clinical research basic terminology

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NIA Glossary of Clinical Research Terms

Adverse Event (AE) – Any untoward or unfavorable medical occurrence in a clinical research study participant, including any abnormal sign (e.g. abnormal physical exam or laboratory finding), symptom, or disease, temporally associated with the participants’ involvement in the research, whether or not considered related to participation in the research.

Baseline – The initial time point in a clinical trial that provides a basis for assessing changes in subsequent assessments or observations. At this reference point, measurable values such as physical exam, laboratory tests, and outcome assessments are recorded.

Bias – A point of view or preference which prevents impartial judgment in the way in which a measurement, assessment, procedure, or analysis is carried out or reported.

Case Report Form (CRF) – A printed, optical, or electronic (eCRF) document designed to capture all protocol-required information for a study.

Coordinating Center (CC) – A group organized to coordinate the planning and operational aspects of a multi-center clinical trial. CCs may also be referred to as Data Coordinating Centers (DCCs) or Data Management Centers (DMCs).

Clinical Research or Study Coordinator (CRC) – An individual that handles the administrative and day-to-day responsibilities of a clinical trial and acts as a liaison for the clinical site. This person may collect the data or review it before it is entered into a study database.

Clinical Research – NIH defines clinical research as:

• Patient-oriented research. Research conducted with human subjects (or on material of human origin such as tissues, specimens and cognitive phenomena) for which an investigator directly interacts with human subjects. Excluded from this definition are in vitro studies that utilize human tissues that cannot be linked to a living individual. Patient-oriented research includes: (a) mechanisms of human disease, (b) therapeutic interventions, (c) clinical trials, or (d) development of new technologies.
• Epidemiologic and behavioral studies .
• Outcomes research and health services research.

Clinical Trial – NIH defines a clinical trial as a research study in which one or more human subjects are prospectively assigned to one or more interventions (which may include placebo or other control) to evaluate the effects of those interventions on health-related biomedical or behavioral outcomes. Clinical trials are used to determine whether new biomedical or behavioral interventions are safe, efficacious, and effective. Behavioral clinical trials involving an intervention to modify behavior (diet, physical activity, cognitive therapy, etc.) fit this definition of a clinical trial.

Concomitant Medication – Prescription and over-the-counter drugs and supplements a study participant has taken along with the study intervention. This information may be collected as a history item as well as during the study. Some studies may collect only those medications that may interact with the study or intervention or that may exclude an individual from participating in a study.

Conflict of Interest – A conflict of interest occurs when individuals involved with the conduct, reporting, oversight, or review of research also have financial or other interests, from which they can benefit, depending on the results of the research. Control Group – The group of individuals in a clinical trial assigned to a comparison intervention.

Controlled Clinical Trial – A clinical trial in which at least one group of participants is given a test intervention, while at least one other group concurrently receives a control intervention.

Data Management – The processes of handling the data collected during a clinical trial from development of the study forms/CRFs through the database locking process and transmission to statistician for final analysis.

Data Management Plan (DMP) – A plan that documents the processes for handling the flow of data from collection through analysis. Software and hardware systems along with quality control and validation of these systems, as relevant are described.

Data and Safety Monitoring Board (DSMB) –A group of individuals independent of the study investigators that is appointed by the NIA to monitor participant safety, data quality and to assess clinical trial progress.

Data and Safety Monitoring Plan (DSMP) – Plan included with the grant application for clinical trials which establishes the overall framework for data and safety monitoring, how adverse events will be reported to the IRB and the NIH and, when appropriate, how the NIH Guidelines and FDA regulations for INDs and IDEs will be satisfied. 

Efficacy – Indication that the clinical trial intervention produces a desired therapeutic effect on the disease or condition under investigation.

Eligibility Criteria – List of criteria guiding enrollment of participants into a study. The criteria describe both inclusionary and exclusionary factors, (e.g. inclusion criterion - participants must be between 55 and 85 years old; exclusion criterion – must not take drug X three month prior to the study). Food and Drug Administration (FDA)  – An agency within the U.S. Department of Health and Human Services (DHHS) responsible for protecting the public health by assuring the safety, efficacy, and security of human and veterinary drugs, biological products, medical devices, nation’s food supply, cosmetics, and products that emit radiation.

Good Clinical Practice – A standard for the design, conduct, performance, monitoring, auditing, recording, analyses, and reporting of clinical trials that provides assurance that the data and reported results are credible and accurate, and that the rights, integrity, and confidentiality of trial participants are protected.

Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule – The first comprehensive Federal protection for the privacy of personal health information. The Privacy Rule regulates the way certain health care groups, organizations, or businesses, called covered entities under the Rule, handle the individually identifiable health information known as protected health information (PHI).

Human Subject – A patient or healthy individual who is or becomes a participant in research, either as a recipient of the intervention