a period of approximately two decades, the incidence of dialysis initiation in most HICs reached a peak in the early 2000s and has remained stable or slightly decreased since then 22 , 26 , 27 . Extrapolation of prevalence data from LMICs suggests that the incidence of dialysis initiation seems to be steadily increasing in LMICs 10 , 28 , 29 , 30 , with further increases expected over the coming decades. However, incidence data in LMICs are less robust than prevalence data, although neither reflect the true demand for KRT given the lack of reporting.

Of note, the incidence of dialysis initiation in HICs is consistently 1.2-fold to 1.4-fold higher for men than for women, despite an apparently higher risk of chronic kidney disease (CKD) in women 31 . Whether this finding reflects physician or health system bias, different preferences with regard to KRT, disparities in the competing risk of death, variation in rates of kidney function loss in women versus men, or other reasons is unknown and requires further study. Few data describe the incidence of haemodialysis by sex in LMICs.

Dialysis outcomes

Mortality is very high among patients on dialysis, especially in the first 3 months following initiation of haemodialysis treatment. Approximately one-quarter of patients on haemodialysis die within a year of initiating therapy in HICs, and this proportion is even higher in LMICs 32 , 33 , 34 . Over the past two decades, reductions in the relative and absolute risk of mortality have seemingly been achieved for patients on haemodialysis. Data suggest that relative gains in survival may be greater for younger than for older individuals; however, absolute gains seem to be similar across age groups 35 . Although controversial, improvements in mortality risk seem to have been more rapid among patients on dialysis than for the general population 36 , suggesting that better care of patients receiving dialysis treatments rather than overall health gains might be at least partially responsible for these secular trends. The factors responsible for these apparent trends have not been confirmed, but could include better management of comorbidities, improvements in the prevention or treatment of dialysis-related complications such as infection, and/or better care prior to the initiation of dialysis (which may translate into better health following dialysis initiation). Historically, although short-term mortality was lower for patients treated with PD than for those treated with haemodialysis, the long-term mortality risk was higher with PD 37 , 38 . In the past two decades, the reduction in mortality risk has been greater for patients treated with PD than with haemodialysis, such that in most regions the long-term survival of patients treated with PD and haemodialysis are now similar 39 , 40 , 41 .

Despite these improvements, mortality remains unacceptably high among patients on dialysis and is driven by cardiovascular events and infection. For example, a 2019 study showed that cardiovascular mortality among young adults aged 22–29 years with incident kidney failure was 143–500-fold higher than that of otherwise comparable individuals without kidney failure, owing to a very high burden of cardiovascular risk factors 42 . The risk of infection is also markedly greater among patients on dialysis than in the general population, in part driven by access-related infections in patients on haemodialysis with central venous catheters and peritonitis-related infections in patients on PD 43 , 44 , 45 , 46 , 47 . Hence, strategies to reduce the risk of infection associated with dialysis access should continue to be a high clinical priority.

The risk of mortality among patients on dialysis seems to be influenced by race. In the USA, adjusted mortality is lower for African American patients than for white patients on dialysis, although there is a significant interaction with age such that this observation held only among older adults, and the converse is actually true among younger African American patients aged 18 to 30 years 48 . A similar survival advantage is observed among Black patients compared with white patients or patients of Asian heritage on haemodialysis in the Netherlands 49 . In Canada, dialysis patients of indigenous descent have higher adjusted mortality, and patients of South Asian or East Asian ethnicity have lower adjusted mortality than that of white patients. In addition, between-region comparisons indicate that mortality among incident dialysis patients is substantially lower for Japan than for other HICs. Whether this difference is due to ethnic origin, differences in health system practices, a combination of these factors or other, unrelated factors is unknown 30 . No consistent evidence exists to suggest that mortality among incident adult dialysis patients varies significantly by sex 50 , 51 , 52 .

Other outcomes

Hospitalization, inability to work and loss of independent living are all markedly more common among patients on dialysis than in the general population 53 , 54 , 55 . In contrast to the modest secular improvements in mortality achieved for patients on dialysis, health-related quality of life has remained unchanged for the past two decades and is substantially lower than that of the general population, due in part to high symptom burden 56 , 57 , 58 , 59 . Depression is also frequent among patients on dialysis 60 , and factors such as high pill burden 61 , the need to travel to dialysis sessions and pain associated with vascular access puncture all affect quality of life 62 .

Future epidemiological challenges

The changing epidemiology of kidney failure is likely to present several challenges for the optimal management of these patients. For example, the ageing global population together with continuing increases in the prevalence of key risk factors for the development of kidney disease, such as diabetes mellitus and hypertension, mean that the incidence, prevalence and costs of kidney failure will continue to rise for the foreseeable future. This increased demand for KRT will undoubtedly lead to an increase in the uptake of haemodialysis, which will pose substantial economic challenges for health systems worldwide. Moreover, as growth in demand seems to be outpacing increases in KRT capacity, the number of deaths as a result of kidney failure is expected to rise dramatically (Fig.  1b ).

The same risk factors that drive the development of kidney disease will also increase the prevalence of multimorbidities within the dialysis population. These comorbidities will in turn require effective management in addition to the management of kidney failure per se 63 and will require technical innovations of dialysis procedures, as well as better evidence to guide the management of comorbidities in the dialysis population.

Finally, the particularly rapid increases in the incidence and prevalence of kidney failure among populations in LMICs will place considerable strain on the health systems of these countries. The associated increases in mortality resulting from a lack of access to KRT will create difficult choices for decision makers. Although LMIC should prioritize forms of KRT other than haemodialysis, some haemodialysis capacity will be required 11 , for example, to manage patients with hypercatabolic acute kidney injury or refractory PD-associated peritonitis, which, once available, will inevitably increase the use of this modality.

Health economy-related considerations

The cost of dialysis (especially in-centre or in-hospital dialysis) is high 64 , and the cost per quality-adjusted life-year associated with haemodialysis treatment is often considered to be the threshold value that differentiates whether a particular medical intervention is cost-effective or not 65 . Total dialysis costs across the population will probably continue to rise, owing to increases in life expectancy of the general population and the availability of improved therapeutics for causes of kidney failure such as diabetes mellitus, which have increased the lifespan of these patients and probably will also increase their lifespan on dialysis. KRT absorbs up to 5–7% of total health-care budgets, despite the fact that kidney failure affects only 0.1–0.2% of the general population in most regions 66 . Although societal costs for out-of-centre dialysis (for example, home or self-care haemodialysis, or PD) are in general lower than that of in-centre haemodialysis in many HICs, these options are often underutilized 67 , adding to the rising costs of dialysis.

Reimbursement for haemodialysis correlates with the economic strength of each region 68 , but in part also reflects willingness to pay . In most regions, the correlation curve for PD or reimbursement with respect to gross domestic product projects below that of in-centre haemodialysis, which in part reflects the lower labour costs associated with PD 68 . Unfortunately, little clarity exists with regard to the aggregated cost of single items that are required to produce dialysis equipment for both PD and haemodialysis and the labour costs involved in delivering haemodialysis 69 , which makes it difficult for governments to reimburse the real costs of haemodialysis.

Although increasing reimbursement of home dialysis strategies would seem to be an appropriate strategy to stimulate uptake of these modalities, evidence from regions that offer high reimbursement rates for PD suggests that the success of this strategy is variable 23 , 68 . However, financial incentives may work. In the USA, reimbursement for in-centre and home dialysis (PD or home haemodialysis) has for a long time been identical. The introduction of the expanded prospective payment system in 2011 further enhanced the financial incentives for PD for dialysis providers, which led to a doubling in both the absolute number of patients and the proportion of patients with kidney failure treated with PD 70 , 71 , 72 , 73 .

Although in countries with a low gross domestic product, dialysis consumes less in absolute amounts, it absorbs a higher fraction of the global health budget 68 , likely at the expense of other, potentially more cost-effective interventions, such as prevention or transplantation. Although society carries most of the costs associated with KRT in most HICs, some costs such as co-payment for drugs or consultations are borne by the individual, and these often increase as CKD progresses. In other regions, costs are covered largely or entirely by the patient’s family, leading to premature death when resources are exhausted 74 . In addition, costs are not limited to KRT but also include the costs of medication, hospitalizations and interventions linked to kidney disease or its complications (that is, indirect costs), as well as non-health-care-related costs such as those linked to transportation or loss of productivity.

Dialysis also has an intrinsic economic impact. Patients on dialysis are often unemployed. In the USA, >75% of patients are unemployed at the start of dialysis, compared with <20% in the general population 53 . Unemployment affects purchasing power but also lifestyle, self-image and mental health. Moreover, loss of productivity owing to unemployment and/or the premature death of workers with kidney failure also has economic consequences for society 75 . Therefore, continued efforts to prevent kidney failure and develop KRT strategies that are less time consuming for the patient and allow more flexibility should be an urgent priority. Concomitantly, employers must also provide the resources needed to support employees with kidney failure.

Hence, a pressing need exists to rethink the current economic model of dialysis and the policies that direct the choice of different treatment options. The cost of dialysis (especially that of in-centre haemodialysis) is considerable and will continue to rise as the dialysis population increases. Maintaining the status quo will prevent timely access to optimal treatment for many patients, especially for those living in extreme poverty and with a low level of education and for patients living in LMICs.

Ethical aspects

A 2020 review by a panel of nephrologists and ethicists appointed by three large nephrology societies outlined the main ethical concerns associated with kidney care 76 . With regard to management of kidney failure (Box  1 ), equitable access to appropriate treatment is probably the most important ethical issue and is relevant not only in the context of haemodialysis but also for the other modalities of kidney care (including transplantation, PD and comprehensive conservative care) 76 . Of note, conservative care is not equivalent to the withdrawal of treatment, but rather implies active management excluding KRT.

As mentioned previously, access to such care is limited in many countries 10 , 77 . Inequities in access to dialysis at the individual level are largely dependent on factors such as health literacy, education and socio-economic status, but also on the wealth and organization of the region in which the individual lives. Even when dialysis itself is reimbursed, a lack of individual financial resources can limit access to care. Moreover, elements such as gender, race or ethnicity and citizenship status 78 , 79 can influence an individual’s ability to access dialysis 80 . These factors impose a risk that patients who are most vulnerable are subject to further discrimination. In addition, without necessarily being perceived as such, dialysis delivery may be biased by the financial interests of dialysis providers or nephrologists, for example, by influencing whether a patient receives in-centre versus home dialysis, or resulting in the non-referral of patients on dialysis for transplantation or conservative care 81 , 82 .

A potential reason for the high utilization of in-centre haemodialysis worldwide is a lack of patient awareness regarding the alternatives. When surveyed, a considerable proportion of patients with kidney failure reported that information about options for KRT was inadequate 83 , 84 . Patient education and decision support could be strengthened and its quality benchmarked, with specific attention to low health literacy, which is frequent among patients on dialysis 85 . Inadequate patient education might result from a lack of familiarity with home dialysis (including PD) and candidacy bias among treating physicians and nurses. Appropriate education and training of medical professionals could help to solve this problem. However, the first step to increase uptake of home dialysis modalities is likely policy action undertaken by administrations, but stimulated by advocacy by patients and the nephrology community, as suggested by the higher prevalence of PD at a lower societal cost of regions that already have a PD-first policy in place 68 .

Although the provision of appropriate dialysis at the lowest possible cost to the individual is essential if access is to be improved 86 , approaches that unduly compromise the quality of care should be minimized or avoided. General frameworks to deal with this challenge can be provided by the nephrology community, but trade-offs between cost and quality may be necessary and will require consultation between authorities, medical professionals and patient representatives. Consideration must also be given to whether the societal and individual impact of providing dialysis would be greater than managing other societal health priorities (for example, malaria or tuberculosis) or investing in other sectors to improve health (for example, access to clean drinking water or improving road safety).

The most favourable approach in deciding the most appropriate course of action for an individual is shared decision-making 87 , which provides evidence-based information to patients and families about all available therapeutic options in the context of the local situation. Providing accurate and unbiased information to support such decision-making is especially relevant for conservative care, to avoid the perception that this approach is being recommended to save resources rather than to pursue optimal patient comfort. Properly done, shared decision-making should avoid coercion, manipulation, conflicts of interest and the provision of ‘futile dialysis’ to a patient for whom the harm outweighs the benefits, life expectancy is low or the financial burden is high 88 . However, the views of care providers do not always necessarily align with those of patients and their families, especially in multicultural environments 89 . Medical professionals are often not well prepared for shared decision-making, and thus proper training is essential 90 . Policy action is also required to create the proper ethical consensus and evidence-based frameworks at institutional and government levels 91 to guide decision-making in the context of dialysis care that can be adapted to meet local needs.

Box 1 Main ethical issues in dialysis

Equity in access to long-term dialysis

Inequities in the ability to access kidney replacement therapy exist worldwide; however, if dialysis is available, the ability to transition between different dialysis modalities should be facilitated as much as possible. Specific attention should be paid to the factors that most prominently influence access to dialysis, such as gender, ethnicity, citizenship status and socio-economic status

Impact of financial interests on dialysis delivery

Financial interests of dialysis providers or nephrologists should in no way influence the choice of dialysis modality and/or result in the non-referral of patients for transplantation or conservative care

Cost considerations

Local adaptations are needed to ensure that the costs of dialysis provision are as low as possible without compromising quality of care

The high cost of dialysis means that consideration must be given to whether the benefits obtained by dialysis outweigh those obtained by addressing other health-care priorities, such as malaria or tuberculosis

Shared decision-making

Shared decision-making, involving the patient and their family, is recommended as an approach to allow an informed choice of the most appropriate course to follow

Approaches to shared decision-making must be evidence based and adapted to local circumstances

Futile dialysis should be avoided

Proper training is required to prepare physicians for shared decision-making

Clinical outcomes to measure progress

Over the past six decades, the availability of long-term dialysis has prolonged the lives of millions of people worldwide, often by serving as a bridge to kidney transplantation. Yet, patients on dialysis continue to bear a high burden of disease, both from multimorbidity and owing to the fact that current dialysis modalities only partially replace the function of the native kidney, resulting in continued uraemia and its consequences. Thus, although dialysis prevents death from kidney failure, life expectancy is often poor, hospitalizations (particularly for cardiovascular events and infection) are frequent, symptom burden is high and health-related quality of life is low 22 , 92 , 93 .

Given the multitude of health challenges faced by patients on dialysis, it is necessary to develop a priority list of issues. For much of the past three decades, most of this prioritization was performed by nephrology researchers with the most effort to date focusing on approaches to reducing all-cause mortality and the risk of fatal and non-fatal cardiovascular events. However, despite the many interventions that have been tested, including increasing the dose of dialysis (in the HEMO and ADEMEX trials 94 , 95 ), increasing dialyser flux (in the HEMO trial and MPO trial 94 , 96 ), increasing haemodialysis frequency (for example, the FHN Daily and FHN Nocturnal trials 97 , 98 ), use of haemodiafiltration (the CONTRAST 99 , ESHOL 100 and TURKISH-OL-HDF trials 101 ), increasing the haemoglobin target (for example, the Normal Haematocrit Trial 102 ), use of non-calcium-based phosphate binders (for example, the DCOR trial 103 ), or lowering of the serum cholesterol level (for example, the 4D, AURORA and SHARP trials 104 , 105 , 106 ), none of these or other interventions has clearly reduced all-cause or cardiovascular mortality for patients on dialysis. These disappointments notwithstanding, it is important that the nephrology community perseveres in finding ways to improve patient outcomes.

In the past 5 years, nephrology researchers have increasingly engaged with patients to understand their priorities for meaningful outcomes that should be used to measure progress. The overarching message from this engagement is that although longevity is valued, many patients would prefer to reduce symptom burden and achieve maximal functional and social rehabilitation. This insight highlights the high symptom burden experienced by patients receiving long-term dialysis 92 , 93 , 96 , 107 . These symptoms arise as a consequence of the uraemic syndrome. Some of these symptoms, such as anorexia, nausea, vomiting, shortness of breath and confusion or encephalopathy, improve with dialysis initiation 108 , 109 , 110 , but many other symptoms, such as depression, anxiety and insomnia do not. Moreover, other symptoms, such as post-dialysis fatigue, appear after initiation of haemodialysis.

Of note, many symptoms of uraemic syndrome might relate to the persistence of protein-bound uraemic toxins and small peptides (so-called middle molecules) that are not effectively removed by the current dialysis modalities. The development of methods to improve the removal of those compounds is one promising approach to improving outcomes and quality of life for patients on dialysis, as discussed by other articles in this issue.

Patients on dialysis report an average of 9–12 symptoms at any given time 92 , 93 , 107 . To determine which of these should be prioritized for intervention, the Kidney Health Initiative used a two-step patient-focused process involving focus groups and an online survey to identify six symptoms that should be prioritized by the research community for intervention. These include three physical symptoms (fatigue, insomnia and cramps) and three mood symptoms (depression, anxiety and frustration) 111 . Parallel to these efforts, the Standardizing Outcomes in Nephrology Group (SONG) workgroup for haemodialysis ( SONG-HD ) has identified several tiers of outcomes that are important to patients, caregivers and health-care providers. Fatigue was identified as one of the four core outcomes, whereas depression, pain and feeling washed out after haemodialysis were identified as middle-tier outcomes 112 , 113 , 114 . Along these same lines, the SONG workgroup for PD ( SONG-PD ) identified the symptoms of fatigue, PD pain and sleep as important middle-tier outcomes 115 , 116 . Despite the importance of these symptoms to patients on dialysis, only a few studies have assessed the efficacy of behavioural and pharmacological treatments on depression 117 , 118 , 119 , 120 , 121 . Even more sobering is the observation that very few, if any, published studies have rigorously tested interventions for fatigue or any of the other symptoms. The nephrology community must now develop standardized and psychometrically robust measures that accurately capture symptoms and outcomes that are important to patients and ensure that these are captured in future clinical trials 122 , 123 .

Approaches to maximizing functional and social rehabilitation are also important to patients with kidney failure. In addition to the above-mentioned symptoms, SONG-HD identified ability to travel, ability to work, dialysis-free time, impact of dialysis on family and/or friends and mobility as important middle-tier outcomes 112 , 113 , 114 . SONG-PD identified life participation as one of five core outcomes, and impact on family and/or friends and mobility as other outcomes that are important to patients 115 , 116 . Given the importance of these outcomes to stakeholders, including patients, it is imperative that nephrology researchers develop tools to enable valid and consistent measurement of these outcomes and identify interventions that favourably modify these outcomes.

Fostering innovation

As described above, the status quo of dialysis care is suboptimal. Residual symptom burden, morbidity and mortality, and economic cost are all unacceptable, which begs the question of what steps are needed to change the established patterns of care. Patients are currently unable to live full and productive lives owing to the emotional and physical toll of dialysis, its intermittent treatment schedule, the dietary and fluid limitations, and their highly restricted mobility during treatment. Current technology requires most patients to travel to a dialysis centre, and current modalities are non-physiological, resulting in ‘washout’, which is defined as extensive fatigue, nausea and other adverse effects, caused by the build-up of uraemic toxins between treatments and the rapid removal of these solutes and fluids over 4-h sessions in the context of haemodialysis. LMICs face additional difficulties in the provision of dialysis owing to infrastructural requirements, the high cost of this treatment, the need for a constant power supply and the requirement for high volumes of purified water. For LMICs, innovations that focus on home-based, low-cost therapies that promote rehabilitation would be especially beneficial.

We contend that initiatives to transform dialysis outcomes for patients require both top-down efforts (for example, those that involve systems changes at the policy, regulatory, macroeconomic and organizational levels) and bottom-up efforts (for example, patient-led and patient-centred advocacy and individual teams of innovators). Top-down efforts are required to support, facilitate and de-risk the work of innovators. Conversely, patient-led advocacy is essential for influencing governmental and organizational policy change. Here, by considering how selected programmes are attempting to transform dialysis outcomes through innovation in support of high-value, high-quality care, we describe how top-down and bottom-up efforts can work synergistically to change the existing ecosystem of dialysis care (Fig.  2 ). The efforts described below are not an exhaustive list; rather, this discussion is intended to provide a representative overview of how the dialysis landscape is changing. Additional articles in this issue describe in more detail some of the bottom-up efforts of innovators to create wearable 124 , portable 125 , more environmentally friendly 126 and more physiological dialysis systems 127 , 128 , priorities from the patients’ perspective 129 , and the role of regulators in supporting innovation in the dialysis space 130 .

Initiatives to transform dialysis outcomes for patients require both top-down efforts (for example, those that involve systems-level changes at the policy, regulatory, macroeconomic and organizational level) and bottom-up efforts (for example, patient-led and patient-centred advocacy efforts and efforts from individual teams of innovators). Both of these efforts need to be guided by priorities identified by patients. Such an approach, focused on patient-centred innovation, has the potential to result in meaningful innovations that support high-quality, high-value care. NGOs, non-governmental organizations.

The Kidney Health Initiative

In 2012, the American Society of Nephrology (ASN) and the FDA established the KHI as an umbrella organization through which the kidney community can work collaboratively to remove barriers to the development of innovative drugs, devices, biologics and food products, in order to improve outcomes for people living with kidney diseases. To advance its mission, KHI has initiated a number of projects composed of multidisciplinary workgroups. A major accomplishment for the KHI was the establishment of a precompetitive environment to promote innovation while ensuring patient safety.

The KHI is the largest consortium in the kidney community, with over 100 member organizations including patient groups, health professional organizations, dialysis organizations, pharmaceutical and device companies, and government agencies. During the first 7 years of its existence, the KHI has launched and in many cases completed projects that have facilitated the development of new therapeutic options for dialysis patients (Box  2 ), as well as published position papers on topics relevant to innovation in haemodialysis care, including innovations in fluid management 131 and symptom management 132 in patients on haemodialysis, recommendations for clinical trial end points for vascular access 133 , perspectives on pragmatic trials in the haemodialysis population 134 and regulatory considerations for the use of haemodiafiltration 135 .

Box 2 Kidney Heath Initiative Projects that Support Dialysis Innovation

Patient and Family Partnership Council

Since 2015, the Kidney Health Initiative (KHI) Patient and Family Partnership Council (PFPC) has helped KHI stakeholders to engage and network with patients and patient organizations. The PFPC also advises industry and research partners of patient needs and preferences as new products are planned and developed. The PFPC continually emphasizes that innovation will only be successful if built around the needs of people with kidney disease and focused on improving their quality of life.

ESRD Data Standard Project

The aim of this project is to create a harmonized common data standard for kidney failure. The availability of a uniform data standard could accelerate the pace of scientific discovery, facilitate the creation of scientific registries for epidemiological surveillance and allow the development of common metrics for value-based health care.

Building Capacity to Incorporate Patient Preferences into the Development of Innovative Alternatives to kidney replacement therapy (KRT)

This project, which is supported by a 3-year contract with the FDA, is based on the premise that access to scientifically valid patient preference information could positively inform the decisions of industry and regulators as they design and review new devices for individuals with kidney failure. This project will collect patients’ preference information and also address a stated goal of the Advancing American Kidney Health (AAKH) initiative, which instructs the FDA to “develop a new survey to gain insight into patient preferences for new kidney failure treatments” 137 .

Clinical Trial Design to Support Innovative Approaches to KRT

This project is intended to facilitate coordinated efforts between regulators and the nephrology community to streamline the clinical development pathway. The primary objectives of the project are to define terminology for future KRT products (for example, wearable, portable, implantable and artificial kidney) and identify the most appropriate trial designs and end points for a variety of KRT products.

Advancing American Kidney Health

In July 2019, President Donald Trump signed an Executive Order on Advancing American Kidney Health (AAKH) 136 , which promises to fundamentally change the clinical care of kidney disease in general and kidney failure in particular. Components of the AAKH that are relevant to dialysis care include a directive for education and support programmes to promote awareness of kidney disease; a shift in the focus of reimbursement initiatives from in-centre haemodialysis to home therapies, transplantation and upstream CKD care; a system that rewards clinicians and dialysis facilities for providing a range of treatments for kidney failure, with the aim of increasing uptake of home dialysis and transplantation; and incentives for nephrology care teams to focus on reducing costs and improving outcomes by providing longitudinal care of patients with kidney disease.

Finally, and perhaps most radically, the AAKH calls on the US Department of Health and Human Services to support premarket approval of wearable and implantable artificial kidneys and welcomes other strategies to facilitate transformative innovation in dialysis devices. The AAKH directive specifically identifies the KidneyX programme (described below) as the vehicle with which to drive this innovation. The AAKH is the most ambitious US policy initiative ever undertaken to transform the care of patients with advanced kidney disease. Its agenda is still being shaped by the federal governmental agencies, with input from professional societies and other kidney community stakeholders, but this initiative provides a framework and support for transformative innovation in dialysis care.

The KHI Technology Roadmap and KidneyX

The KHI Technology Roadmap for Innovative Approaches to KRT, published in 2019 (ref. 137 ), is aimed at supporting the development of innovative dialysis devices by providing guidance on technical criteria, patient preferences, assessment of patient risk tolerances and regulatory, reimbursement and marketing considerations. Key strengths of the Roadmap include its patient-centred focus and the description of multiple solution pathways for different technologies (for example, portable, wearable and implantable devices that may be purely mechanical, cell-based or hybrid systems), each with appropriate timeline projections.

The KRT Roadmap was designed to be complementary to the Kidney Innovation Accelerator (also known as KidneyX). KidneyX is a public–private partnership between the Department of Health and Human Services and the ASN, and is aimed at accelerating the development of drugs, devices, biologics and other therapies across the spectrum of kidney care. The current major focus of KidneyX is to catalyse the fundamental redesign of dialysis, supported by a series of competitions. Phase I prizes focused on innovations in biomaterials, novel biosensors and safety monitors used for haemodialysis, as well as approaches for improved vascular access and the development of novel technologies that replicate kidney function more precisely than conventional dialysis. Phase II focuses on strategies to build and test prototype solutions or components of solutions that can replicate normal kidney function or improve haemodialysis access. KidneyX has also awarded a series of Patient Innovator Challenge prizes to patients who have proposed innovative solutions to problems emanating from their everyday experiences with kidney disease, including approaches to monitoring blood electrolyte levels and increasing the accessibility of patient education resources.

Dutch Kidney Foundation and Neokidney

The Dutch Kidney Foundation (DKF; or Nierstichting Nederland ) was founded in 1968. It supports research into the causes, prevention and treatment of kidney failure. Furthermore, it works to improve the quality of dialysis treatment and increase the number of kidney transplants. All projects are planned and organized with considerable patient involvement. The DKF also offers financial support to kidney research projects by large Dutch multi-centric consortia. These projects not only promote innovation in the Netherlands but also support trans-national European Union (EU)-supported projects with Dutch participation or leadership, such as Horizon 2020 and Horizon Europe.

Neokidney is a partnership between the DKF and several companies that specialize in miniaturization of dialysis equipment (including dialysis pumps) and sorbent technology for dialysate regeneration. This partnership is aimed at developing a small, portable haemodialysis device that will enable more frequent dialysis sessions, permit more flexibility for patients and improve patient quality of life, as well as reduce health-care costs. The first prototype is currently undergoing preclinical testing and is expected to be tested in humans soon, with the aim of demonstrating proof-of-concept for the first portable haemodialysis machine for daily use, requiring only a limited volume of dialysate. In addition to the development of miniaturization technologies, the partnership is also investigating the use of polymer membranes that permit combined filtration and absorption to achieve more effective haemodialysis 138 .

Nephrologists Transforming Hemodialysis Safety

Nephrologists Transforming Hemodialysis Safety (NTDS) is a collaborative initiative of the ASN and Centers for Disease Control and Prevention (CDC) that is aimed at addressing a specific complication inherent to contemporary dialysis — infection. In 2016, the CDC observed that 10% of dialysis patients in the USA died each year as the result of infections — most of which were preventable. The aim of NTDS is to develop and deploy innovations to achieve zero preventable infections in dialysis facilities across the USA. To reach this goal, NTDS uses a multi-pronged approach. For example, education strategies via publications 139 , 140 , 141 , 142 , 143 and webinars that address various aspects of infection prevention and standards of care, use of social media, development of an interactive chapter for trainees and clinicians, and invited lectures are aimed at ensuring that nephrologists, nurses, dialysis administrators and other professionals understand the risk of dialysis-related infections and evidence-based best working practices.

NTDS also interacts with experts in infection detection, prevention and treatment within federal, state and local health departments who can provide advice and assistance that is independent of the regulatory and potentially punitive arms of health departments. NTDS promotes the appropriate use of these experts in settings where expert advice is needed.

To promote leadership among physicians and nurses, NTDS is sponsoring a leadership academy to ensure that knowledge pertaining to evidence-based best working practices is applied to improve workflows in clinical practice. Effective leadership is a requirement, particularly in complex settings, to ensure that patient safety is prioritized and to motivate staff to use best practices.

NTDS are also collaborating with human factors engineers to study the workflows used in haemodialysis facilities and help to define ways of avoiding errors that lead to infection. As a first step in this process, NTDS and human factors engineers have spent time in various haemodialysis facilities to obtain information about the complex processes of care within those facilities, particularly with regard to the use of haemodialysis catheters and approaches to hand hygiene, injection safety and disinfection. Better understanding of current processes may lead to better workflow design.

Finally, based on lessons learned during the Ebola Crisis of 2014, an NTDS work group has designed processes to anticipate and respond to unexpected health-care crises. At the time of writing this Review, the NTDS team is working with CDC and haemodialysis organizations to anticipate and respond to the COVID-19 epidemic and its effect on dialysis care.

The Affordable Dialysis Prize

As discussed earlier, kidney failure remains a death sentence for many residents of LMICs owing to a lack of access to dialysis. In response to the pressing need for cost-effective dialysis options, the International Society of Nephrology in collaboration with the George Institute for Global Health and the Asian Pacific Society of Nephrology launched the Affordable Dialysis Prize in 2017 with the objective of facilitating the design of a dialysis system that would cost less than US $1,000, and provide treatment for less than $5 a day, yet be as safe and effective as existing dialysis systems. The prize was awarded to an engineer for a system that runs off solar power and includes a miniature distiller for producing pure water from any source via steam distillation. The purified water can then be mixed with electrolytes in empty PD bags to produce cheap, homemade dialysis solutions. This strategy identifies the lack of cheap, high-quality water as a major impediment to dialysis in LMICs and LICs. The system will ideally fit into a small suitcase 144 . This device remains under development with the goal of initiating clinical trials and ultimately commercializing the technology.

Empowered in-centre haemodialysis

For some patients with kidney failure, maintenance in-centre haemodialysis will always be the preferred treatment, and despite incentivizing policy levers, they will not be interested in pursuing home dialysis or kidney transplantation. In-centre self-dialysis (also referred to as empowered haemodialysis) originated in Sweden, when a young engineer named Christian Farman returned to haemodialysis in 2010 after a failed transplant. Farman began negotiating with his nurses to perform his own dialysis treatments with staff supervision and caught the attention of other patients 145 . Eventually, the process of self-dialysis within this centre — whereby coaches in the dialysis unit train people to take over control of their own treatments and health — grew so popular that a new unit was built at the hospital for self-dialysis patients only, with patient input into the design of the unit. Since then, self-care units were installed in several haemodialysis units in Europe and the USA, offering patients the autonomy and flexibility of home haemodialysis within the safety of a controlled environment. This approach to empowering patients has not been widely used to date, but deserves rigorous study and evaluation 146 .

Remote monitoring to support self-care

Telemedicine is defined as the electronic exchange of medical information between sites with the aim of improving a patient’s health. Telehealth encompasses a broader set of services such as the provision of educational content. New technologies have broadened the scope of telemedicine and telehealth applications and services, making these tools more accessible and useful in the care of patients who live remotely or have difficulty visiting a clinic. The range of services that can be delivered by telehealth now includes two-way interactive video, device data programming, asynchronous messaging , sensors for remote monitoring and portals to enable patients to access electronic health records. Although relatively understudied in haemodialysis patients to date, telehealth has the potential to increase the acceptance of home dialysis and improve patient satisfaction, while potentially decreasing costs and improving outcomes.

Telehealth and the remote monitoring of dialysis patients has become more commonplace in the past decade, particularly in Australia, where telehealth is used widely for patients receiving home dialysis. Telemedicine is also considered a support tool for kidney care in disaster situations such as earthquakes where many individuals in remote locations can be affected. Telemedicine has also been used for distance monitoring of patients receiving PD 147 , 148 . In the USA, the Bipartisan Budget Act of 2018 included provisions to expand telehealth coverage to include patients on home dialysis. This legislation allows patients on home dialysis to choose to have their monthly care-provider visits take place via telehealth, without geographic restrictions. The ongoing COVID-19 pandemic has also resulted in an unprecedented and rapid expansion in the use of telemedicine for providing health care in many regions worldwide, including for the care of patients undergoing in-centre haemodialysis. The experience gained during this pandemic has the potential to permanently embed telemedicine in health-care delivery in many health-care systems.

Although telehealth has considerable promise for the care of dialysis patients, the implementation of telehealth in clinical practice can be challenging 149 . Telehealth-guided digital interactions have the potential to improve outcomes through the provision of activities such as individualized patient-centred education, remote communication and data exchange, in-home clinical guidance and monitoring, assessment of prescription and/or treatment efficacy and adherence, real-time modification of treatments and early alerts for problems that require intervention, although all of these interventions need to be rigorously tested 150 .

The European Kidney Health Alliance

The European Kidney Health Alliance (EKHA) is a non-governmental organization based in Brussels, Belgium, which advocates for kidney patients and the nephrology community at relevant bodies of the EU and also at European national organizations. The EKHA represents all of the major stakeholders in kidney care, including physicians, patients, nurses and foundations. The actions of the EKHA are supported by a dedicated group of Members of European Parliament. Of note, according to the treaty of Lisbon 151 , health-care systems are the responsibility of the national authorities of EU countries, which limits the role of the European Commission to one of complementing national policies and fostering cooperation. The EKHA has undertaken several initiatives in the area of kidney care, mainly focusing on measures to decrease the costs of kidney care while maintaining quality of care and access for all appropriate candidates, and to reduce demand for dialysis by promoting efforts to prevent the progression of kidney disease, and encouraging kidney transplantation as the KRT of choice 66 , 152 . In 2021, the EKHA will focus on reimbursement strategies and access to KRT, especially home haemodialysis.

The Nephrology and Public Policy Committee is a similar initiative created by the European Renal Association–European Dialysis and Transplant Association (ERA–EDTA). This committee aims to translate important kidney-related clinical topics into public policy, including the search for novel biomarkers of CKD, improving transition between paediatric and adult nephrology, and improving collaboration between the ERA-EDTA Registry and the guidance body of the ERA-EDTA, European Renal Best Practice 153 .

Beating Kidney Disease

Together with the Dutch Federation for Nephrology and the Dutch Kidney Patients Association, the DKF has initiated a strategic agenda for research and innovation in the Netherlands. This initiative, called Beating Kidney Disease (Nierziekte de Baas) will promote four specific research areas 154 : prevention of kidney failure, including root causes such as other chronic diseases; personalized medicine including genome and big data analyses, and studies of rare diseases; patient-centred outcomes and quality of life, transplantation and home haemodialysis; and regenerative medicine including bio-artificial kidneys. In collaboration with the EKHA, the Beating Kidney Disease initiative will be proposed as a framework for future initiatives at the Directorate General for Health and Food Safety of the European Commission, and the European Commissioner of Health. Similar to European initiatives that have promoted transplantation 152 , 155 , 156 , these efforts will emphasize shifts in policy action to strengthen institutional frameworks, improve education, training and information, optimize registries, and ensure appropriate benchmarking in nephrology.

Conclusions

The past 50 years have seen rapid changes in how and to whom dialysis is provided. From a global perspective, the escalating numbers of patients who require dialysis mean that even current costs are not sustainable, and yet most people who develop kidney failure forego treatment owing to a lack of access, with millions of lives lost every year as a consequence. Also important, the limitations of current dialysis treatment in alleviating patient suffering, morbidity and mortality are now viewed as unacceptable. Consequently, patients, payors, regulators and health-care systems are increasingly demanding improved value, which can only come about through true patient-centred innovation that supports high-quality, high-value care. Substantial efforts are now underway to support requisite transformative changes. These efforts need to be catalysed, promoted and fostered through international collaboration and harmonization to ensure that in the future, people living with kidney failure have more and better treatment options than exist today.

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J.H. declares that The Kidney Research Institute and the Center for Dialysis Innovation at the University of Washington, which he directs, has received gift and grant support from the Northwest Kidney Centers, a not-for-profit dialysis provider. The Center for Dialysis Innovation has also received a Phase I prize from KidneyX, and a grant from the Veterans Administration. J.H. is also a founder and holds equity in AKTIV-X Technologies, Inc. R.V. has consulted for Baxter Healthcare, B. Braun and Neokidney. R.M. has received an honorarium from Baxter Healthcare and serves as a member of the Board of Trustees of the Northwest Kidney Centers. M.T. has received a lecture fee from B. Braun, which was donated to charity.

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Himmelfarb, J., Vanholder, R., Mehrotra, R. et al. The current and future landscape of dialysis. Nat Rev Nephrol 16 , 573–585 (2020). https://doi.org/10.1038/s41581-020-0315-4

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• Published: 25 March 2022

Relationship between modifiable lifestyle factors and chronic kidney disease: a bibliometric analysis of top-cited publications from 2011 to 2020

• Ting Yin 1 ,
• Yilong Chen 2 ,
• Lei Tang 1 ,
• Huaihong Yuan 1 , 3 ,
• Xiaoxi Zeng 1 , 2 &
• Ping Fu 1  

BMC Nephrology volume  23 , Article number:  120 ( 2022 ) Cite this article

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Chronic kidney disease (CKD) affects 8 to 16% of the world’s population and is one of the top ten important drivers of increasing disease burden. Apart from genetic predisposition, lifestyle factors greatly contribute to the incidence and progression of CKD. The current bibliometric analysis aims to characterize the current focus and emerging trends of the research about the impact of modifiable lifestyle factors on CKD.

We searched articles addressing the impact of modifiable lifestyle factors on the incidence and/or progression of CKD, published between 2011 and 2020, from the Science Citation Index Expanded (SCIE) database. An adjusted citation index, which considered both the original citation count and publication year, was derived for the selection of most-cited publications. Publishing trends, co-authorship network, keywords, and research hotspots were analyzed and visualized.

Among the top 100 most influential articles, 32 were narrative reviews, 16 systematic reviews and/or meta-analysis, 44 clinical research, and 8 basic research. The United States occupied a dominant position in the perspective of article numbers and international partnerships, followed by European countries. The modifiable factors that drew the most and constant attention over the decade were diet or nutrition management reported in 63 papers, followed by obesity or body mass index ( n  = 27), and physical activity or exercises ( n  = 8). Alcohol consumption, fish oil, chain fatty-acids, and water-soluble vitamins were emerging hotspots identified in the recent most cited publications.

Conclusions

Based on the bibliometric analysis of the most influential articles, our study provides a comprehensive description of publishing trends and research focus over a decade in the field of lifestyle factors’ impact on CKD. Diet, obesity, and physical activity were factors receiving the most attention in this topic.

Peer Review reports

Chronic kidney disease (CKD), defined as abnormalities of kidney structure or function presenting for >3 months with health implications [ 1 ], affects 8–16% of the world’s population [ 2 ]. CKD is closely associated with an increased risk of adverse events, including end-stage renal disease (ESRD), cardiovascular events, hospitalizations, and mortality [ 3 , 4 , 5 , 6 , 7 ]. The global all-age mortality rate from CKD increased by 41.5% from 1990 to 2017 [ 8 ]. It is currently ranking the 16th leading cause of years of life lost [ 2 ] and is projected to rise in the ranking, to the 5th, by 2040 [ 9 ].

CKD imposes great burdens in both developed and developing countries. For example, Medicare expenditures for ESRD in the United States (the US) increased by about 20.3% from 2009 to 2018 and accounted for 7.2% of overall Medicare fee-for-service spending in 2018 [ 10 ]. The burden of CKD is even more pronounced in low- and lower-middle-income countries [ 11 ]. In several regions, particularly Oceania, sub-Saharan Africa, and Latin America, the burden of CKD is much higher than expected for the level of development [ 8 ]. Thus, it is considered to be one of the top ten important drivers of increasing burden according to the latest analysis for the Global Burden of Disease Study [ 12 ].

CKD is affected by both genetic and environmental factors [ 13 ]. While modification of the genetic predisposition for CKD is quite challenging, evidence shows that the incidence and rapid progression of CKD can be protected via modifiable lifestyle factors, ie. diet, physical activity, alcohol consumption, tobacco smoking, sleep, and obesity [ 14 , 15 , 16 , 17 , 18 ]. Recently, growing literature has addressed the underlying mechanism and the health impact of modifiable factors on CKD. However, to our knowledge, there have been no bibliometric analyses on this topic.

Bibliometric analysis is a valuable tool for navigation in a particular research area [ 19 , 20 ]. It has been used to provide qualitative and quantitative analysis of publications, enabling researchers to identify core articles, study hotspots, and publishing patterns within a given subject area [ 21 ]. Thus, bibliometric analysis is an integral part of the evaluation methodology for assessment of the research evolution and current development stage of the discipline [ 19 , 22 ]. In this study, based on bibliometric analysis of the top-cited articles, we aim to elucidate the current focus, growing trends, and future direction of the research about the impact of modifiable factors on CKD.

Search strategy

We aimed to analyze the most influential publications within the last ten years. Inclusion criteria were (1) original articles or reviews which addressed the impact of modifiable lifestyles, ie. diet (including foods, nutrients, and dietary patterns), physical activity, alcohol consumption, smoking, sleep, and obesity, on the incidence and/or progression of CKD; (2) published between January 2011 to December 2020; (3) with restriction of language of English. The Science Citation Index Expanded database (SCIE) of Web of Science, which includes multidisciplinary bibliographic information and is now regarded as one of the collections of the highest impact, most influential international and regional journals [ 23 , 24 ], was searched for the inclusion of publications. A comprehensive search strategy was performed to identify the intersect of search terms describing CKD and modifiable lifestyles, being limited to the field of “Topic”. Other document types, such as meeting abstracts, letters, and corrections, were excluded. The detailed search terms were listed in Table S 1 .

Study selection and data collection

Considering papers that were published earlier had innately higher opportunities to be cited than those published later, to ensure recently published influential papers also be included for analysis, we derived an adjusted citation index, which was defined as the mean number of citations per year, calculated by the equation: adjusted citation index = total cited count / (2021- publication year), to evaluate the publications for inclusion.

Among the original 20,157 records obtained via the above-mentioned search strategy, to facilitate the following study selection process, we firstly excluded studies after the 300th rank each year in descending order of total citation count. Next, for the 3000 remaining studies for further evaluation, the abstracts, as well as full texts when necessary, were thoroughly reviewed by investigators (YT and HY) independently to exclude ineligible studies. Any disagreement was resolved through discussion with another viewer (XZ). Finally, the top 100-cited articles according to the adjusted citation index were included in our bibliometric analysis. The information of titles, authors, institutions, abstracts, countries, publication years, journals, total citation number of the article, document types, author keywords and keywords plus, and research areas of these publications, were downloaded on 6 August 2021. The selection process of the articles was shown in Fig.  1 .

Flow diagram of the article selection process used in the study

• Bibliometric analysis

We read the abstract or full text of each article and classified the research into clinical research, basic research, review, and meta-analysis. We used ‘bibliometrix’ package in R software (version 3.6.3) to analyze the bibliographic information [ 25 ]. The country of origin of the articles was defined according to the corresponding author. H-index was used to evaluate scholars’ scientific output based on their published articles and citations. The value of H-index is equal to the number of papers (N) of a researcher that has been cited by others at least N times [ 26 ]. The annual percentage growth rate was calculated by ‘biblioAnalysis’ function in R software to describe the annual change in the scientific production.

VOSviewer software (version 1.6.16) [ 27 ] was used to visualize the co-authorship network and analyze keywords. The link in the co-authorship network represented authors’ collaborations and bigger nodes indicated more publications of the authors [ 28 ].

For keyword analysis, we extracted both the original keywords provided by the authors and the keywords plus, which were words or phrases that frequently appeared in the titles of an article’s references but did not appear in the title of the article itself. For articles that did not provide author keywords, keywords plus were used instead, since keywords plus were considered to be as effective as author keywords when investigating the knowledge structure of scientific fields [ 29 ]. We merged some synonym keywords and unified keywords with the same meaning (Table S 2 ) [ 30 ]. For example, “chronic kidney disease”, “chronic renal insufficiency”, and “CKD” were merged into “chronic kidney disease”. We derived a word cloud to visualize the word significance, the dimensions of each word representing the frequency of occurrences in publications [ 31 ]. The keyword co-occurrence network, in which an edge between two nodes representing the co-occurrence of two words, was derived to reflect the research hotspots in the discipline fields. Bigger nodes represent higher importance of items. A shorter distance indicates stronger relation between nodes. The thicker of the line represents more co-occurrence between two keywords [ 32 ].

Research areas, publishing trends, and citation index

Among the top 100 most influential articles, 32 were narrative reviews, 16 systematic reviews and/or meta-analysis, 44 clinical research, and 8 basic research. The modifiable factors that drew the most attention were diet or nutrition management in 63 papers, including plant-based diets, dietary sodium restriction, Mediterranean diet, dietary cadmium intake, red meat, high dietary acid load, high protein diet, among others, followed by obesity or body mass index (BMI; n  = 27), and physical activity or exercises ( n  = 8). Other factors being investigated that obtain high citations included smoking, alcohol consumption, and lipid. The outcomes of interest were the risk of the incidence and progression of CKD, including, in three articles, kidney transplantation, as well as the management and prevention of adverse outcomes associated with CKD. Based on original information on research areas retrieved from the SCIE database, 65 papers were classified into urology and nephrology, 16 in nutrition dietetics, 10 in general internal medicine, 10 in transplantation, and 7 in endocrinology metabolism. The characteristics and methodology of the included top 20 and top 100-cited articles, and summarized authors’ views on the impact of modifiable lifestyles on CKD were listed in Table 1 and Table S 3 respectively, ordered by descending adjusted citation index.

Despite minor recessions in certain years, the trend analysis demonstrated an annual growth rate of 4.6% in the number of publications across the decade and climbed to the peak in 2019 ( n  = 15; Fig.  2 ). The H-index was 60 of the retrieved articles. The original citation number of these articles ranged from 12 to 436, with an average citation number of 87.2 per paper. Among the included 48 narrative and systematic reviews/meta-analysis, 28 cited other top highly-cited articles listed in this study, but no duplicated publications were identified. The top three articles receiving the highest citation included one study investigating the interaction between obesity-induced hypertension with neurohumoral and renal mechanisms [ 33 ], a review on the association between obesity, oxidative stress, adipose tissue dysfunction, and health risks, including CKD [ 34 ], both published in 2015, and a study on the association between dietary sodium intake, ESRD, and mortality in diabetic patients published in 2011 [ 35 ]. If adjusted citation index was considered, in the latest three years, the most influential papers were three reviews addressing the impact of obesity and diet nutrition on CKD [ 36 , 37 , 38 ].

Annual publication numbers and citations per article by year

Journals, authors, and their countries and institutions

The top 100-cited articles were published in 40 journals, with 2020 impact factor (IF) ranging between 3.655 to 39.890. The four journals with the most publications were Journal of the American Society of Nephrology ( n  = 12; IF = 10.121), American Journal of Kidney Diseases ( n  = 12; IF = 8.860), and Kidney International ( n  = 9; IF = 10.612) based in the US, and Nephrology Dialysis Transplantation ( n  = 9; IF = 5.992) based in Europe (Fig. 3 ). The primary corresponding authors of the top 100-cited articles were from 37 countries. Table 2 and Table 3 list the corresponding authors’ countries who contributed to more than two articles and institutions that contributed more than five articles. The US occupied a dominant position in the perspective of article numbers and international partnerships (Fig. 4 ). Johns Hopkins University in the US was identified as the most productive institution for the highly-cited papers on this topic ( n  = 12), followed by University of California Irvine in the US ( n  = 11), and Karolinska Institute in Sweden ( n  = 8).

Journals that contribute 2 articles or more to the top 100-cited papers and journal impact factor in 2020. IF, impact factor; Am J Nephrol, American Journal of Nephrology; Clin Nutr, Clinical Nutrition; Cochrane Database Syst Rev., Cochrane Database of Systematic Reviews; Lancet Diabetes Endocrinol, Lancet Diabetes & Endocrinology; Nat Rev. Nephrol, Nature Reviews Nephrology; J Renal Nutr, Journal of Renal Nutrition; Clin J Am Soc Nephrol, Clinical Journal of the American Society of Nephrology; Kidney Int, Kidney International; Nephrol Dial Transplant, Nephrology Dialysis Transplantation; Am J Kidney Dis, American Journal of Kidney Diseases; J Am Soc Nephrol, Journal of the American Society of Nephrology

The cooperation relationships of countries that published the top 100-cited articles. The US, the United States; NLD, Netherlands; GBR, the United Kingdom; CHE, Switzerland; NZL, New Zealand; ARE, United Arab Emirates

A total of 591 authors contributed to the top 100-cited articles. The top ten researchers contributing to the field are listed in Table 4 based on their number of publications, and Fig. 5 shows the co-authorship network of authors who contributed at least two papers in the top 100-cited articles. The most productive author was, in the US, Kalantar-Zadeh, Kamyar based in University of California Irvine with active collaboration with other scholars, and outside the US, Campbell, Katrina L. based in Princess Alexandra Hospital, Brisbane, Australia. The above-mentioned information of authors’ institutions was based on their publications in 2020.

Network visualization map of the co-authorship network for authors in top 100-cited articles

Keywords and research focus

There were 254 keywords provided by original authors and 494 keywords plus in the top 100-cited articles. Analysis was mainly based on author keywords, except 37 papers in which author keywords were not provided and keywords plus were used instead. The top five keywords with the most frequent occurrence were obesity, diet, blood pressure, BMI, and hypertension; and the top five keywords reflecting outcomes were CKD, glomerular filtration rate, mortality, cardiovascular risk, and dialysis (Fig. S 1 ). Generally, we found diet modification, physical activity, or moderate alcohol consumption was associated with a protective role for the incidence and progression of CKD and its related complications, while obesity or smoking was associated with increased risk for the above-mentioned outcomes (Table S 3 ). Figure 6 presents a co-occurrence network of keywords being listed in at least two papers. They were classified into four clusters, which we assumed to reflect research themes. The leading keywords in the yellow cluster were CKD, dialysis, blood pressure, and hypertension, indicating the focus was mainly on the relationship between blood pressure and CKD, including dialysis. The leading keywords in the red cluster were glomerular filtration rate, cardiovascular risk, proteinuria, kidney disease, association, and progression. The keywords related to lifestyles included dietary protein restriction, low-protein diet, and red meat. We supposed the research focus of the red cluster lied in the impact of protein intake on CKD, especially on kidney function and cardiovascular comorbidities. Leading keywords in the green cluster included mortality, ESRD, kidney transplantation, obesity, BMI, physical activity, and metabolic syndrome. Smoking was also included in the group. Therefore, we assumed the cluster as a group referring to the relation between obesity, physical activities, smoking with the advanced CKD, and adverse outcomes. The leading keyword in the blue cluster was diet, followed by nutrition, vegetarian, protein-intake, disease progression, kidney, gut microbiota, and kidney function. This was considered a concrete cluster that discussed diet and CKD progression.

Network visualization map of the keyword co-occurrence network

In addition, we visualized keywords according to the average publication year to evaluate the trends in the research focus over time. As shown in Fig. 7 , the color of the nodes, from purple, blue, green to yellow, corresponds to the earliest to most recent keywords that were used in the publications [ 39 ], reflecting which keywords have become popular in recent years and indicating the trend of future hotspots [ 40 ]. The nodes for some keywords, ie. dietary sodium, water, and salt were small and colored in purple, indicating these were research topics gaining more popularity a few years ago. Keywords with highly frequent occurrences, such as CKD, physical activity, obesity, diet, nutrition, glomerular filtration rate, progression, mortality, blood pressure, cardiovascular risk, and ESRD were colored in green, we considered these were research topics receiving consistent attention over the decade. We noticed a trend of increasing attention on the gut-kidney axis in the field over 2014 to 2019, with four most-cited papers published [ 41 , 42 , 43 , 44 ]. Alcohol consumption, fish oil, chain fatty-acids, and water-soluble vitamins, colored in yellow, appeared in 2020 for the first time, indicating the recently emerging research hotspots. Among the newly emerging keywords colored in yellow, words related to diet accounted for a considerable portion.

Overlay visualization map of keywords according to the average publication time

In this study, we used bibliometric analysis to identify and characterize the top 100-cited articles published between 2011 and 2020 in the field of lifestyle factors’ impact on CKD. Our study provides legible insights on the publishing trends and research themes on the topic. We found about two-thirds of the most cited papers addressing the association between modifiable factors and CKD were clinical research, while basic studies only accounted for a small fraction. Developed countries, especially the US, showed overwhelming influence in this field in terms of the number of top-cited publications. We also noticed the transition of research hotspots over the decade, with diet, nutrition, obesity, and physical activity being the factors constantly drawing attention, and alcohol consumption, gut-kidney axis, fish oil, chain fatty-acids, molecular-weight protein, and water-soluble vitamins being among the newly emerging keywords.

Our finding, that the modifiable factors gaining most popularity were diet or nutritional management, is consistent with the fact that diet contributes substantially to the incidence and progression of CKD, and stays focused in the academic community. Recommendations on protein and sodium intake have been incorporated into guidelines for clinical management of CKD, such as the Kidney Disease: Improving Global Outcomes guideline [ 1 ], National Institute for Health and Care Excellence guideline [ 45 ], and National Kidney Foundation Kidney Disease Outcomes Quality Initiative guideline [ 46 ]. However, as Suetonia C Palmer pointed out, current evidence for dietary interventions in the setting of CKD, with clinical uncertainty, is yet sufficient to guide comprehensive clinical practice [ 47 ]. For instance, there are very limited data available evaluating potential adverse effects and participants’ quality of life related to dietary protein restriction [ 48 ]. Thus, as indicated in our study, the impact of diet and nutrition on CKD remains an important research topic, and further studies to evaluate the effects of nutritional interventions in the general population for the prevention of incident CKD and in CKD participants for slowing the progression to ESRD are required [ 48 ].

Our study showed obesity and health-related behaviors, such as physical activity and smoking, were among the research hotspots of modifiable factors. This evidence supports the inclusion of advice on physical activity, healthy weight, and smoking cessation into CKD management guidelines [ 1 ]. This reflects the attention from the field of nephrology on the influence of emerging obesity issues and unhealthy behavioral factors on health outcomes. Both obesity and sedentary lifestyle have become major driving forces for global disease burdens [ 49 , 50 , 51 ]. Their associations with CKD are investigated intensely by scholars. For example, in the top-cited articles included in the study, obesity is associated with increased CKD risk, and obese or overweight CKD patients are suggested to maintain a healthy weight and lifestyle [ 14 ]. A study evaluated the risk of ESRD associated with obesity at the time of donation among live kidney donors and found that obese live kidney donors have a significant 86% increased risk of ESRD compared to non-obese donors [ 52 ]. Regular physical activity instead of sedentariness can reduce the risk and mortality of CKD in type 2 diabetes [ 53 ]. A randomized clinical trial found that dietary calorie restriction and aerobic exercise can improve the metabolic milieu in patients with moderate to severe CKD [ 54 ]. Besides, a low-intensity exercise program may improve physical performance and quality of life in dialysis patients [ 55 ]. Studies suggest that cigarette smoking is an independent risk factor for incident CKD [ 56 , 57 ], and nonsmoking is associated with a lower risk of adverse outcomes in CKD patients [ 58 ] and all-cause mortality [ 59 ].

It is interesting to investigate the evolution of research hotspots over time. For example, water intake and dietary sodium were factors receiving high citation years ago. A cross-sectional analysis of the National Health and Nutrition Examination Survey found that higher total water intake, particularly plain water, has a protective effect on CKD [ 60 ]. Julie Lin had analyzed longitudinal cohort data to fill the research vacancy of the influence of sodium intake on microalbuminuria and estimated glomerular filtration rate decline and found that less sodium intake can reduce the risk for estimated glomerular filtration rate decline [ 61 ]. Besides, dietary salt restriction is essential in patients with CKD and hypertension [ 62 ]. Nowadays, alcohol consumption, gut-kidney axis, fish oil, chain fatty-acids, and water-soluble vitamins have drawn more attention. Consuming a low or moderate amount of alcohol may lower the risk of developing CKD [ 63 ]. Gut microbiota dysbiosis induces gut-derived uremic toxins formation and is associated with CKD progression [ 64 ]. A recent study finds that omega-3 polyunsaturated fatty acids supplementation, such as fish oil can reduce cardiovascular mortality in patients on hemodialysis [ 65 ]. Short-chain fatty acids, being derived from fiber-rich diets [ 42 ], can delay CKD progression [ 66 ]. Vitamin K deficiency in patients on dialysis is associated with vascular calcification, bleeding risk, and cardiovascular disease [ 67 ]. Diet modification has been receiving persistent attention from scholars as most newly emerging keywords were related to diet. More research is needed to determine the optimal dietary patterns to prevent kidney disease and its progression [ 68 ]. Meanwhile, we noticed, certain research hotspot in other academic fields has not drawn as much attention in nephrology yet. For example, sleep, one of the important modifiable lifestyle factors, which was reported to be associated with a wide range of diseases [ 69 ], including CKD [ 18 , 70 , 71 ], was not found in the top 100-cited list. The low citation might be caused by the most recent publication time not allowing the papers to be fully cited, or might indicate not so many scholars were dedicated to the research of sleep and its relation to CKD. Lifestyle modification of sleep in CKD patients requires more attention.

The results showed the US was the most productive country on the current topic and with the most active international partnership. Journal of the American Society of Nephrology, American Journal of Kidney Diseases, Kidney International based in the US, and Nephrology Dialysis Transplantation based in Europe were the four journals with the most publications, indicating the US and European were pilots in the research field about the impact of modifiable factors on CKD; while developing countries were not active in producing highly influential research. The disparity of the quantity of academic publications between developing and developed world has long been recognized, which might be attributed to multifaced causes, to name a few, lacking of research capacity in developing countries [ 72 ], funding and principal investigator status owned by developed world [ 73 ], language and writing barriers, and editorial bias [ 74 ]. Considering the disease burden of CKD in developing countries are rising and might be more pronounced than that in developed countries, high-quality research about the impact of modifiable factors on CKD conducted in population from less developed regions, and more cooperations between developed countries and developing countries are required, such that the evidence can be disseminated to these population more precisely.

Our study has many strengths. To our knowledge, this is the first bibliometric analysis of the relationship between modifiable lifestyles and CKD. Our study finds the evolution of hot topics over the decade and provides clues for scholars to choose research themes. However, there are some limitations of our study. First, only English literature was included in the study, so we may fail to capture some landmark articles published in other languages. Second, all data were extracted from the SCIE of Web of Science, thus, we may fail to capture certain related publications provided in other sources. Third, despite we analyzed the top-cited articles in this field representing the research hotspots, we admit certain research topics with few publications due to publication bias [ 75 ], may be missed. In addition, ‘obliteration by incorporation’, which represents that the older publications are no longer cited because their findings are common-use and incorporated into the current discipline, is a notable concern in the bibliometric analysis [ 76 ]. Thus, we included publications within the last ten years and ranked articles based on an adjusted citation index rather than the number of citations received in the current year.

In summary, in the bibliometric analysis of the top 100-cited articles addressing the influence of modifiable factors on CKD, our study provides a comprehensive description of publishing trends and research focus over a decade. The association between modifiable factors and CKD has been among the research focus over the decade. While the study hotspots are evolving over time, diet, obesity, and physical activity were factors receiving the most attention in this topic.

Availability of data and materials

All data generated or analysed during this study are included in this published article [and its supplementary information files].

Abbreviations

• Chronic kidney disease

End-stage renal disease

The United States

Science Citation Index Expanded database

Impact factor

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Acknowledgments

We thank the reviewers and editors for their suggestions to improve the work.

Xiaoxi Zeng was supported by the 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (ZYJC18010); Funding from National Natural Science Foundation of China (81900614), Science and Technology Department of Sichuan Province (2021YF0035), and Chengdu Science and Technology Bureau (2020-YF09–00117-GX) for obtaining the original articles and for the support of publication.

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HY, XZ, and PF were responsible for the study’s design and revised the manuscript. TY, LT, HY, and XZ searched and evaluated papers for inclusion. TY and YC extracted data and performed the bibliometric analyses. TY and XZ drafted the manuscript. The authors have read and approved the final manuscript.

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Supplementary Information

Additional file 1: supplementary table 1..

The detailed search strategy.

Additional file 2: Supplementary Table 2.

Keywords merging details. Supplementary Table 3. Bibliometric information of the top 100-cited articles on the impact of modifiable lifestyles on CKD.

Additional file 3: Figure S1.

Word cloud of keywords of the top 100-cited articles.

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Yin, T., Chen, Y., Tang, L. et al. Relationship between modifiable lifestyle factors and chronic kidney disease: a bibliometric analysis of top-cited publications from 2011 to 2020. BMC Nephrol 23 , 120 (2022). https://doi.org/10.1186/s12882-022-02745-3

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Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review

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A Correction to this article was published on 06 March 2023

This article has been updated

In this systematic review we aimed at assessing how artificial intelligence (AI), including machine learning (ML) techniques have been deployed to predict, diagnose, and treat chronic kidney disease (CKD). We systematically reviewed the available evidence on these innovative techniques to improve CKD diagnosis and patient management.

We included English language studies retrieved from PubMed. The review is therefore to be classified as a “rapid review”, since it includes one database only, and has language restrictions; the novelty and importance of the issue make missing relevant papers unlikely. We extracted 16 variables, including: main aim, studied population, data source, sample size, problem type (regression, classification), predictors used, and performance metrics. We followed the Preferred Reporting Items for Systematic Reviews (PRISMA) approach; all main steps were done in duplicate.

From a total of 648 studies initially retrieved, 68 articles met the inclusion criteria.

Models, as reported by authors, performed well, but the reported metrics were not homogeneous across articles and therefore direct comparison was not feasible. The most common aim was prediction of prognosis, followed by diagnosis of CKD. Algorithm generalizability, and testing on diverse populations was rarely taken into account. Furthermore, the clinical evaluation and validation of the models/algorithms was perused; only a fraction of the included studies, 6 out of 68, were performed in a clinical context.

Conclusions

Machine learning is a promising tool for the prediction of risk, diagnosis, and therapy management for CKD patients. Nonetheless, future work is needed to address the interpretability, generalizability, and fairness of the models to ensure the safe application of such technologies in routine clinical practice.

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Introduction

Chronic Kidney Disease (CKD) is a state of progressive loss of kidney function ultimately resulting in the need for renal replacement therapy (dialysis or transplantation) [ 1 ]. It is defined as the presence of kidney damage or an estimated glomerular filtration rate less than 60 ml/min per 1.73 m 2 , persisting for 3 months or more [ 2 ]. CKD prevalence is growing worldwide, along with demographic and epidemiological transitions [ 3 ]. The implications of this disease are enormous for our society in terms of quality of life and the overall sustainability of national health systems. Worldwide, CKD accounted for 2,968,600 (1%) disability-adjusted life-years and 2,546,700 (1% to 3%) life-years lost in 2012 [ 4 ]. Therefore, it is of the utmost importance to assess how to promptly and adequately diagnose and treat patients with CKD.

The causes of CKD vary globally. The most common primary diseases causing CKD and ultimately kidney failure are diabetes mellitus, hypertension, and primary glomerulonephritis, representing 70–90% of the total primary causes [ 1 , 2 , 4 ]. Although these three causes are at the top of the CKD etiology charts, other features are involved in CKD pathophysiology (e.g., pollution, infections and autoimmune diseases) [ 5 , 6 , 7 , 8 , 9 ]. Similarly, there are numerous factors that play a role in CKD progression, namely non-modifiable risk factors (e.g., age, gender, ethnicity) and modifiable ones (e.g., systolic and diastolic blood pressure, proteinuria) [ 1 , 2 , 4 , 5 , 6 , 7 , 8 , 9 ].

Given how dauntingly vast the number of factors that can play a significant role in the etiology and progression of CKD is, it can be difficult to correctly assess the individual risk of CKD and its progression. Naturally, as with any complex problem, humans seek simplification, and therefore the question shifts to what to take into account when assessing CKD risk. Thanks to new methodological techniques, we now have the ability to improve our diagnostic and predictive capabilities.

Artificial Intelligence (AI) is the capacity of human-built machines to manifest complex decision-making or data analysis in a similar or augmented fashion in comparison to human intelligence [ 10 ]. Machine Learning (ML) is the collection of algorithms that empower models to learn from data, and therefore to undertake complex tasks through complex calculations [ 11 , 12 , 13 , 14 , 15 ]. In recent years AI and ML have offered enticing solutions to clinical problems, such as how to perform a diagnosis from sparse and seemingly contrasting data, or how to predict a prognosis [ 16 ]. Given the enormous potential of ML, and its capacity to learn from data, researchers have tried to apply its capacities to resolve complex problems, such as predicting CKD diagnosis and prognosis, and managing its treatment.

In this complex scenario, we aimed to systematically review the published studies that applied machine learning in the diagnosis and prediction, prognosis, and treatment of CKD patients. In doing so, the primary objective is to describe how ML models and variables have been used to predict, diagnose and treat CKD, as well as what results have been achieved in this field.

Search strategy and selection criteria

We conducted a systematic literature review, following the Preferred Reporting Items for Systematic Reviews (PRISMA) approach [ 17 ], including studies that applied ML algorithms to CKD forecasting, diagnosis, prognosis, and treatment. This systematic review’s outcomes of interest are machine learning models, features used, performances and uses regarding diagnosis, prognosis and treatment of CKD. The review itself and its protocol were not registered.

The initial search was implemented on October 20, 2021. The search query consisted of terms considered pertinent by the authors.

We searched for publications on PubMed using the following search string: “((artificial intelligence[Title/Abstract]) OR (machine learning[Title/Abstract]) OR (computational*[Title/Abstract]) OR (deep learning[Title/Abstract])) AND ((ckd) OR (chronic kidney disease) OR (chronic kidney injury) OR (chronic kidney) OR (chronic renal) OR (end stage renal) OR (end stage kidney) OR (ESKD) OR (ESRD) OR (CKJ) OR (CKI) OR (((renal) OR (kidney)) AND (failure)))” .

We included articles for review if they were in vivo studies (human-based), which applied AI & ML techniques in order to assess the diagnosis, prognosis, or therapy of CKD patients and reported original data. We did not limit our inclusion criteria to any specific study design, nor to any outcome of interest, as our main goal was to be as inclusive as possible, and we wanted to capture all available evidence from any study design and any outcome of interest.

We excluded studies that were not in English, those focusing on animals, reviews, systematic reviews, opinions, editorials, and case reports. We decided to exclude in vitro studies (conducted on cellular substrates) and studies focusing on animals, in order to summarize the current evidence on the application of ML models on humans.

Data extraction

Data were extracted by two independent reviewers (AC and FS). Disagreement on extracted data was discussed with an independent arbiter (DGol).

The following data were extracted from each included article (main text and/or supplementary material): author(s) name, date of publication, first author affiliation (country and region), main study objective, objective category (risk, diagnosis, prognosis, and treatment), prognosis category, study population, data source, sample size, problem type (regression, classification), machine learning algorithms examined in the study, predictor categories, number of predictors used, predictor list, performance metrics, final conclusions, use in clinical context and the 5 most important model features. When more than one model was considered in the study, the one the authors deemed best was extracted. Performance metrics always refer to the models’ performance on test sets.

Quality and risk assessment

Evaluation of the included studies was performed using both PROBAST [ 18 ] and the Guidelines for developing and reporting machine learning predictive models in biomedical research developed by Luo and colleagues [ 19 ].

Included studies

Of the 648 articles retrieved from PubMed, 421 were ruled out after title screening, and 140 were excluded after abstract screening; a total of 87 articles were selected for full-text screening (Fig.  1 ). Of these 87 studies, 68 were included in the final set of articles (Table 1 ) [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 ].

PRISMA flow-chart

Most of the included articles ( n  = 51) were published from 2019 to 2021. Among the 68 articles selected for data extraction, the majority were published by authors from organizations based in Asia ( n  = 33; 48.5%). The remaining articles were published by authors from Europe ( n  = 17; 25%), North America ( n  = 12; 17.6%), Africa ( n  = 5; 7.35%) and South America ( n  = 1; 1.47%). The analyzed studies were classified as observational.

A total of 28 studies focused on the use of ML algorithms in disease prognosis analysis, 21 investigated the use of ML techniques on diagnosis (4 evaluated both), 12 evaluated the risk of developing the disease, and 3 investigated the use of ML in CKD treatment. Among the articles focusing on prognosis, the majority studied the application of ML in evaluating CKD progression ( n  = 13) and mortality ( n  = 8).

Study populations and sample size

The most commonly investigated study population consisted of patients with CKD and healthy subjects ( n  = 26; 38.2%), followed by patients with CKD only ( n  = 16; 23.5%) and patients with CKD treated with hemodialysis ( n  = 12; 17.6%). The sample size investigated in the selected articles varied from a minimum of 30 individuals to a maximum of 550,000 (median = 776; IQR 400–12,020).

Data sources

The majority of the included articles analyzed data obtained from single-hospital registries ( n  = 33; 48.5%), datasets provided by universities ( n  = 15; 22.1%), and datasets collected in multi-center studies ( n  = 12, 17.6%). Five studies analyzed health insurance data (7.35%) and 3 studies used data provided by national health services (4.41%).

The most commonly used data were various combinations of demographic data along with individual clinical characteristics and laboratory data ( n  = 60; 82.24%), followed by data obtained by medical imaging technologies ( n  = 5; 7.35%) and genomic data ( n  = 3; 4.41%).

The number of models tested and reported in each article varied from a minimum of 1 model to a maximum of 10 (mean = 3). The most frequently tested model class was tree algorithms ( n  = 58, 33.53%), such as random forest ( n  = 27, 15.61%), decision trees ( n  = 10, 5.78%) and extreme gradient boosting ( n  = 9, 5.20). Subsequently, neural networks (NNs) were often inspected ( n  = 44, 16.18%), especially the multilayer perceptron (MLP) ( n  = 28, 16.18%). Another popular choice of machine learning model class was Support Vector Machines ( n  = 25, 14.45%) and logistic regression ( n  = 18, 10.45%) with various regularizations. Another popular method that we did not classify into a larger model class was the non-parametric k-Nearest Neighbors algorithm ( n  = 8, 2.31%). The complete list of models can be found in Table 2 .

All the articles implemented supervised learning algorithms, 57 (83.8%) of them addressed classification tasks and 11 (16.2%) regression tasks.

The majority of the included articles ( n  = 52) specified the total number of features used to train the models. These models used a highly variable number of features, ranging from 4 to 6624 (median = 24; IQR = 17—46). Of the 68 included studies, 55 specified the variables used in the models ( n  = 130). The most frequently used features are reported in Fig.  2 .

Occurrence of variables in the selected articles, divided per aim

Performance metrics

The most common performance metrics were accuracy ( n  = 30, 17.05%) and the area under the receiver operating characteristic curve (often also referred to as ROC-AUC, AUROC, AUC, or C-statistic) ( n  = 30, 17.05%). Subsequently, other classification metrics, such as sensitivity ( n  = 29, 16.48%), specificity ( n  = 24, 13.64%), precision ( n  = 16, 9.09%), and F1-score ( n  = 14, 7.95%) were often used to compare the machine learning models. Note that all the aforementioned metrics, except ROC AUC, were used for classification and required establishing a risk threshold as a decision boundary. ROC AUC conversely did not require setting a decision threshold as it was calculated by iterating over all the decision thresholds. In terms of regression, the most used metrics for comparison were mean absolute error ( n  = 6, 3.41%) and root mean squared error ( n  = 5, 2.84%). The full list of the metrics and how often they occurred can be found in Table 3 .

Best performing models, and their performances

In the included articles, neural networks were the models that commonly performed best ( n  = 28, 41.18%) compared to the median performance of other models, such as MLP ( n  = 18, 26.47%) and convolutional neural networks ( n  = 7, 24.53%). Tree-based algorithms performed best ( n  = 24, 35.29%); these algorithms included Random Forest ( n  = 16, 23.53%) and Extreme Gradient Boosting ( n  = 5, 7.35%). The results for Support Vector Machines ( n  = 5, 7.35%) were also noteworthy. A complete list of the best performing models in the selected papers can be found in Table 4 .

In terms of performance, we compared the metrics of prediction models, diagnostic models and risk prediction models separately. Of the 25 (36.76%) machine learning models for diagnosis, 19 papers reported accuracy. Three models reported the highest accuracy of 1.00 while the lowest reported accuracy is 0.80 (mean = 0.95, median = 0.98). Sensitivity was reported 15 times, with a maximum of 1.00, a minimum of 0.56, a mean of 0.95 and a median of 0.99. In addition, specificity was reported in 13 cases (max = 1.00, min = 0.79, mean = 0.96, median = 0.99). The ROC-AUC was reported in 6 papers (max = 0.99, min = 0.91, mean = 0.941, median = 0.94).

For the prediction models ( n  = 32, 47.06%), 15 papers reported the ROC-AUC with a maximum of 0.96 and a minimum of 0.69 (mean = 0.82, median = 0.82). Ten papers reported accuracy, ranging from 0.54 to 0.99, with a mean of 0.85 and a median of 0.87. Sensitivity was reported 8 times, ranging from 0.54 to 0.93 (mean = 0.765, median = 0.76), and specificity was reported 5 times (max = 0.99, min = 0.78, mean = 0.917, median = 0.96).

Next, the risk prediction models ( n  = 12, 17.65%) showed ROC-AUC 9 times (max = 0.96, min = 0.76, mean = 0.864, median = 0.86) and accuracy 4 times (max = 0.99, min = 0.82, mean = 0.901, median = 0.91).

Finally, 3 (4.41%) papers focused on therapy, one of which reported an accuracy of 0.95, while the other two focused on outcome differences ( p -values).

Most common variables and most important ones

The total number of variables used in the included studies was 813. The five most common ones were: Blood Pressure ( n  = 62, 7.63%), Age ( n  = 45, 5.54%), Hemoglobin ( n  = 37, 4.55%), Creatinine (serum) ( n  = 31, 3.81%) and Sex ( n  = 31, 3.81%).

Nonetheless, to better capture how variables were used in the selected papers, we classified the variables into 4 subsets (CKD Prognosis, CKD Diagnosis, Risk of Developing CKD, CKD Treatment) based on the primary aim the authors stated their model would have attempted to achieve.

Regarding CKD Prognosis, 342 variables were used out of 813 total (42%). The most common ones were: Blood Pressure ( n  = 24, 7%), Age ( n  = 19, 5,56%), Cholesterol (serum) ( n  = 18, 5.26%), Sex ( n  = 14, 4%) and Hemoglobin (blood) ( n  = 13, 3.8%), with the most important variables being: Age, Hemoglobin and Proteinuria.

Concerning CKD Diagnosis, 311 variables were used out of 813 total (38.25%). The most common ones were: Blood Pressure ( n  = 22, 7%), Hemoglobin (blood) ( n  = 19, 6.1%), Pus Cell General—used to indicate the number of dead white cells in urine—( n  = 18, 5.79%), Age ( n  = 14, 4.50%) and Glucose (serum) ( n  = 14, 4.50%). The most important variables in this case were Albumin, Creatinine, and Hemoglobin.

With regard to Risk of Developing CKD, 137 variables were used out of 813 total (16.85%). The most common ones were: Blood Pressure ( n  = 12, 8.75%), Age ( n  = 9, 6.57%), Sex ( n  = 7, 5.11%), History of Cardiovascular Disease ( n  = 6, 4.38%) and estimated Glomerular Filtration Rate (eGFR) ( n  = 6, 4.38%). The most important variables were Age, GFR and Blood Pressure.

Finally, regarding CKD Treatment, 23 variables were used out of 813 total (2.83%). The most common ones were: Blood Iron ( n  = 5, 21.74%), Hemoglobin ( n  = 3, 13%), Drugs Used ( n  = 2, 8.70%), MCV ( n  = 2, 8.70%) and White Blood Cells (blood) ( n  = 2, 8.70%). Regarding this aim, no weights were listed in the examined articles.

The complete spreadsheet with all variables and percentages can be found in Supplemental Material, together with the most important variables, divided per aim.

Other than using PROBAST to assess risk of bias, we also assessed fairness based on how the authors explicitly used variables. In some studies, variables were not fully listed, and in such cases, if the variable (sex, or race/ethnicity) was not indexed, we considered the feature as not included in the general model.

Out of 68 studies, 43 included gender in the model and 12 included race/ethnicity. When Non-Hispanic Whites were part of the assessed cohort, they were the majority group, ranging from 87 to 31%. Ten out of 68 studies addressed both gender and race/ethnicity, and included these variables in the model.

Race/ethnicity was included in 4 out of 12 studies predicting risk, in 5 out of 28 studies predicting prognosis, and in 3 out of 21 studies classifying diagnosis. It was never included in models investigating prognosis and diagnosis combined, and therapeutics.

Clinical Deployment

Regarding Diagnosis, just one model was actually deployed in a clinical environment [ 60 ]. The authors applied a lasso regression with metabolites as features, achieving an accuracy of 99%; the authors used data from a real clinical context, and therefore they deployed and evaluated their model performance on a clinical context, nevertheless, they did not validate their model. Regarding Prognosis, just 3 studies were conducted in a clinical setting [ 49 , 50 , 62 ]. Komaru et al. [ 49 ] predicted 1-year mortality following the start of hemodialysis through hierarchical clustering and achieved an AUC of 0.8; the authors used data from a clinical prospective study to deploy and evaluate their model. Furthermore, they validated the used clusters. Kanda et al. [ 50 ] applied a support vector machine model onto a real population in an observational study to deploy and evaluate their model. The authors achieved an accuracy of 89% through 13 variables; unfortunately, they did not disclose the weights of the variables nor did they validate the model, and therefore we do not know which variables were the most important. Akbilgic et al. [ 62 ] used a model based on a Random Forest algorithm, and achieved an AUC of 0.69; the most important features were eGFR, Spontaneous Bacterial Peritonitis, Age, Diastolic Blood Pressure and BUN. The authors used data from a real clinical context to deploy and evaluate their model; furthermore, they validated their results and model internally. Regarding Risk of developing CKD, one study’s model was used in a clinical context [ 42 ]. The authors used a NN, achieving an AUC of 0.89, using retinal images as features from a clinical context to deploy, evaluate and validate their model. Finally, regarding CKD Treatment, one study’s model was used in a clinical environment [ 26 ]; they presented their results through differences in achieved values by their algorithms, and the best performance was achieved by a NN. They evaluated the model with clinical data, but did not validate it.

Quality assessment

According to the PROBAST assessment tool [ 18 ], most of the included articles showed an overall low risk of bias ( n  = 48; 67.6%), and 65 (91.5%) of the included articles showed low applicability. Moreover, only 8.5% of the included studies scored less than 70% in the reporting guidelines for machine learning predictive models in biomedical research developed by Luo and colleagues [ 19 ]. The complete quality assessment can be found in Supplemental Material.

This systematic review describes how machine learning has been used for CKD. Six overarching themes were found, each of which underlines the need for further consideration by the scientific community.

First, despite the ever-growing number of studies focusing on the topic, a staggeringly low amount are being considered for actual clinical implementation. In this review, just 5 out of 68 articles tried to deploy their model in a real clinical setting. This might indicate either that the technology is not ready yet, or, considering 4 of these 5 articles were published in the last 3 years, that the technology is just starting to creep into real clinical settings. Recent evidence suggests that it is paramount to test newly developed algorithms in clinical settings before trying to deploy them [ 88 ]. Despite promising laboratory results, clinical translation is not always guaranteed. As an example, when studying the feasibility of providing an automated electronic alarm for acute kidney injury in different clinical settings, substantial heterogeneity in the findings among hospitals was described, with the worrying result of a significantly increased risk of death for some hospitals [ 89 ].

Second, as expected, the most important features were profoundly related to the main aim the authors were pursuing. In this regard, there were no surprises in the studied topics as the most important features were related to conditions known to lead to CKD diagnosis, worsening of prognosis and risk of developing CKD (e.g., age, comorbidities, systolic and diastolic blood pressure and eGFR values).

Third, a lack of consistency in reporting results was found. Most of the studies chose to report accuracy, but this was not the norm. Furthermore, while accuracy provides information on model performance, it fails to consider class imbalance and data representation. This is extremely important as accuracy in highly unbalanced datasets can be very high by always predicting the same binary outcome because of a flawed model. For instance, considering a low prevalence disease, if the algorithm is flawed for it always predicts a negative event, the accuracy will be high, but the veracity of the model will not [ 90 ]. As a result, AUCs and ROCs better measure the model precision without requiring the definition of a risk threshold. Twenty-nine authors chose to express their results including AUCs and ROCs: the minimum value was 0.69 and the maximum was 0.99 (mean: 0.83, median: 0.84). These results best express how precise the algorithms were and confirm the overall high performance of the assessed models.

Fourth, a common conundrum regarding feature selection and output was found in studies assessing CKD diagnosis. The definition of CKD requires certain variables to be present in order to make a diagnosis, thus including those variables in the model might be considered mandatory. Nonetheless, including those variables forces the model to streamline its decision process to a simple match in altered values, effectively transforming a complex machine learning model into a linear decision flow-chart, the performance of which will always be stellar.

This phenomenon is especially clear in four of the studies this systematic review assessed [ 36 , 39 , 46 , 47 ]. In these studies, the same database [ 91 ] is used, and accuracy, sensitivity, specificity, and ROC-AUC are never below 98%. We believe researchers should carefully assess the variables used in their machine learning models to make sure that no data leakage is present between features and results.

Fifth, model bias and fairness were almost never considered. This is critical, as both biased and unfair models will not achieve the same results in different demographics, and their societal impact could exasperate disparities in certain populations. These issues need to be further explored before any model can be implemented at point of care.

Finally, among the included studies, only 6 evaluated their models in a clinical setting [ 26 , 42 , 49 , 50 , 60 , 62 ], and only 3 were validated [ 42 , 49 , 62 ]. These studies showed promising results and did not report any unintended consequences after evaluation and/or validation. Notwithstanding the robust results described by the authors, as discussed before, recent evidence suggests that it is paramount to test newly developed algorithms in clinical settings to avoid adverse or unintended consequences [ 88 , 89 ]. Taking into account the pinnacle of importance of validating ones’ results in real clinical contexts and not just “in lab”, in reading their results, their generalizability has to be questioned, especially since no multi-center validations were described among the validated models.

This systematic review presents a few limitations: first, only one database (PubMed) was used to collect studies of interest. It should be noted that systematic reviews are usually exhorted to use at least two databases as stated by the PRISMA statement. Nonetheless, as PubMed has grown to be one of the most used search engines for medical sciences this limitation should be self-amending. Secondly, this systematic review assessed only papers written in English since English is the most widely adopted and commonly used language for the publication of medical papers.

In addition to these limitations, due to this review’s design, all in vitro studies (on cellular substrates) were excluded. Consequently, the evidence presented in this review is not to be interpreted as definitive for all things concerning CKD, since in vitro studies (on cellular substrates), the insight of which is critical in understanding pathogenetic as well as therapeutic mechanisms, were not assessed.

Lastly, the majority of included studies did not evaluate the integration of ML models in daily clinical practice, therefore the results and discussion have to be considered largely from an academic standpoint. Despite these limitations, we feel this review advances the knowledge on the current state of data-driven algorithms to advance CKD diagnosis, prognosis and treatment.

Despite the potential benefits, the application of machine learning for CKD diagnosis, prognosis, and treatment presents several issues, namely fairness, model and result interpretability [ 90 ], and the lack of validated models. Result interpretability concerns reflect the inability to explain which aspects of the dataset used in the training phase led to a predicted result in a particular case [ 92 , 93 ]. Therefore, as the trend in machine learning techniques moves from traditional algorithms (e.g., lasso regressions, support vector machine, and decision trees), to more complex ones (e.g., ensemble algorithms and deep learning), the interpretability concerns become more pronounced [ 90 ]. Notably, researchers highlighted the need for explainability and for models that could have a significant impact on patients' health [ 94 , 95 ]. These models should be reported using best practice reporting guidelines such as the Transparent Reporting of a Multivariate Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) [ 94 ] or MINimum Information for Medical AI Reporting (MINIMAR) [ 97 ]. Transparent and accurate reports are also fundamental in advancing multi-center validations of the applied models, which in turn is an essential step to ensure that only safe and sound models are applied on a large scale.

Most of the studies failed to report on the ethical issues revolving around their model development; the impact on the patient's well-being can also be affected by algorithmic bias [ 98 , 99 ] and this can be worse in certain underrepresented populations. This concern is closely related to the generalizability of the developed model [ 100 , 101 , 102 ]. Specifically, retrospective data that are usually used during the training phase often have significant biases towards subgroups of individuals that have been defined by factors such as age, gender, educational level, socioeconomic status, and location [ 98 ]. The issues of fairness and bias in algorithms should be evaluated by investigating the models’ performance within population subgroups.

This systematic review underlines the potential benefits and pitfalls of ML in the diagnosis, prognosis, and management of CKD. We found that most of the studies included in this systematic review reported that ML offers invaluable help to clinicians allowing them to make informed decisions and provide better care to their patients; nonetheless most of those articles were not actually piloted in real life settings, and therefore, notwithstanding the excellent model performance results reported by authors, the technology might not be ready for mass real-time adoption or implementation.

Although future work is needed to address the viability, interpretability, generalizability, and fairness issues, to allow a safer translation of these models for use in daily clinical practice, the implementation of these techniques could further enhance the effective management of hospital resources in a timely and efficient manner by potentially identifying patients at high risk for adverse events and the need for additional resources.

We hope the summarized evidence from this article will facilitate implementation of ML approaches in the clinical practice.

Data availability Statement

Data that support the findings of this study are available upon reasonable request from the corresponding author, AC.

Change history

06 march 2023.

A Correction to this paper has been published: https://doi.org/10.1007/s40620-023-01609-9

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Sanmarchi, F., Fanconi, C., Golinelli, D. et al. Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review. J Nephrol 36 , 1101–1117 (2023). https://doi.org/10.1007/s40620-023-01573-4

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Article Contents

The global burden of non-communicable diseases, the case of chronic kidney disease, causes of ckd vary in developed and developing nations, ckd is a major risk factor for cardiovascular disease, the need to raise awareness about early ckd and implement prevention programs, conclusions.

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Chronic kidney disease: a research and public health priority

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Norberto Perico, Giuseppe Remuzzi, Chronic kidney disease: a research and public health priority, Nephrology Dialysis Transplantation , Volume 27, Issue suppl_3, October 2012, Pages iii19–iii26, https://doi.org/10.1093/ndt/gfs284

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The growing global burden of non-communicable diseases (NCDs) worldwide has been disregarded until recently by policy makers, major aid donors and academics. However, NCDs are the leading cause of death in the world [ 1–3 ]. In 2008, there were 57 million deaths globally, of which 63% were due to NCDs. These chronic diseases are the largest cause of death, led by cardiovascular disease (17 million deaths, mainly from ischaemic heart disease and stroke) followed by cancer (7.6 million), chronic lung disease (4.2 million, including asthma and chronic obstructive pulmonary disease) and diabetes mellitus (1.3 million deaths) [ 4 ]. They share key risk factors: tobacco use, unhealthy diets, lack of physical activity and alcohol abuse [ 4 ]. The current burden of chronic diseases reflects past exposure to these risk factors, and the future burden will be largely determined by the current exposure. Actually, worldwide the prevalence of these chronic diseases is projected to increase substantially over the next decades [ 5 ]. According to WHO, the global number of individuals with diabetes in 2000 was estimated to be 171 million (2.8% of the world's population), a figure anticipated to increase in 2030 to 366 million (6.5%), 298 million of whom will live in developing countries [ 6 ].

As a consequence, predictions for the next two decades show a near 3-fold increase in the ischaemic heart disease and stroke mortality rate in Latin America, Sub-Saharan Africa and the Middle East [ 4 ]. Countries in transition in the South-East and East Asia have also witnessed a rapid deterioration of their chronic disease risk and mortality profile [ 7 ]. India, the second most populous country, has the highest number of diabetics in the world, and in 2008, the estimates for age-standardized deaths per 100 000 population due to diabetes and cardiovascular disease were 386.3 and 283.0 in males and females, respectively [ 7 ]. In China, age-specific death rates from cardiovascular disease increased between 200 and 300% in those aged 35 through 44 years between 1986 and 1999, and by more than 100% in those aged 45–54 years [ 8 ]. Of note, the 2011 WHO report on CKD Country Profiles [ 7 ] shows that globally low- and lower-middle income countries have the highest proportion of deaths under 60 years of age from NCDs. In 2008, the proportion of these premature NCD deaths was 41% in low-income and 28% in lower-middle income countries, respectively, threefold and more than twofold as compared with the proportion in the high-income countries (13%).

Risk factors for chronic diseases are also escalating. Smoking prevalence and obesity levels among adolescents have risen considerably worldwide over the past decade and portend a rapid increase in chronic diseases [ 9 , 10 ].

In all countries, the increased burden of NCDs is also leading to growing economic costs. For example, it has been anticipated that in the United States, cardiovascular diseases and diabetes together cost $750 billion annually [ 11 ]. In the next 10 years the United Kingdom will lose $33 billion in national income as a result of largely preventable heart disease, stroke and diabetes [ 12 , 13 ]. Over the same period, the national income loss for NCDs in India and China will account for $237 and $558 billion, respectively [ 12 , 13 ].

Thus, NCDs are among the most severe threats to global economic development, probably more detrimental than fiscal crisis, as underlined by the World Economic Forum's 2009 report.

Chronic kidney disease (CKD) is a key determinant of the poor health outcomes for major NCDs [ 14 ]. CKD is a worldwide threat to public health, but the size of the problem is probably not fully appreciated. Estimates of the global burden of the diseases report that diseases of the kidney and urinary tract contribute with ∼830 000 deaths annually and 18 867 000 disability-adjusted life years (DALY), making them the 12th highest cause of death (1.4% of all deaths) and the 17th cause of disability (1% of all DALY). This ranking is similar across World Bank regions, but, among developing areas, East Asia and Pacific regions have the highest annual rate of death due to diseases of the genitourinary system [ 15 ].

National and international renal registries offer an important source of information on several aspects of CKD. In particular, they are useful in characterizing the population on renal replacement therapy (RRT) due to end-stage renal disease (ESRD), describing the prevalence and incidence of ESRD and trends in mortality and disease rates. One of the most comprehensive sources of information about the prevalence of ESRD worldwide is the United States Renal Data System (USRDS). We have implemented the USRDS dataset with ESRD data from renal registries identified after searches of web resources for registry databases, annual reports and published literature. According to this analysis, the most recent available data indicate that the prevalence of ESRD ranges from 2447 pmp in Taiwan to 10 pmp in Nigeria (Figure  1 ). However, there is paucity of renal registries globally with an international standard for registry data collection, especially in low- and middle-income countries, where, in addition, the use of RRT is scarce or non-existent, eventually making it difficult to compare ESRD results [ 16 ]. For these reasons, the reported prevalence rate of ESRD varies widely among countries, especially in the emerging world, which may be related more to the capacity of the health system to provide the costly RRT treatment than true difference in epidemiology of renal disease. Thus, in Latin America, the ESRD prevalence ranges from 1019 pmp in Uruguay to 34 pmp in Honduras, a difference that may also reflect the relationship with the gross national product [ 17 ]. Much less is known in Africa, with the highest ESRD prevalence in Tunisia (713 pmp) and Egypt (669 pmp) [ 18 ]. In relatively developed regions of China, especially in major cities, the prevalence of ESRD has been reported to be 102 pmp [ 19 ], whereas in Japan, it is more than 2200 pmp, one of the highest rates worldwide.

Prevalence of ESRD (dialysis and transplantation) worldwide. Data are from the 2011 USRDS Annual Report and from national registry database and published literature. All rates are unadjusted and presented as prevalence rate per million population.

Therefore, overall there are ∼1.8 million people in the world who are alive simply because they have access to one form or another of RRT [ 20 ]. Ninety per cent of those live in industrialized countries, where the average gross income is in excess of US $10 000 per capita [ 21 ]. The size of this population has been expanding at a rate of 7% per year. As an example, over the last decade, the number of those requiring dialysis has increased annually by 6.1% in Canada [ 22 ], 11% in Japan [ 23 ] and 9% in Australia [ 24 ]. However, <10% of all patients with ESRD receive any form of RRT in countries such as India and Pakistan. In India, ∼100 000 patients develop ESRD each year [ 25 ]. Of these, 90% never see a nephrologist. Of the 10 000 patients who do consult a nephrologist, RRT is initiated in 90%; the remaining 10% are unable to afford any form of RRT. Of the 8900 patients who start haemodialysis, 60% are lost to follow-up within 3 months. These patients drop out of therapy, because they realize that dialysis is not a cure and has to be performed over the long-term, ultimately causing impoverishment of their families.

Patients on RRT can be regarded as the tip of the iceberg, whereas the number of those with CKD not yet in need of RRT is much greater. However, the exact prevalence of pre-dialysis CKD is not known and only rough estimates exist. In industrialized countries such as the USA, the Third National Health and Nutrition Evaluation Survey (NHANES III, 1999–2006) has shown a prevalence of CKD in the adult population of 11.5% (∼23.2 million people) [ 26 ]. A sizeable proportion of these people will experience the progression of their disease to ESRD. In Europe, the Prevention of End-Stage Renal and Vascular End-points (PREVEND) study undertaken in the city of Groningen (the Netherlands) evaluated almost 40 000 individuals in a cross-sectional cohort study [ 27 ]. It was found that no less than 16.6% had high normal albuminuria and ∼7% of those screened had microalbuminuria. If these data were to be extrapolated to the world population, the number of people with CKD could be estimated as hundreds of millions.

Although data concerning the prevalence of pre-dialysis CKD in developing countries are scarce, we would expect that there are comparable numbers of patients with CKD in poor countries as in industrialized nations. To this, the International Society of Nephrology (ISN) Global Outreach (GO) funded the Kidney Disease Data Center database to house data from sponsored programmes aimed at preventing CKD and its complications in developing nations. Some examples indicate that the overall prevalence of CKD, diagnosed based on a urinary albumin/creatinine ratio ≥30 or glomerular filtration rate (GFR) ≤60 L/min/1.73 m 2 (as Modification of Diet in Renal Disease, four variables), is 11 and 10.6% in urban areas, respectively, of Moldova [ 28 ] and Nepal [ 29 ]. Moreover, in the attempt to compare the burden of illness among centres in Nepal, China and Mongolia, in 11 394 adult subjects, it has been found that decreased estimated GFR (<60 L/min/1.73 m 2 ) was present in 7.3–14% of participants across centres; proteinuria (≥1+) on dipstick (2.4–10%) was also common [ 30 ]. By a recent cross-sectional survey of a nationally representative sample of Chinese adults, the overall prevalence of CKD was 10.8% [ 31 ].

Data from India also suggest that in a developing country, the prevalence rate of CKD could vary almost 5-fold between the rural and city population [ 32 , 33 ]. These observations imply that CKD would affect not only very many people in the developing world, but preferentially the poor within these countries who usually have no information about disease and risk factors, and cannot have access to healthcare. Interestingly, low socioeconomic status is associated with CKD also in developed nations, as shown in Unites States by the NHANES survey, which reported people with lower income being disproportionately afflicted with a higher burden of CKD risk factors [ 34 ]. Similarly, in Sweden [ 35 ] and the UK [ 36 ], lower income and social deprivation are associated with micro- or macro-albuminuria, reduced GFR and progressive kidney function loss.

Diabetes and hypertension

Diabetes and hypertension are the major causes of CKD leading to kidney failure in the USA, accounting for 153 and 99 pmp, respectively [ 37 ], of incident causes of ESRD. Definitely lower is the contribution of glomerulonephritis (23.7 pmp) [ 37 ]. The proportion of people with CKD not explained by diabetes and hypertension is substantially lower in the USA (28% of stage 3–4 CKD) than in developing countries [ 37 , 38 ]. Indeed, in a recent study analysing screening programs in Nepal, China and Mongolia, 43% of people with CKD did not have diabetes or hypertension [ 30 ].

Infectious diseases

There is also increasing evidence that infectious diseases, still a major health problem in low-income countries, may substantially contribute to the burden of chronic nephropathies. This mainly relates to poor environmental conditions, unsafe life habit and malnutrition. Urinary tract infections, occurring in the entire population, but with particular impact on females of all ages, especially during pregnancy, may have long-term consequences over and above the direct infectious disease morbidity and mortality these infections cause. They include chronic injury of the kidney which eventually may lead to loss of renal function, development of secondary hypertension and, for pregnant women, increased risk of maternal toxaemia, neonatal prematurity and low birth weight which is usually associated with lower-than-normal nephron number anticipating the high risk for hypertension and chronic renal injury during the life time [ 39 ]. Moreover, in several regions worldwide, tuberculosis is still an endemic infection with many cases of renal tuberculosis remaining clinically silent for years while irreversible renal destruction takes place [ 40 ]. Glomerular involvement with parasitic diseases, including malaria [ 41 ], schistosomiasis [ 42 ] and leishmaniasis [ 43 ], may also pave the way to progressive renal disease. A variety of glomerular lesions, and in particular a unique form of glomerular damage, HIV-associated nephropathy, have emerged as significant forms of renal disease in HIV-infected patients [ 44 ]. With the increasing rate of this viral infection, kidney failure in HIV-infected patients will progressively become a major public health problem, particularly in Sub-Saharan Africa. Therefore, in developing countries, infectious diseases add substantial burden to non-communicable risk factors, in enhancing the global prevalence of CKDs.

Malnutrition

There are also factors that link early malnutrition with being overweight in adulthood, ultimately developing into diabetes and diabetic nephropathy [ 45 ]. A number of observational epidemiological studies have postulated that early (intrauterine or early postnatal) malnutrition causes an irreversible differentiation of the metabolic system, which may, in turn, increase the risk of certain chronic diseases in adulthood. For example, a fetus of an undernourished mother will respond to a reduced energy supply by switching on genes that optimize energy conservation. This survival strategy means a permanent differentiation of regulatory systems that result in an excess accumulation of energy (and consequently body fat) when the adult is exposed to an unrestricted dietary energy supply [ 45 ]. Because intrauterine growth retardation and low birth weight are common in developing countries or within minority groups, this mechanism may result in the establishment of a population in which many adults are particularly susceptible to developing obesity and CKD. These observations further imply that CKD would affect preferentially the poor within these countries.

Acute kidney injury

CKD is also linked to acute kidney injury (AKI). Thus, both the rate of progression to ESRD and all-cause mortality are increased in patients with CKD after transient increases in serum creatinine when compared with patients without CKD [ 46 ]. Moreover, up to 28% of the patients with no pre-existing kidney disease who recover from AKI develop de novo CKD [ 47 ]. Non-steroidal anti-inflammatory medications, several cardiovascular and diabetes drugs, as well as traditional medicines used in the primary-care setting in developing countries, may lead to the development of transient episodes of AKI. These findings emphasize the relevance of CKD detection and appropriate adjustments in management to optimal outcome in major NCDs.

It is increasingly recognized that the burden of CKD is not limited to its implication on demands for RRT but has a major impact on the health of the overall population. Indeed, patients with reduced kidney function represent a population not only at risk for the progression of kidney disease and development of ESRD, but also at even greater risk for cardiovascular diseases. CKD is a major risk factor for cardiovascular mortality, and kidney disease is a major complication of diabetes. In ∼400 000 Medicare patients with diabetes and CKD, in USA over 2 years of follow-up, the risk of death for cardiovascular diseases (32.3%) far exceeded that of the development of ESRD (6:1) [ 48 ]. Moreover, CKD has been documented as an independent risk factor for angina, myocardial infarction, heart failure, stroke, peripheral vascular disease and arrhythmias [ 49 , 50 ]. The increased risk of cardiovascular disease associated with CKD has been shown in both general [ 37 , 51 , 52 ] and high-risk [ 52 ] populations, in young and elderly people [ 53 ], as well as in Caucasians [ 49 ], African blacks [ 54 ] and in Asian people [ 55 ].

There is also evidence that the increased cardiovascular risk in CKD patients does not just coexist with diabetes or hypertension. Indeed, an independent and progressive association between GFR and risk of cardiovascular events and death has been found in a community-based study in more than 1 million adult subjects in the USA [ 56 ]. Similarly, a recent study in more than 6000 people followed on average 7 years has shown that the risk of cardiovascular death was increased 46% in subjects with a mild-to-moderate reduction in GFR (30–60 L/min), independent of conventional risk factors such as diabetes and hypertension [ 57 ].

The reason why CKD is a risk factor for cardiovascular outcomes is not entirely clear, but it seems largely related to the excess prevalence of traditional cardiovascular risk factors, including hypertension, diabetes and dyslipidaemia associated with the renal disease. In addition, other factors such as hyperhomocystinaemia, abnormalities of mineral metabolism and parathyroid function may become more prevalent and have pathogenetic relevance as CKD progresses [ 58 , 59 ]. Even patients with microalbuminuria and proteinuria, but still normal renal function, are at increased risk of cardiovascular morbidity and mortality [ 60 ]. Large studies in the general population showed that the presence of microalbuminuria or proteinuria is associated with enhanced risk of all-cause mortality at all levels of baseline kidney function [ 27 , 49 , 61–63 ].

Thus, through its impact on cardiovascular morbidity, CKD may directly contribute to the increasing global burden of death caused by cardiovascular disease. Therefore, these are the patients in whom efforts should be focused.

The major societal effect of CKD is the enormous financial cost and loss of productivity with associated advanced or ESRD. In many developed countries, treatment for ESRD accounts for more than 2–3% of their annual health-care budget, while the population with ESRD represents ∼0.02–0.03% of the total population [ 64 ]. This situation is even worse in most developing countries, where RRT is often unavailable or unaffordable, and ∼1 million people die with ESRD each year [ 65 ]. On the other hand, awareness of early and advanced CKD is low, even in developed nations, being <20% [ 38 ]. For example, in a recent survey in almost 500 000 people in Taiwan, as a part of medical screening programme, <4% of those with CKD (12%) were aware of their condition [ 66 ]. Moreover, it should be considered that CKD, even at more advanced stages, is treatable. Ample evidence from clinical trials has shown that control of hypertension and of proteinuria, especially with inhibitors of the renin–angiotensin system, are highly effective interventions for slowing the progression of diabetic and non-diabetic CKD [ 67 , 68 ]. Studies have also documented that even sustained remission or regression of proteinuric CKD is achievable especially in a large proportion of non-diabetic patients [ 69 ].

Together, these observations underline the urgent need for strategies to enhance awareness about CKD, especially in developing countries, where the low awareness may serve as a barrier to accessing appropriate care even when available [ 70 ] (Table  1 ). To this purpose, recently, the International Society of Nephrology and the International Federation of Kidney Foundation joined efforts to raise awareness regarding CKD by promoting the annual World Kidney Day (WKD). On this particular day, public activities such as free screening for CKD and its risk factors and meeting with the community population and leaders are planned and performed in numerous centres worldwide [ 71 ]. Nevertheless, the resources to implement effective early awareness, detection and prevention programmes for CKD should ultimately come from government health programmes as part of global strategy to improve public health. Some examples are the National Health Programme in Uruguay that has already incorporated CKD into their NCD prevention programmes, and the Strategic Network of Health Services against Chronic Kidney Disease in Mexico.

Public health initiatives targeting CKD

These programmes will help to decrease the costs of managing ESRD and cardiovascular disease and respond to public health demand. However, before these surveillance and intervention efforts are expanded, information on their sustainability and affordability to the public sector, especially in low-income countries, should be collected.

Medicine is developing evidence for the importance of CKD to public health and its contribution to the global burden of major NCDs, but has no equity plan [ 14 , 72 ]. A more concerted, strategic and multisectorial approach, underpinned by solid research, is essential to help reverse the negative trends in the incidence of CKD and its risk factors, not just for a few beneficiaries but on a global health equity programme. Thus, a pragmatic approach to reduce the global burden of renal and cardiovascular diseases has to be adopted. For that, well-defined screening of community or high-risk populations followed by intervention programmes have to be initiated, especially in developing countries.

In recognition of the increasing burden and importance of chronic diseases, a high-level United Nations meeting with heads of governments of member states was organized last September in New York to discuss a global NCD Action Plan prepared by WHO. Although this document did provide the unique opportunity to bring attention to the pandemic of NCDs, it prioritized four chronic diseases, namely cardiovascular disease, cancer, diabetes and chronic respiratory disease [ 73 ]. Nevertheless, through intensive lobbying also by ISN, CKD has gained recognition in the final Political Declaration [ 73 ]. Indeed, a paragraph of the NCD Action Plan stated that the members of States of the UN General Assembly ‘recognize that renal, oral and eye disease pose a major health burden for many countries and that diseases share common risk factors and can benefit from common responses to non-communicable diseases’ [ 73 ]. However, NCD advocacy groups, such as ISN [ 74 ], as well as the editors of The Lancet and The British Medical Journal have underlined their disappointment over the insufficient emphasis on action to be taken by governments [ 75 , 76 ]. In addition, they pointed out that a major opportunity to advance global health was in danger of being lost since the Political Declaration did not set substantive targets or timelines in the need for member states to activate policies in their public health programmes to address NCD issues [ 74–77 ].

In developing nations, there must also be a commitment to create in-country capacity, notably a human capacity that can determine for itself locally specific problems dealing with kidney diseases to be addressed through clinical research programmes. However, this implies greater efforts by the developed nations to limit the brain drain of scientists and health personnel from low- and middle-income countries [ 78 ]. The North-South capacity gap in health science, including nephrology, continues to narrow, but it has by no means disappeared. At the same time, a new gap in capacity has emerged between scientifically proficient and scientifically lagging developing countries, the so-called South–South gap. This divide has surfaced because the number of developing countries making significant strides in building scientific capacity remains small (Brazil, Argentina, Mexico, Chile, South Africa, India, China and Malaysia). There are examples of increasing South–South cooperation that are helping to close this gap. However, even developing countries that have successfully strengthened their scientific capacity have proven more adept at building their knowledge base than applying the know-how, scientists/physicians acquire to address societal concerns. Along these lines, ISN through its Global Outreach programmes, especially the Research and Prevention programme, has developed several initiatives for emerging countries that can be implemented according to the peculiar needs and organization facilities of the given nation [ 79 ]. Overall, the emphasis is on models to promote and foster autonomous programmes in regions where they are most needed.

The hope is that all these efforts will assist to make a major advance in addressing the neglected aspect of the renal health of people worldwide.

Conflict of interest statement . None declared.

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What to know

With chronic kidney disease (CKD), kidneys become damaged and over time may not clean the blood as well as healthy kidneys. If kidneys don't work well, toxic waste and extra fluid accumulate in the body and may lead to high blood pressure, heart disease, stroke, and early death. However, people with CKD and people at risk for CKD can take steps to protect their kidneys with the help of their health care providers.

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• More than 1 in 7 US adults—about 35.5 million people, or 14%—are estimated to have CKD. †
• As many as 9 in 10 adults with CKD do not know they have it.
• About 1 in 3 adults with severe CKD do not know they have CKD.

CKD by age, sex, and race/ethnicity

According to current estimates: †

• CKD is more common in people aged 65 years or older (34%) than in people aged 45–64 years (12%) or 18–44 years (6%).
• CKD is slightly more common in women (14%) than men (12%).
• CKD is more common in non-Hispanic Black adults (20%) than in non-Hispanic Asian adults (14%) or non-Hispanic White adults (12%).
• About 14% of Hispanic adults have CKD.

† How estimates were calculated for this page and full report: Percentage of CKD stages 1–4 among US adults aged 18 years and older using data from the 2017–March 2020 National Health and Nutrition Examination Survey based on 2021 CKD Epidemiology Collaboration GFR estimating equation, including serum creatinine, age, and sex. CKD stage 5 (that is, kidney failure) was not included. Severe CKD refers to stage 4. These estimates were based on a single measure of albuminuria or serum creatinine; they do not account for persistence of albuminuria or elevated creatinine as indicated by the Kidney Disease Improving Global Outcomes recommendations. Thus, CKD in this report might be overestimated. Estimates by sex and race/ ethnicity were age-standardized using the 2010 US Census population; the overall percentage is unadjusted. The number of adults with CKD stages 1–4 was estimated by applying the overall percentage to the 2019 US Census population aged 18 years and older. Blood pressure–lowering medicines included angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers; blood sugar–lowering medicines included GLP-1 receptor agonists, SGLT2 inhibitors, and DPP-4 inhibitors; diagnosed diabetes was self-reported.

Percentage of US Adults Aged 18 Years and Older With CKD,* by Age, Sex, and Race/Ethnicity

Suggested citation.

Centers for Disease Control and Prevention. Chronic Kidney Disease in the United States, 2023. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention; 2023.

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Ozempic Cuts Risk of Chronic Kidney Disease Complications, Study Finds

A major clinical trial showed such promising results that the drug’s maker halted it early.

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By Dani Blum

Dani Blum has reported on Ozempic and similar drugs since 2022.

Semaglutide, the compound in the blockbuster drugs Ozempic and Wegovy , dramatically reduced the risk of kidney complications, heart issues and death in people with Type 2 diabetes and chronic kidney disease in a major clinical trial, the results of which were published on Friday. The findings could transform how doctors treat some of the sickest patients with chronic kidney disease, which affects more than one in seven adults in the United States but has no cure.

“Those of us who really care about kidney patients spent our whole careers wanting something better,” said Dr. Katherine Tuttle, a professor of medicine at the University of Washington School of Medicine and an author of the study. “And this is as good as it gets.” The research was presented at a European Renal Association meeting in Stockholm on Friday and simultaneously published in The New England Journal of Medicine .

The trial, funded by Ozempic maker Novo Nordisk, was so successful that the company stopped it early . Dr. Martin Holst Lange, Novo Nordisk’s executive vice president of development, said that the company would ask the Food and Drug Administration to update Ozempic’s label to say it can also be used to reduce the progression of chronic kidney disease or complications in people with Type 2 diabetes.

Diabetes is a leading cause of chronic kidney disease, which occurs when the kidneys don’t function as well as they should. In advanced stages, the kidneys are so damaged that they cannot properly filter blood. This can cause fluid and waste to build up in the blood, which can exacerbate high blood pressure and raise the risk of heart disease and stroke, said Dr. Subramaniam Pennathur, the chief of the nephrology division at Michigan Medicine.

The study included 3,533 people with kidney disease and Type 2 diabetes, about half of whom took a weekly injection of semaglutide, and half of whom took a weekly placebo shot.

Researchers followed up with participants after a median period of around three and a half years and found that those who took semaglutide had a 24 percent lower likelihood of having a major kidney disease event, like losing at least half of their kidney function, or needing dialysis or a kidney transplant. There were 331 such events among the semaglutide group, compared with 410 in the placebo group.

People who received semaglutide were much less likely to die from cardiovascular issues, or from any cause at all, and had slower rates of kidney decline.

Kidney damage often occurs gradually, and people typically do not show symptoms until the disease is in advanced stages. Doctors try to slow the decline of kidney function with existing medications and lifestyle modifications, said Dr. Melanie Hoenig, a nephrologist at Beth Israel Deaconess Medical Center who was not involved with the study. But even with treatment, the disease can progress to the point that patients need dialysis, a treatment that removes waste and excess fluids from the blood, or kidney transplants.

The participants in the study were extremely sick — the severe complications seen in some study participants are more likely to occur in people the later stages of chronic kidney disease, said Dr. George Bakris, a professor of medicine at the University of Chicago Medicine and an author of the study. Most participants in the trial were already taking medication for chronic kidney disease.

For people with advanced kidney disease, in particular, the findings are promising. “We can help people live longer,” said Dr. Vlado Perkovic, a nephrologist and renal researcher at the University of New South Wales, Sydney, and another author of the study.

While the data shows clear benefits, even the researchers studying drugs like Ozempic aren’t sure how, exactly, they help the kidneys. One leading theory is that semaglutide may reduce inflammation, which exacerbates kidney disease.

And the results come with several caveats: Roughly two-thirds of the participants were men and around two-thirds were white — a limitation of the study, the authors noted, because chronic kidney disease disproportionately affects Black and Indigenous patients. The trial participants taking semaglutide were more likely to stop the drug because of gastrointestinal issues, which are common side effects of Ozempic.

Doctors said they wanted to know whether the drug might benefit patients who have kidney disease but not diabetes, and some also had questions about the potential long-term risks of taking semaglutide.

Still, the results are the latest data to show that semaglutide can do more than treat diabetes or drive weight loss. In March, the F.D.A. authorized Wegovy for reducing the risk of cardiovascular issues in some patients. And scientists are examining semaglutide and tirzepatide, the compound in the rival drugs Mounjaro and Zepbound, for a range of other conditions , including sleep apnea and liver disease.

If the F.D.A. approves the new use, it could drive even more demand for Ozempic, which has faced recurrent shortages .

“I think it’s a game changer,” Dr. Hoenig said, “if I can get it for my patients.”

Dani Blum is a health reporter for The Times. More about Dani Blum

A Close Look at Weight-Loss Drugs

Reduced Disease Complications: Semaglutide, the compound in Ozempic and Wegovy, dramatically reduced the risk of kidney complications , heart issues and death in people with Type 2 diabetes and chronic kidney disease in a major clinical trial.

Supplement Stores: GNC and the Vitamin Shoppe are redesigning displays and taking other steps  to appeal to people who are taking or are interested in drugs like Ozempic and Wegovy.

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A Company Remakes Itself: Novo Nordisk’s factories work nonstop turning out Ozempic and Wegovy , but the Danish company has far bigger ambitions.

Transforming a Small Danish Town: In Kalundborg, population under 17,000, Novo Nordisk is making huge investments to increase production  of Ozempic and Wegovy.

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Drinking Water of Patients With Chronic Kidney Disease—Get the Lead Out

• 1 Division of Urology, Stanford University, Palo Alto, California
• 2 Division of Nephrology, University of California, San Francisco
• 3 Division of Hematology, Stanford University, Palo Alto, California
• Original Investigation Water Lead and Hematologic Toxic Effects in Chronic Kidney Disease John Danziger, MD, MPhil; Joanna Willetts, MS; John Larkin, PhD; Sheetal Chaudhuri, PhD; Kenneth J. Mukamal, MD, MPH; Len A. Usvyat, PhD; Robert Kossmann, MD JAMA Internal Medicine

Of the 3 available chronic dialysis modalities, home hemodialysis is the most uncommon, supporting approximately 2% of patients receiving chronic dialysis in the US vs 12% peritoneal dialysis and 86% in-center hemodialysis. Most patients receiving home hemodialysis currently in the US are prescribed 4 to 5 sessions per week, each lasting 2.5 to 4 hours. 1

This low use of home hemodialysis stands in contrast to multiple surveys of nephrologists who believe that home hemodialysis provides multiple advantages—including better control of volume and uremia in a more gentle fashion—and would often choose this modality for themselves should they develop kidney failure and were unable to receive a transplant. Patients receiving home hemodialysis tend to be younger, at least partly employed, less likely to have diabetes as their cause of kidney failure, and more likely to be White than those receiving in-center hemodialysis. 1

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Polasko AL , Hsu C , Chien M. Drinking Water of Patients With Chronic Kidney Disease—Get the Lead Out. JAMA Intern Med. Published online May 28, 2024. doi:10.1001/jamainternmed.2024.0901

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This paper is in the following e-collection/theme issue:

Published on 29.5.2024 in Vol 13 (2024)

Effects of Empagliflozin in Type 2 Diabetes With and Without Chronic Kidney Disease and Nondiabetic Chronic Kidney Disease: Protocol for 3 Crossover Randomized Controlled Trials (SiRENA Project)

Authors of this article:

• Steffen Flindt Nielsen 1, 2 , MD   ; 
• Camilla Lundgreen Duus 1, 2 , MD   ; 
• Niels Henrik Buus 2, 3 , MD, PhD   ; 
• Jesper Nørgaard Bech 1, 2 , MD, PhD   ; 
• Frank Holden Mose 1, 2 , MD, PhD  

1 University Clinic in Nephrology and Hypertension, Gødstrup Hospital and Aarhus University, Herning, Denmark

2 Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

3 Department of Renal Medicine, Aarhus University Hospital, Aarhus, Denmark

Corresponding Author:

Steffen Flindt Nielsen, MD

University Clinic in Nephrology and Hypertension

Gødstrup Hospital and Aarhus University

Hospitalsparken 15

Herning, 7400

Phone: 45 21278747

Email: [email protected]

Background: Sodium-glucose-cotransporter 2 inhibitors (SGLT2is) have revolutionized the treatment of type 2 diabetes mellitus (DM2) and chronic kidney disease (CKD), reducing the risk of cardiovascular and renal end points by up to 40%. The underlying mechanisms are not fully understood.

Objective: The study aims to examine the effects of empagliflozin versus placebo on renal hemodynamics, sodium balance, vascular function, and markers of the innate immune system in patients with DM2, DM2 and CKD, and nondiabetic CKD.

Methods: We conducted 3 double-blind, crossover, randomized controlled trials, each with identical study protocols but different study populations. We included patients with DM2 and preserved kidney function (estimated glomerular filtration rate >60 mL/min/1.73 m 2 ), DM2 and CKD, and nondiabetic CKD (both with estimated glomerular filtration rate 20-60 mL/min/1.73 m 2 ). Each participant was randomly assigned to 4 weeks of treatment with either 10 mg of empagliflozin once daily or a matching placebo. After a wash-out period of at least 2 weeks, participants were crossed over to the opposite treatment. End points were measured at the end of each treatment period. The primary end point was renal blood flow measured with 82 Rubidium positron emission tomography–computed tomography ( 82 Rb-PET/CT). Secondary end points include glomerular filtration rate measured with 99m Technetium-diethylene-triamine-pentaacetate ( 99m Tc-DTPA) clearance, vascular function assessed by forearm venous occlusion strain gauge plethysmography, measurements of the nitric oxide (NO) system, water and sodium excretion, body composition measurements, and markers of the complement immune system.

Results: Recruitment began in April 2021 and was completed in September 2022. Examinations were completed by December 2022. In total, 49 participants completed the project: 16 participants in the DM2 and preserved kidney function study, 17 participants in the DM2 and CKD study, and 16 participants in the nondiabetic CKD study. Data analysis is ongoing. Results are yet to be published.

Conclusions: This paper describes the rationale, design, and methods used in a project consisting of 3 double-blind, crossover, randomized controlled trials examining the effects of empagliflozin versus placebo in patients with DM2 with and without CKD and patients with nondiabetic CKD, respectively.

Trial Registration: EU Clinical Trials Register 2019-004303-12; https://www.clinicaltrialsregister.eu/ctr-search/search?query=2019-004303-12, EU Clinical Trials Register 2019-004447-80; https://www.clinicaltrialsregister.eu/ctr-search/search?query=2019-004447-80, EU Clinical Trials Register 2019-004467-50; https://www.clinicaltrialsregister.eu/ctr-search/search?query=and+2019-004467-50

International Registered Report Identifier (IRRID): DERR1-10.2196/56067

Introduction

The World Health Organization has recently named diabetes the ninth leading cause of death globally [ 1 ]. Worldwide, more than 500 million people are living with diabetes. By 2045, this number is expected to rise to more than 780 million [ 2 ]. The disease burden is immense and complications are common. One of the most common and serious complications is cardiovascular disease (CVD), which affects more than 30% of all patients with diabetes [ 3 ]. Other complications include retinopathy, neuropathy, and nephropathy.

Chronic kidney disease (CKD) affects up to 50% of all patients with type 2 diabetes mellitus (DM2) [ 4 , 5 ] and is common in patients without diabetes as well. It ranks just below diabetes as the 10th leading global cause of death, resulting in an estimated 1.3 million deaths annually. The most common cause of death in both patients with diabetes and patients with CKD is CVD [ 3 , 6 ].

Recently, sodium-glucose-cotransporter 2 (SGLT) inhibitors (SGLT2is) have revolutionized the treatment of both DM2 and CKD. Originally developed as an antidiabetic medication, SGLT2is block the SGLT2 channels in the proximal kidney tubule, inhibiting the reabsorption of sodium and glucose from the preurine, leading to glycosuria and a modest decrease in plasma glucose [ 7 ].

Several recent large randomized controlled clinical trials (RCTs) have shown that SGLT2is exert remarkable effects in patients with diabetes, both with and without CKD, reducing the risk of death by CVD, hospitalization for heart failure, and progression of CKD [ 8 - 10 ]. The effects are similar in patients with nondiabetic CKD, reducing the risk of CKD progression and death by renal or cardiovascular causes by 30% to 40% [ 11 , 12 ]. As a consequence, current guidelines recommend treatment with SLGT2i for patients with DM2 both with and without concomitant CKD, as well as for patients with nondiabetic CKD [ 13 , 14 ].

The mechanisms underlying these remarkable effects are, however, not yet fully understood. There are several possible pathways [ 15 ]. In this study, we examine 4 pathways.

SLGT2i and Renal Hemodynamics

Increased renal reabsorption of sodium and glucose mediated by the SGLT2 channels is thought to be an important pathophysiological feature of diabetic nephropathy, instigating an increase in renal blood flow (RBF) via tubule-glomerular feedback mechanisms [ 16 ]. This, in turn, causes renal hyperfiltration; intraglomerular hypertension; and in time, kidney damage.

Intraglomerular hypertension is not unique to diabetic nephropathy but is thought to play a key role in the pathophysiology of nondiabetic CKD as well. A decline in functioning nephrons leads to a cascade of maladaptive hemodynamic changes, including increased intraglomerular pressure and hyperfiltration in the remaining nephrons [ 17 , 18 ].

Conversely, by blocking the SLGT2 channels, SGLT2is are hypothesized to alleviate the changes by reducing RBF and hyperfiltration, which could be a possible explanation of the observed beneficial effects. The acute drop in estimated glomerular filtration rate (eGFR) seen after initiation of SGLT2is could be a part of this mechanism as well [ 19 ]. While the effects of eGFR are well known, the reduction in RBF has only been demonstrated in a single study in patients with type 1 diabetes as well as in animal models [ 20 , 21 ]. None of the studies examining hemodynamic effects of SGLT2is in DM2 have found decreases in RBF [ 22 , 23 ], and it has, to our knowledge, never been examined in patients with CKD.

SGLT2i and Sodium Balance

In addition to blocking glucose reuptake, SGLT2is inhibit sodium reuptake in the proximal tubule, which leads to a transient increase in urinary sodium excretion [ 24 ]. Furthermore, a modest reduction in body weight, plasma volume, and a decrease in sodium skin content is seen and may point to a decrease in volume status and total body sodium [ 25 , 26 ]. This might help explain the rapid improvement in cardiac function seen after SGLT2i initiation [ 27 ]. However, the natriuretic effects of SGLT2is seem to dissipate quickly, possibly due to renal compensatory mechanisms [ 28 ]. These mechanisms are not yet fully understood and have been sparsely studied.

SGLT2i and Vascular Function

SGLT2is are also thought to exert an effect on the endothelial cells lining the inner walls of the blood vessels. DM2, CKD, and especially the combination of the 2 are associated with endothelial dysfunction and the subtle signs of endothelial dysfunction are often evident long before the clinical signs of vascular damage [ 29 , 30 ]. One of the most important reasons for endothelial dysfunction is the decreased synthesis and bioavailability of nitric oxide (NO), which leads to a decrease in systemic vasodilation, dysfunctional cell adhesion, smooth muscle cell proliferation, and hypercoagulability [ 31 , 32 ]. SGLT2is improve endothelial function in animal studies and seems to be able to improve vascular function and arterial stiffness in patients with DM2 [ 33 - 36 ]. So far, no studies have examined the effects in patients with CKD.

SGLT2i and the Immune System

Inflammatory changes are common in the kidneys of patients with CKD and could be an important component in the development of glomerular injury, albuminuria, and CKD progression [ 37 ]. The innate immune system is involved in CKD progression and could be a target for SGLT2is. Both pattern recognition molecules (eg, collectin and mannan-binding lectin [MBL]) and complement activation pathways, notably the lectin pathway, could be involved in the progression of CKD, particularly in diabetes. Therefore, it is of interest to examine this system in diabetic and nondiabetic CKD and determine sensitivity to SGLT2is. Complement system components such as collectins, split products such as anaphylatoxins C3a and C5a, and terminal complexes (membrane attack complex) can be measured in plasma and urine along with other markers of the immune system [ 38 , 39 ]. SGLT2is can reduce the expression of inflammatory molecules such as tumor necrosis factor-α (TNF-α) and interleukin 6 (IL-6) [ 40 ]. Whether SGLT2is also affect markers of the immune system in the kidney remains to be examined. Since the complement system is associated with cell surfaces, we plan to use urine microvesicles (exosomes) and use them as imprints or “wet biopsies” for apical membrane deposition of complement activation products along with quantitation of soluble components in plasma and urine.

Aims and Hypotheses

We aim to examine the effects of the SGLT2i empagliflozin versus placebo on renal hemodynamics, vascular function, sodium balance, and markers of the immune system in patients with DM2 with and without CKD, as well as in patients with nondiabetic CKD, hereby reflecting patient populations who would be offered SGLT2is in a clinical setting. In this paper, we describe and discuss our research hypothesis and the methods we used.

We hypothesize that the SGLT2i results in the following changes: (1) SLGT2i reduces RBF and glomerular filtration rate (GFR); (2) SGLT2i increases NO activity and improves endothelial function; (3) SGLT2i increases fractional sodium excretion, which is modified by more distally localized compensatory mechanisms; (4) SGLT2i increases renin angiotensin aldosterone system activity and decreases 24-hour ambulatory blood pressure and arterial stiffness; and (5) SLGT2i decreases renal innate immune activity.

We conducted 3 double-blind, crossover RCTs, each with identical study protocols but different study populations. We included patients with (1) DM2 and preserved kidney function, (2) DM2 and CKD, and (3) nondiabetic CKD.

Each participant started with a run-in period of at least 2 weeks, wherein ongoing SGLT2i or nonsteroidal anti-inflammatory drug (NSAID) treatment, which is known to affect both renal hemodynamics and fluid homeostasis [ 41 ], was paused. If patients were not treated with SGLT2i or NSAID prior to inclusion, they could proceed directly to randomization. If deemed necessary, the SLGT2i could be substituted with a different class of antidiabetic treatment. The substitution was done in accordance with national treatment guidelines at the time [ 42 ]. After run-in, participants were randomly assigned to 4 weeks of treatment with either 10 mg of empagliflozin or a matching placebo, both taken once daily. After a wash-out period of at least 2 weeks, participants were crossed over to 4 weeks of the opposite treatment. Each 4-week treatment period was finalized with 2 examination days: 1 day at The University Clinic in Nephrology and Hypertension, Gødstrup Hospital, Denmark, and 1 day at The Department of Renal Medicine, Aarhus University Hospital, Denmark.

We aimed to keep examination days adjacent, but due to logistic considerations, we allowed for an interval of up to 1 week between examination days in each treatment period. If there was an interval between the examination days, the treatment period was extended concomitantly, ensuring that the last dose of study medication was taken on the morning of the last examination day ( Figure 1 ).

Recruitment and Screening

Participants were recruited through announcements at general practitioners, through newspaper advertisements, and through email or letters to participants from previous trials, who have consented to being contacted about new trials. Furthermore, participants could be recruited from the outpatient clinics at The Department of Internal Medicine, Nephrology and The Department of Internal Medicine, Endocrinology, Gødstrup Hospital, Denmark.

Participants were screened prior to inclusion to ensure they fulfilled all inclusion criteria and none of the exclusion criteria. Screening involved physical examination; medical history; office blood pressure; electrocardiogram; urine test strip measurement; urinary albumin and albumin-to-creatinine ratio; and the following blood samples: p-glucose, p-alanine transaminase, b-glycated hemoglobin A 1c (HbA 1c ), p-potassium, p-sodium, p-albumin, p-creatinine, eGFR, B-leukocytes, B-hemoglobin, B-erythrocytes, and B-thrombocytes. Office blood pressure was measured 3 times and calculated as an average of the last 2 measurements. It was measured in both arms, and in case of difference between arms, the arm with the highest values was chosen for further measurements. If identical, the left arm was chosen. Inclusion, exclusion, and withdrawal criteria can be seen in Textbox 1 .

Inclusion criteria

Study 1: Type 2 diabetes mellitus (DM2) and preserved kidney function

• Aged 18 years or older
• Estimated glomerular filtration rate (eGFR) > 60 mL/min/1.73 m 2
• DM2 was diagnosed at least 1 year before inclusion and in stable medical antidiabetic treatment for at least 3 months
• Hemoglobin A 1c (HbA1c) 48-70 mmol/mol (Diabetes Control and Complications Trial [DCCT] values 6.5%-8.6%)
• Fertile women were to use safe contraception

Study 2: DM2 and chronic kidney disease (CKD)

• eGFR 20-60 mL/min/1.73 m 2
• DM2 was diagnosed at least 1 year before inclusion, and in stable medical antidiabetic treatment for at least 3 months
• HbA 1c 48-70 mmol/mol. (DCCT values 6.5%-8.6%)

Study 3: Nondiabetic CKD

Exclusion criteria

Study 1 and 2: DM2 and preserved kidney function and DM2 and CKD

• Type 1 diabetes
• Alcohol or substance abuse
• Pregnancy or breastfeeding
• Anamnestic or clinical signs of heart or liver failure
• Active cancers, aside from skin cancers (spinocellular or basocellular carcinomas)
• BMI > 35 kg/m 2
• Allergies or unacceptable side effects to the experimental treatment or background treatment
• If the investigator found the participant unfit to complete the trial.
• Previous kidney transplant
• Autosomal dominant polycystic kidney disease (ADPKD).
• Same as in study 1 and study 2

Withdrawal criteria

• For all 3 studies, participants were withdrawn if they developed an exclusion criterion, withdrew consent, were noncompliant, or experienced serious or unacceptable adverse events.

Participants

Our power calculation was based on the primary end point, RBF. In total, 15 patients were needed in each study to detect a minimal relevant difference in RBF of 0.167 mL/min/g, with an SD of 0.180 mL/min/g, a 2-sided α-level of 5%, and a power of 90%.

Randomization and Study End Points

Randomization numbers were provided by the manufacturer, Boehringer-Ingelheim. Randomization was performed by the Hospital Pharmacy, Central Denmark Region, Department Gødstrup. Participants were randomized in blocks of 4. Treatment assignment and allocation were concealed from clinicians, participants, and research staff until the trials were completed and as long as they were involved in data analysis. A copy of the randomization list and sealed envelopes with individual randomization numbers were kept in a locked safe at The University Clinic of Nephrology and Hypertension, in case unblinding was required. A single participant could be unblinded without it affecting the rest of the trial. At the end of the project, the envelopes will be returned to the Hospital Pharmacy where a receipt will be drawn up. The primary and secondary study end points can be viewed in Textbox 2 .

Primary end point

• Renal blood flow

Secondary end points

• Glomerular filtration rate
• Renal vascular resistance (RVR), filtration fraction, afferent and efferent arteriolar resistance (Ra and Re)
• Vascular function
• The nitric oxide–system, measured as plasma and urinary levels of nitrite, nitrate, and cyclic guanosine monophosphate (cGMP)
• The complement system, measured as plasma and urine levels of mannan-binding lectin (MBL), collectin kidney 1 (CL-K1), collectin liver 1 (CL-L1), mannan-binding lectin serine protease (MASP) 1-3, C4c, C3c, C3dg, sC5b-9, and urinary exosomes.
• Systemic hemodynamics, measured as 24-hour ambulatory brachial blood pressure, heart rate, pulse wave velocity, and peripheral resistance
• Plasma levels of renin, angiotensin II, aldosterone, vasopressin, and brain natriuretic peptide
• Water and sodium excretion: urinary sodium, free water clearance, urinary glucose, urinary albumin, fractional sodium excretion, urinary excretion of tubular transporter proteins (aquaporin 2 [AQP2], endothelial sodium channel [ENaC], sodium chloride symporter channel [NCC], and sodium-potassium-chloride cotransporter [NKCC]), extracellular body water (EBW), total body water, intracellular body water (IBW), adipose tissue mass, and erythrocyte salt sensitivity
• Hemoglobin A 1c (HbA 1c ) and p-glucose
• β-hydroxy butyrate and urate
• Urinary excretion of adenosine, neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and interleukin 6 (IL-6)
• Plasma concentrations of parathyroid hormone, phosphate, calcium, alkali phosphatase and fibroblast growth factor (FGF23), and urinary excretion of phosphate and calcium

Study Medication

The active treatment, 10 mg of empagliflozin, and a matching placebo were produced and distributed by the manufacturer, Boehringer-Ingelheim. The placebo tablet was identical to empagliflozin in every way, except for the lack of active substance. The study medication was delivered from The Hospital Pharmacy in identical pill bottles and was allocated corresponding to the randomization number.

Compliance was checked with a phone call midway through each examination period and by pill count when the study medication was returned on the last examination day.

Study Methods

82 rubidium positron emission tomography–computed tomography.

RBF was measured with 82 Rubidium positron emission tomography–computed tomography ( 82 Rb-PET/CT) scans. All scans were performed on a Siemens Biograph mCT; 64 slice-4R (Siemens Healthcare GmbH). The method has been previously described by Langaa et al [ 43 , 44 ].

Participants rested in a sitting position for at least 30 minutes prior to the scan. During the scan, participants were placed in a supine position with arms resting over their heads. After positioning, a low-dose CT scan (25 mAs, 100 kV) was performed for attenuation control. This was immediately followed by a bolus injection of 555 megabecquerel (MBq) 82 Rb through a peripheral venous catheter (PVC), whereafter an 8-minute dynamic PET scan was performed. Through iterative reconstruction, 3D images of the activity changes in the abdominal aorta and the parenchyma of both kidneys were generated.

A 1-tissue compartment model was used for flow estimation, and RBF was calculated as a K1-value based on activity uptake in the abdominal aorta and both kidneys. Values were calculated using PMOD (PMOD Technologies Ltd).

82 Rb was obtained using an 82 Rb-generator (Cardiogen-82; Bracco Diagnostics Inc). Scans were done in cooperation with The Department of Nuclear Medicine, Regional Hospital Gødstrup.

Venous Occlusion Strain Gauge Plethysmography

Vasodilatory function was measured using classic forearm venous occlusion plethysmography (Hokanson EC6) as previously described by Fredslund et al [ 45 ], although we did not perform measurements in the contralateral arm. An indium-gallium strain gauge placed around the forearm senses changes in forearm volume. Changes in forearm volume during brief, very fast, occlusions (using the Hokanson E20 inflator) of venous outflow by a cuff on the upper arm will then reflect the arterial inflow. The plethysmography method, therefore, allows direct assessment of the effects of vasoactive drugs infused into the brachial artery. In this project, we used the infusion of acetylcholine (ACh) and sodium nitroprusside (SNP) for the evaluation of endothelium-dependent and independent vasodilatation, respectively.

GFR was determined through clearance of 99m Technetium-diethylene-triamine-pentaacetate ( 99m Tc-DTPA). Through a PVC, 25 MBq of 99m Tc-DTPA was injected intravenously. Before injection, a zero sample was drawn. Blood samples were drawn after 3, 4, and 5 hours, measuring residual plasma 99m Tc-DTPA activity, whereby GFR was calculated. Measurements were done in cooperation with The Department of Nuclear Medicine, Regional Hospital Gødstrup.

Blood Pressure Measurement and Arterial Stiffness

24-Hour ambulatory brachial blood pressure, heart rate, pulse wave velocity, and arterial stiffness were measured with Mobil-O-Graph (IEM GmbH).

Biochemical Analyses

Plasma and serum levels of sodium, HbA 1c , glucose, brain natriuretic peptide, potassium, albumin, creatinine, phosphate, parathyroid hormone, alkali phosphatase, urate, total protein, hemoglobin, erythrocyte volume fraction, thrombocytes, and calcium were routinely analyzed by The Department of Biochemistry, Gødstrup Hospital, Denmark. β-hydroxy butyrate was measured with a FreeStyle Precision Neo point of care devise (Abbott Laboratories).

Plasma levels of renin, angiotensin II, aldosterone, and vasopressin were measured by radioimmunoassay. Plasma levels of cyclic guanosine monophosphate (cGMP) and fibroblast growth factor 23 (FGF23) were measured by enzyme-linked immunosorbent assay (ELISA).

Plasma and urine levels of nitrite and nitrate were measured by spectrophotometry.

Erythrocyte salt sensitivity was measured with a salt blood test (CARE Diagnostica Laborreagenzien GmbH). Plasma and urinary osmolality were measured by freeze point depression with an A2O osmometer (Advanced Instruments).

Plasma and urinary levels of MBL, collectin kidney 1 (CL-K1), collectin liver 1 (CL-L1), mannan-binding lectin serine protease (MASP) 1-3, C4c, C3c, C3dg, sC5b-9, and urinary exosomes were measured at The Department of Cardiovascular and Renal Research, University of Southern Denmark.

Urine volume and urinary levels of sodium, creatinine, albumin, calcium, and phosphate were measured routinely by The Department of Biochemistry, Gødstrup Hospital, Denmark.

Urinary levels of glucose, aquaporin 2 (AQP2), epithelial sodium channel (ENaC), sodium chloride symporter channel (NCC), and sodium-potassium-chloride cotransporter (NKCC) were measured by radioimmunoassay; cGMP, IL6, neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and adenosine were measured by ELISA.

Bioimpedance Measurement

EBW, total body water, intracellular body water, and Adipose Tissue Mass were measured with bioimpedance spectroscopy using a body composition monitor (Fresenius Medical Care AG & Co KGaA).

Renal Hemodynamics

Renal vascular resistance was calculated as mean arterial pressure/RBF. Filtration fraction was calculated as GFR/renal plasma flow. Afferent and efferent arteriolar resistance were calculated using the Gomez equations [ 46 ].

Data following a normal distribution was calculated with parametric statistics. Paired data were compared with either paired 2-tailed t test or ANOVA. Nonparametric statistics were applied if variables were not normally disrupted. Paired comparisons were compared with Wilcoxon Signed Rank test or Friedman test. Statistics were performed using STATA (version 18.0; StataCorp LLC).

Experimental Procedure

Prior to examination.

Fluid intake was standardized from 4 days prior to the first examination day till the last examination day in each treatment period. Each participant was encouraged to drink at least 2 L of water per day, and 2 cups of coffee or tea daily was allowed, except for 8 hours prior to the examinations. Alcohol or soft drinks were prohibited in this period. The use of mouthwash products was prohibited throughout the study period. Furthermore, in each treatment period, participants were encouraged to adhere to their usual diets from 4 days prior to the first examination and till the last examination. Participants were not required to fast prior to the examination but did not eat throughout the examinations.

Examination Day: University Clinic in Nephrology and Hypertension, Gødstrup Hospital

Participants were set to meet at 8 AM, having ingested their usual medication and the study medication. First, participants emptied their bladder, body weight was measured, and they rested in a chair for 30 minutes. A pregnancy test was performed on fertile women. Then, a PVC was inserted and the Mobil-O-Graph was placed on the upper arm, opposite the PVC. At time point 0 blood samples were drawn and a bolus injection of 99m Tc-DTPA was given ( Figure 2 ). After this, the 82 Rb-PET/CT scan was performed. Two successive body composition monitor measurements were done within the first 2 hours of the examination day.

Urine was collected at 2 and 5 hours and if additional voiding was necessary. All urine, except the first void, was pooled and analyzed. From the first void, 50 mL of fresh spot urine was collected, a protease inhibitor was added, and the sample was frozen for later exosome analyses. Two mL of spot urine, also from the first void, was frozen for analysis of complement factors. Blood samples were drawn at 3, 4, and 5 hours. At the end of the examination day, body weight was measured again. The Mobil-O-Graph was removed by the participant 24 hours after mounting. During the entire examination day, participants were to rest in a bed or on a chair. Voiding was done standing or sitting. Participants were given 175 mL of water each hour from time point 0 till the end of the examination day.

Examination Day: Department of Renal Medicine, Aarhus University Hospital

The strain gauge plethysmography was performed at the Department of Renal Medicine, Aarhus University Hospital ( Figures 3 and 4 ). Participants had taken their usual medication and the study medication on the morning prior to the examination. Participants were placed in a supine position in a room where the temperature was kept fixed at 25 °C. The brachial artery was then cannulated with a 27-gauge needle and kept from clotting by a slow infusion of isotonic saline. The strain gauge was placed on the broadest part of the forearm, a venous occlusion cuff was placed on the upper arm, and an arterial occlusion cuff was placed at the wrist. After 30 minutes of saline infusion, baseline measurements were recorded (8 readings were performed per measurement). ACh was infused in increasing concentrations at 5-minute intervals. Measurements were recorded at each concentration. After the last measurement, saline was infused for another 30 minutes. Afterward, isotonic glucose was infused for 5 minutes, and new baseline measurements were recorded. SNP was now infused in increasing concentrations again at 5-minute intervals, with measurements done at each concentration. Arterial circulation to the hand was interrupted during infusion. When the last measurement had been performed, the infusion was stopped, the needle was removed, and the examination day ended.

Due to delivery issues, ACh was replaced with carbachol (CCh) after the first 23 participants had been examined. Two participants, both in the DM2 and CKD group, had their first examination done with ACh and the second with CCh. The remaining examinations were done entirely with CCh.

Ethical Considerations

All 3 studies were approved by The Central Denmark Region Committees on Health Research Ethics (cases: 1-10-72-214-20, 1-10-72-339-20, and 1-10-72-340-20, respectively) and The Danish Medicines Agency (EU Clinical Trials Register: 2019-004303-12, 2019-004447-80, and 2019-004467-50) and were conducted in accordance with the Declaration of Helsinki 2013. Informed and signed consent was obtained from all participants. The study was monitored by the Good Clinical Practice (GCP) Unit of Aarhus and Aalborg University Hospitals. All the data have been deidentified. Participants could be compensated for travel expenses related to the studies.

Approval from the regulatory agencies was obtained for the first study (DM2 and preserved kidney function) by October 2020. Recruitment began in April 2021. Approval for the remaining studies was obtained by May 2021 and recruitment began in March 2022. The inclusion of participants for all studies was completed by September 2022. Examinations started in August 2021 and were completed (last patient, last visit) by December 2022. In total, 49 participants completed the project: 16 in the DM2 and preserved kidney function study, 17 in the DM2 and CKD study, and 16 in the nondiabetic CKD study. Data analysis is currently ongoing. So far, no results from the project have been published.

Future Perspectives

In this paper, we present the background, hypothesis, design, and methodology of a project consisting of 3 RCTs examining the effects of the SGLT2i empagliflozin versus placebo on a wide range of parameters in different patient populations. This will hopefully provide important information on the mechanisms underlying the beneficial effects of SGLT2is and is the first project to examine both patients with and without diabetes and with and without CKD using the same experimental setup. To our knowledge, very few mechanistic studies have examined SGLT2is in a CKD population.

We use a novel method for estimating RBF by using 82 Rb-PET/CT. Compared with measuring effective renal plasma flow (ERPF) with para-aminohippuric acid (PAH) clearance, a method often used in other studies examining hemodynamic effects of SGLT2is [ 20 , 23 , 47 ], flow estimation with 82 Rb-PET/CT can be performed much quicker (in less than half an hour) without the need for blood or urine samples and allows for estimation of single kidney RBF. Furthermore, the effective radiation dose of a single scan is limited (≈1 milliSievert [mSv]). There is an ongoing discussion around whether our method in fact reflects RBF or rather RPF. This should be taken into account when calculating intrarenal hemodynamics since the calculations rely on which parameter is used. However, the method has proven both precise and reliable when evaluating relative changes in kidney perfusion, which is what we assess in this project [ 43 , 44 ].

Vascular function and SGLT2is have been studied widely, as specified in the introduction, though mainly by flow-mediated dilation [ 34 , 35 ]. The venous occlusion strain-gauge plethysmography gives a more in-depth examination of the potential mechanisms at play by measuring both endothelial-dependent and independent vasodilation.

A clear strength of our project is the robust, randomized, placebo-controlled, crossover design. We examine different patient populations using the exact same design, allowing for comparison of effect between groups. Furthermore, we investigate a number of different variables, allowing for different mechanisms to be examined. With the current updated guidelines, all 3 examined groups represent patient populations who would be offered SGLT2is in a clinical setting, which adds to the generalizability of our results. It is important to note that inclusion in the DM2 and CKD group did not require a diagnosis of diabetic nephropathy, so participants could potentially have kidney disease or other etiologies. We used 10 mg of empagliflozin and not the 25-mg dose, since this was the dose used in the EMPA-KIDNEY study and since both doses have equivalent effects on both renal outcomes and eGFR decline [ 8 ].

Limitations

Our project has several limitations: one being the small study sample sizes, increasing the risk of the studies being underpowered for detecting changes in secondary end points. In addition to being a strength, examining multiple mechanisms of action can be a limitation, since it increases the risk of type 1 errors; thus, most of our secondary end points should be interpreted as exploratory. Our inclusion criteria are broad by design, mainly to reflect a real-world patient population that could potentially be prescribed SGLT2is, but the broad criteria make for a more heterogeneous study population and increase the risk of heterogeneity of the outcome effects. Despite being a well-known risk factor for disease progression in both DM2 and CKD [ 48 ], we did not make albuminuria an inclusion criterion. We chose this approach because albuminuria was not an inclusion criterion for all patients in either the EMPA-REG OUTCOME, DECLARE-TIMI 58, or EMPA-KIDNEY trial [ 49 - 51 ], although it was in the CREDENCE and DAPA-CKD trials [ 9 , 12 ]. By allowing the inclusion of patients without albuminuria, we risk including patients at low risk where treatment benefits could be less pronounced. Furthermore, patients were not fasting before examinations, nor did we take steps to ensure stable blood glucose levels throughout the examination days. This was considered, but discarded for feasibility reasons, but it does increase the risk of our outcomes being affected by confounders. Adding to this was the fact that we allowed for the substitution of antidiabetic treatment in the run-in period if SGLT2is were paused. This was done to ensure glycemic control during the trial period but may have introduced further confounding. This methods paper was written after data collection was completed. While it would have been optimal to publish it prior to inclusion, we judge this to be a precise description of the methods used and it will provide a valuable framework for future articles, detailing exactly how our results were obtained and what considerations lay behind them.

Conclusions

This paper describes the rationale, design, and method used in a project consisting of 3 double-blind, crossover RCTs, examining the effects of empagliflozin versus placebo in patients with DM2 with and without CKD and patients with nondiabetic CKD, respectively.

Acknowledgments

This project is supported by The Augustinus Foundation, The Research Foundation of the Central Denmark Region, The Medicine Fund of the Danish Regions, The Research Fund of the Hospital of Western Jutland, and Boehringer-Ingelheim, who delivered the study medication, including placebo.

Boehringer-Ingelheim was given the opportunity to review the manuscript for medical and scientific accuracy as it relates to Boehringer-Ingelheim substances, as well as intellectual property considerations. Boehringer-Ingelheim had no role in the design of the study nor will they have a role in the analysis and interpretation of results.

Authors' Contributions

All authors contributed to the manuscript. SFN, JNB, NHB, and FHM designed the project. SFN drafted the manuscript. SFN, CLD, JNB, NHB, and FHM edited the manuscript. All authors approved the final manuscript. Generative artificial intelligence was not used in any portion of the manuscript.

Conflicts of Interest

FHM disclosed advisory board participation and speaker honoraria from Boehringer-Ingelheim and AstraZeneca. JNB disclosed advisory board participation for AstraZeneca, Boehringer, and Bayer. SFN, CLD, and NHB have no conflicts of interest to declare.

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Abbreviations

Edited by S Ma; submitted 04.01.24; peer-reviewed by IA Eide, C Ott, E Kodani; comments to author 24.04.24; revised version received 25.04.24; accepted 25.04.24; published 29.05.24.

©Steffen Flindt Nielsen, Camilla Lundgreen Duus, Niels Henrik Buus, Jesper Nørgaard Bech, Frank Holden Mose. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 29.05.2024.

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Systems Biology and Kidney Disease

The kidney is a complex organ responsible for maintaining multiple aspects of homeostasis in the human body. The combination of distinct, yet interrelated, molecular functions across different cell types make the delineation of factors associated with loss or decline in kidney function challenging. Consequently, there has been a paucity of new diagnostic markers and treatment options becoming available to clinicians and patients in managing kidney diseases. A systems biology approach to understanding the kidney leverages recent advances in computational technology and methods to integrate diverse sets of data. It has the potential to unravel the interplay of multiple genes, proteins, and molecular mechanisms that drive key functions in kidney health and disease. The emergence of large, detailed, multilevel biologic and clinical data from national databases, cohort studies, and trials now provide the critical pieces needed for meaningful application of systems biology approaches in nephrology. The purpose of this review is to provide an overview of the current state in the evolution of the field. Recent successes of systems biology to identify targeted therapies linked to mechanistic biomarkers in the kidney are described to emphasize the relevance to clinical care and the outlook for improving outcomes for patients with kidney diseases.

Why Is a Systems Approach Needed to Tackle Kidney Diseases?

The kidney plays a central role in maintaining homeostasis in the human body. To successfully carry out these functions, the kidney contains numerous cell types arranged in the complex three-dimensional structure of the nephron to respond to a variety of hormonal, neuronal, inflammatory, and intra- and intercellular signals. The network of complex, intertwined regulatory functions across different cell types make the delineation of specific mechanism associated with loss or decline in kidney function challenging. Clinical trials for the development of diagnostic markers and novel therapies targeting kidney diseases have consequently been limited ( 1 – 3 ), resulting in few prevention and treatment options available to clinicians and patients.

Much of our knowledge of kidney physiology and pathophysiology has been gleaned from a reductionist approach, where careful experimentation has elucidated the effect of one molecular pathway on kidney health and disease, mostly in animal models. However, many kidney diseases, most notably CKD and AKI, comprise diseases of multiple etiologies. Thus, patients enrolled in clinical trials often have heterogeneous disease mechanisms activated, which has likely contributed to the low success rate of clinical trials of pathway-specific targets in nephrology. Biomarkers to further classify subgroups of patients, thus far, have focused more on clinical features rather than on molecular mechanisms that might indicate efficacy of putative therapies. Integrating a wide spectrum of information on the underlying disease mechanism using a systems biology approach has the potential to addresses some of these challenges. This strategy leverages our existing granular knowledge obtained through traditional reductionist approaches toward a holistic understanding of disease processes in a given patient.

A global, or systems biology, approach takes advantage of recent developments in computational methods to integrate diverse types of data, such as molecular, tissue, and clinical parameters, to unravel the interplay of multiple genes, proteins, and molecular mechanisms ( Figure 1 ) that drive discrete steps in kidney health and disease ( 4 , 5 ). A core element of this strategy is the integration of various data sources, including conventional clinical phenotypic patient data, clinicopathologic parameters, and comprehensive genome-scale data sets (also referred to as “omics”) through bio-informatics analytical workflows. Integrating such diverse data into analytical processes necessitate the blending of a variety of expertise including clinical, biologic, information technology, mathematical, statistical, and computational research in nephrology research teams. Sophisticated information technology infrastructure is required to manage and connect information across research and health care. Meanwhile, software tools for analysis and interpretation of data need “integrative workflows” that involve a combination of statistical, computational, and mathematical techniques ( 6 , 7 ). The purpose of this review is to provide an overview of the current state in the evolution of systems biology for the nephrologist. By highlighting the advances made through this approach toward developing targeted therapies linked to mechanistic biomarkers, the potential effect on clinical care and improving outcomes for patients with kidney diseases are discussed ( 8 – 10 ).

Integrative systems approach to address challenges in kidney disease. A systems biology approach to the kidney adds to the reductionist approach by leveraging recent advances in computational technology and methods to integrate diverse sets of data.

What Is Systems Biology and How Does It Work?

The understanding of what systems biology encompasses has evolved and the definition of “systems biology” has reflected these changes over time ( 11 ). The National Centers for Systems Biology’s definition emphasizes the use of advanced computational modeling techniques and high-throughput technologies to integrate physical, computational, and experimental sciences in biomedical research ( 12 ). For the purposes of this review, we define systems biology as the use of computational modeling and mathematical techniques in developing an integrative picture of a biologic system derived from multiple types of data.

The types and complexity of data used in this approach have also evolved with advances in biologic and computational capabilities. Initially, linking one gene to one phenotype was considered systems biology; the example of HER2 and breast cancer is used later in this paper ( 13 ). Development of microarray technologies, single-nucleotide polymorphism arrays for genome-wide association studies, or Affymetrix microarrays for gene expression analysis, formed the first phase of “big data” that allowed researchers to examine thousands of genes or transcripts at one time. Development of multiple cell- and organ-scale molecular (omic) platforms, focusing on changes in fundamental cellular components like DNA, RNA, and proteins, have enabled the generation of substantial quantities of data that can comprehensively map the human genome, transcriptome, proteome, and metabolome ( Figure 1 ). Combining the insights derived through each platform in healthy and disease states is now at the heart of systems biology approaches aiming to define the underlying biology of a complex organ like the kidney.

In addition to omics data, there are increasing amounts of non-omic, large-scale data derived from clinical settings that are becoming available to kidney researchers. These include the digital transformation of traditional phenotype-defining clinical features, like histopathology. Digital pathology using whole-slide imaging (WSI) is poised to transform the practice of diagnostic pathology. WSI data sets can now be treated as a data type of equal complexity to genomic data and can be integrated with other data types ( 14 ). In nephrology, kidney biopsies are used routinely in clinical practice for the diagnosis and management of glomerular diseases. Therefore, the availability of tissue samples combined with digital pathology promises to generate comprehensive structural information ( 15 ). In large cohorts it has enabled unbiased capture of complex features of kidney structure and associated changes in disease ( 16 ). For example, in the Nephrotic Syndrome Study Network (NEPTUNE), careful and reproducible assessment of histologic features allowed identification of molecular pathways associated with increased interstitial fibrosis and progressive loss of kidney function ( 17 ). WSI data repositories are expanded in a series of efforts, including the recently initiated Kidney Precision Medicine Project ( kpmp.org ) for studying AKI and CKD while establishing a framework to safely obtain research kidney biopsies. Electronic health records (EHRs), electronic medical records, and epidemiologic data contain rich descriptions of health-related traits ( 18 ) and are an additional data type that can be leveraged via a system biology approach. Demographic information, such as socioeconomic factors, have been linked to CKD and its major risk factors ( 19 ), and can be incorporated into systems biology workflows. Integrating the clinical profiles, environmental exposures, and imaging data from organs and tissues with the molecular data sets is the next step in the evolution of systems biology.

The coalescence of these different data types with state of the art data integration technologies has the potential to advance our understanding of molecular mechanisms involved in kidney disease. One of the main thrusts is to move from a descriptive disease pattern ( i.e. , nephrotic syndrome) to a mechanistic disease definition (phospholipase A2 receptor [PLA2R]-positive membranous nephropathy) to identify and classify patients on the basis of characteristics relevant to disease prognosis and treatment. This is a critical step in the pursuit of personalized medicine—that is, “the right drug for the right patient at the right time.”

Systems Biology Using a Single Omic Data Type

There are now several techniques that systems biologists can use to organize omics data in a way that will uncover the molecular mechanisms involved in kidney diseases. For example, clustering algorithms using genome-wide mRNA (transcriptomics) data, can identify patients with similar expression profiles in specific tissues or cell-types in the kidney, irrespective of clinical disease status or classification. Grouping patients on the basis of these molecular signatures, rather than clinical features, helps identify common molecular pathways involved in organ or tissue damage across different kidney diseases. This type of molecular clustering has been prioritized in rare diseases such as nephrotic syndrome and ANCA vasculitis, where disease cause is wide-ranging in a relatively small patient population ( 20 ). Another useful tool applied to transcriptomics data is the development of individual, patient-level pathway activation scores. An activation score is calculated for each participant on the basis of the expression levels of every gene known to be regulated by a well established cellular pathway in a specific tissue compartment, such as the glomerulus. This score can then be used as a “read-out” for the activation or inhibition of that pathway in a specific disease (sub)type or in response to treatment exposures. Comparison across individuals on the basis of this score enables identification of common pathways, potentially implicated in the conditions and outcomes experienced by those participants. Although activation scores are not yet used in clinical practice, they hold great promise to help classify diseases. For example, as proof of concept, data-driven clustering of patients with FSGS and minimal change disease identified two subgroups of patients independent of traditional disease classification. One cluster displayed higher activation of the TNF pathway, and was associated with worse long-term outcomes, including loss of kidney function. Urinary biomarkers in the same pathway were then identified that could be used to identify patients with increased TNF activity ( 21 ). Similarly, JAK/STAT pathway activation was identified as a marker of kidney disease progression in FSGS ( 22 ) and across glomerular diseases ( 20 ). Although further elucidation and validation of these findings are needed, they illustrate the potential of systems biology in matching interventions to patients.

Systems Biology Connecting Multiple Omics Data Types

As our ability grows to generate different, comprehensive data sets from the same individuals with kidney disease, a plethora of computational methods to link multiple, heterogeneous data types have been developed ( 23 ). The most prevalent data integration methods are unsupervised, i.e. , the analysis draws an inference from input data sets without any guidance by the investigator from existing classifications. To facilitate comparison across data sets, matrix factorization–based methods like joint non-negative matrix factorization (joint-NMF) and iCluster are dimensionality reduction methods that reduce number of variables under consideration by obtaining a set of principle variables. For example, using a few metagenes to describe the patterns of expression for >20,000 genes in a data set. Commonalities within the data, across samples, are used to group variables that behave similarly. One can also use the underlying similarity structure in network-based approaches like PAthway Recognition Algorithm using Data Integration on Genomic Models (PARADIGM) and similarity network fusion (SNF), where mathematical models are used to decipher the underlying data patterns to discover regulatory networks.

The majority of these data integration strategies focus on specific aspects of the data (features), e.g. , linking a specific gene within the genomics data set with the corresponding protein from proteomics data, rather than integrating data from different samples ( e.g. , blood, urine, and tissue samples). These feature-specific approaches focus on specific genes, proteins, or metabolites and use known biologic relationship among the data types. For example, for a specific gene, what is the relationship between gene copy number variation, RNA transcription levels, and protein abundance across individuals and samples? Each omic platform measures different aspects (variables) of this interdependent biologic process. The goal of the systems biology approach, in these examples, is to identify the interconnected crosscutting signals that link a biologic process to a particular condition and can describe this process, i.e. , a network signature. For example, iCluster, a machine learning approach, was used to reveal distinct tumor subtypes ( 24 , 25 ) suggestive of different genetic pathways in colon cancer progression. This was achieved by connecting gene mutation, gene copy number, DNA methylation, and gene expression information derived from genomic, epigenomic, and transcriptomic data available for 189 tumor samples ( 24 ). In the case of CKD, such approaches could be used to determine the interconnected network signature involved in an established pathway, such as the JAK/STAT pathway, to identify inflammation-specific disease subtypes that might be responsive to targeted therapeutic interventions. However, these approaches have been limited primarily to omics data integration.

Systems Biology Integrating Omics and Non-Omic Data Types

The next challenge for systems biology is to link molecular data sets to clinical features in the absence of an a priori mapping structure. These strategies often use the patient as the anchor point to link the diverse data sets together via a participant-centric approach. These are highly flexible algorithms that can not only integrate omics data, but also include non-omic data types, such as clinical data, digital pathology, and even environmental exposures and demographic information. Person-centric integration methodologies, e.g. , the frequently used SNF, construct individual networks mapping the similarities within each available data type for each person. Next, the network pattern seen in each data set are iteratively linked or “fused” together to build a consensus network mapping the patients on the basis of their similarity across all data types. The consensus network now represents all of the individual networks into a single network capturing the entire spectrum of heterogeneous, diverse data types, regardless of biologic relationship. This enables formation of distinct patient subgroups on the basis of all of the information sources available, as well as identifying key data points ( i.e. , set of genes or set of histology observations) contributing to the overall grouping. SNF methods were successfully applied to identifying and linking cancer subtypes to associated clinical outcome in five different cancers ( 26 ). With the emergence of long-term studies in kidney disease, the collected data types are not limited to omics data and include digital pathology and detailed clinical phenotyping and demographic information. Therefore, patient-centric approaches like SNF can be leveraged to delineate molecular mechanisms and pathways relevant to disease progression in different patient subgroups.

Translating Multiscalar Data into Clinical Practice with Artificial Intelligence

The future direction of system biology will involve the use of artificial intelligence (AI) approaches such as machine learning and deep learning. A specific strength of these computational processes are to extract from large-scale, multiscalar data sets clinically actionable knowledge, for example outcome predictions or risk stratifications. AI is especially well suited to tackle the challenges of scalability ( e.g. , going from cell level to a patient population), and high dimensionality ( e.g. , number of variables and data types describing each sample) of data. Natural language processing has enabled information to be automatically extracted and summarized from electronic medical records or from manually written doctor notes ( 27 – 30 ). In another example, AI has transformed medical image reading ( 31 ) in diagnosing metastatic breast cancer ( 32 ), melanoma ( 33 ), and several eye diseases ( 34 ). In the kidney, applications range from AI-based prediction of AKI events across diverse EHR systems ( 35 ) via noninvasive, AI-based GFR estimation from kidney ultrasound imaging ( 36 ), to AI-driven identification for patients at risk of rapid loss of kidney function via a combination of EHR-derived clinical parameters and a targeted biomarker panel ( 37 ).

Why Systems Biology in Nephrology Now?

The past decade has seen the development of multiple cohorts across a wide spectrum of kidney diseases with associated rich, multilevel data sets, including genome, transcriptome, proteome, digital pathology, and prospective long-term clinical characteristics and outcomes. These studies have also collected and stored a variety of biosamples, including blood, urine, kidney tissue, and DNA, which ensures that these cohorts will continue to contribute data as novel technologies and mathematical techniques are discovered.

As several of these studies have now prospectively ascertained clinically meaningful endpoints, the comprehensive information from these patient cohorts can now be used to address key questions asked of nephrologists by patients in clinical care settings: “Why do I have this disease?”, “What will this disease do to me?”, and “What treatment options do I have?”. Defining kidney diseases in mechanistic terms has the potential to provide new starting points for pathophysiology-driven disease definition and management.

Application of Systems Biology to Improve Clinical Care

Oncology has provided a framework for how systems biology approaches can be used to provide new answers to at least some of the fundamental challenges in nephrology. The following examples highlight the application of systems biology approaches to complex disease processes to develop new solutions for diagnosis and treatment.

HER2 in Breast Cancer

Personalized medicine in cancer started with the use of imatinib, targeting the 922 translocation ( 38 ), in chronic myeloid leukemia but is best described through examples in breast cancer. Multiple studies in breast cancer in the 1980s demonstrated alterations in the expression pattern of a single transmembrane protein, HER2, in breast cancer could explain some of the underlying biology in tumor progression. Tumors that were positive for HER2 were associated with more aggressive biology, leading to poorer outcomes for patients ( 13 ). A systems biology approach was able to associate a specific single genetic aberration with clinical outcome, leading to the development of anti-HER2 therapies via an mAb against HER2, trastuzumab. This drug has shown immense clinical benefit in treating HER2-positive, metastatic breast cancers ( 39 ) and targeted agents are considered the standard of care in oncology clinics ( 40 ), paving the way for 140 therapies targeting 95 different genetic aberrations to be approved by the US Food and Drug Administration ( 41 ).

Gene Signature Score Prognostic Marker

With the advent of array technologies, thousands of genes could be measured at the same time. Using a modest cohort of 65 surgical breast tumor specimens from 42 patients, Perou et al. demonstrated that tumors can be classified into subtypes on the basis of their gene expression patterns ( 42 ), and that these subtypes showed significantly different outcomes. This led to the discovery of a 70-gene signature that was able to show that women initially identified as high risk for recurrence on the basis of clinical and pathologic factors could be reclassified because of low genomic risk, and successfully forgo chemotherapy, which was replicated in a study of 6000 patients across 112 centers ( 43 , 44 ). These findings have revolutionized patient care practices, promoted more individualized treatment, and minimized harm related to unnecessary treatments and procedures leading to improved, cost-effective care ( 45 ).

Systems Biology Effect on Clinical Care of Kidney Disease

Identification of pla2r in primary membranous nephropathy.

Salant and colleagues integrated proteomics data with clinical data to identify a protein antigen in serum samples from patients with idiopathic and secondary membranous nephropathy. Serum from patients with idiopathic membranous nephropathy contained antibodies binding to a protein band of glomerular cell lysates. Proteomic analysis of the protein band generated an extensive list of peptides, which were filtered using a systems biology approach toward a small list of candidate proteins leading to the discovery of PLA2R ( 46 ) as the main antigen in membranous nephropathy. A causal role of PLA2R for disease pathogenesis was further supported by the identification of a major risk allele associated with membranous nephropathy using a genomic approach ( 47 ). These independent lines of evidence from omics data sets implicating PLA2R in the pathophysiology of membranous nephropathy have, like HER2 in cancer, established a mechanistically homogenous subgroup of patients with membranous nephropathy. Antibodies against PLA2R are now an integral part of clinical practice for diagnosis and management of primary membranous nephropathy. The serum test is used to monitor disease activity and guide treatment decisions regarding immunosuppressive therapy withdrawal ( 48 ). Efforts are underway to combine the serum test with genetic testing for noninvasive disease diagnosis and monitoring. Clinical trials, like Membranous Nephropathy Trial of Rituximab, can now use the molecular-defined disease types to document the specificity of the interventions ( 49 ).

Impaired kidney function particularly in early stages of CKD remains difficult to accurately prognosticate with eGFR and urinary protein excretion as the only available tests in clinical practice. There have been numerous attempts to identify other prognostic markers for progression of CKD, with varying degrees of success. Many of these attempts have relied on using markers of acute tubular injury because tubulointerstitial fibrosis is the best-known predictor of kidney tissue outcomes. Unfortunately, some of these biomarkers are expressed in other tissues or are affected by eGFR, which makes interpretation difficult.

By analyzing the transcriptome from the tubulointerstitial compartment of >200 kidney biopsies from patients with various causes of CKD, a transcript set predicting eGFR decline was identified at the time of biopsy using an AI-based strategy ( 50 ). Among the tissue-level outcome predictors, EGF was found to be almost exclusively expressed in the distal tubular compartment of the kidney and excreted in urine. Levels of EGF measured in urine improved prediction of CKD progression compared with models that relied only on eGFR and urine protein. This biomarker has since been validated in >10,000 patients and has shown robust ability to improve prediction of CKD progression and prognosis ( 51 – 53 ).

Identification of JAK-STAT as a Drug Target for Diabetic Kidney Disease

Integration of clinical and tissue transcriptomics data of patients with diabetic kidney disease identified the JAK-STAT pathway as a potential molecular target for therapeutic intervention ( 54 ). Animal models supported the involvement of this pathway in mediating responses to important fibrotic factors such as TGF β , leading to a phase 2 clinical trial of diabetic kidney disease where the JAK inhibitor, baricitinib, demonstrated a dose dependent decrease in albuminuria, the established biomarker for diabetic kidney disease ( 55 ). Target engagement biomarkers predicted by systems biology approach from human diabetic kidney diseases cohorts were able to detected the response to JAK inhibition after 14 days, preceding observable responses in albuminuria levels by 10 weeks.

A New Level of Resolution: Single-Cell Analyses Unveiling the Molecular Architecture of the Kidney

One of the key challenges in defining molecular mechanisms of kidney disease is the cellular heterogeneity of the kidney, second probably only to the human brain ( 56 ). Sustained efforts to overcome this challenge include microdissection of kidney tissue and biopsies for molecular analysis ( 57 , 58 ), development of profiling technologies for individual microdissected cells ( 59 ), and computational efforts to define cell type–specific signals from complex kidney biopsies signatures ( 60 ). The recent development of genome-wide single-cell RNA sequencing (scRNAseq) of cell populations harvested from kidney tissues and biopsies harbors unparalleled opportunities to dissect molecular mechanisms of kidney function and disease ( 61 – 63 ). This technology contributes another dimension of cell-level data and will test the ability of systems biology approaches to link signals derived from molecularly defined kidney cell populations with an individual phenotype. scRNAseq relies on cell separation techniques combined with omic technologies to generate a cell type–specific molecular profile ( 63 ). Thus far, scRNAseq has been successfully applied to mouse kidney ( 64 ), human kidney allografts ( 61 ), and organoids ( 62 , 65 ), and explored in lupus nephritis ( 66 , 67 ) and glomerular disease ( 62 ). Technologies are being developed to integrate the signals assigned to a kidney cell state into the tissue context of the healthy and diseased organs, with research networks dedicated to define the cellular compartments of the kidney in molecular terms (Human Cell Atlas, HCA.org [ 68 ]; and HubMap [ 69 ]) and in diseases states, with the Kidney Precision Medicine Project targeting AKI and CKD ( kpmp.org ), NEPTUNE proteinuric diseases ( Neptune-study.org ), and the Accelerating Medicines Partnership rheumatoid arthritis and lupus program ( amp-ralupus.stanford.edu [ 67 ]). Generating and analyzing several thousand genes in >10,000 cells from an individual patient poses unprecedented challenges and strategies are still being developed to integrate the data deluge from single-cell data with phenotypic and histologic data types, among others. However, first compelling insights of the power of these strategies are starting to emerge, giving us a new window how the intrakidney immune defense is set up in a spatially orchestrated manner to counteract invading pathogens in the healthy kidney ( 70 ), or how specific tissue resident macrophage populations in lupus nephritis can be recovered from urinary single cell studies to monitor the immune state of the kidney in lupus ( 67 ).

With the convergences of nanotechnology, molecular biology, and computational biology as applied to the kidney in its infancy, we should be prepared to find more novel insights into the molecular intricacies of human kidney disease.

Summary and Outlook

Systems biology is opening up paths forward for improved care for our patients with kidney disease ( Figure 2 ). Integration of omics and nonomics data provide opportunities for identifying new molecular signatures indicative of disease progression, disease subtypes, and common shared disease pathways. These molecular signatures are the basis for developing specific biomarkers and related clinical assessments to help with diagnosis and prognosis. The molecular pathways can also help prioritize optimal therapeutic targets for molecular intervention and clinical trials.

The systems biology process toward targeted treatments in nephrology. The emergence of large, detailed, multilevel biological and clinical data from national databases, cohorts studies and trials provide critical pieces needed to improve the pathway to targeted treatments in nephrology.

Challenges to the systems biology approach include the need to keep pace with our increasing capacity to capture the cellular and molecular complexity of the kidney. Researchers have to identify ways to link the data emerging from these novel technologies with other data types, most importantly clinical presentation and the variable outcomes seen across diseases. The identification of PLA2R-positive membranous nephropathy provides a compelling example of how a complex multiomics research effort led to an ELISA test now routinely used to manage patients. The feasibility and costs associated with translating the accumulation of large quantities of data into meaningful options for personalized medicine in the clinic is a frequently raised concern. However, requirements for making omics data publicly available, diverse bioinformatics, computational capabilities, and iteratively increasing knowledge about molecular mechanisms allow the same data sets to be queried in different ways by the global kidney research community to answer numerous questions. Further, judicious use of specimens and careful biobanking allow for measurements with multiple omics platforms from a single sample provided by an individual participating in a study.

Thus, systems biology provides the techniques and tools necessary to build a comprehensive and integrated picture of the kidney, both in health and disease. The foundations laid by successes in oncology, increasing availability of digitized clinical data, and the investments made in developing longitudinal studies provide the other key pieces needed for accelerated innovations in the prevention and treatment of kidney diseases. The rapid emergence of a multitude of targeted therapies from these efforts has already changed the field of clinical research in nephrology, with 20 clinical trials active in primary glomerular diseases alone ( kidneyhealthgateway.com ), allowing our patients for the first time to ask a core question in precision medicine: which is the best trial for me?

Disclosures

Dr. Kretzler reports receiving grants from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Elpidera, European Union Innovative Medicine Initiative, Gilead Sciences, Goldfinch Bio, Janssen, JDRF, Merck, and Novo Nordisk, all outside of the submitted work. Dr. Kretzler also reports holding a United States patent on “Biomarkers for CKD progression,” encompassing urinary EGF as biomarker of CKD progression. Dr. Hamidi, Dr. Schaub, and Dr. Subramanian have nothing to disclose.

Dr. Kretzler is supported by grants from the National Institutes of Health (NIH) and receives nonfinancial support from the University of Michigan . Support for this work is through the George M. O’Brien Michigan Kidney Translational Core Center, funded by NIH/ National Institute of Diabetes and Digestive and Kidney Diseases grant 2P30-DK-081943, awarded to Dr. Kretzler.

Published online ahead of print. Publication date available at www.cjasn.org .

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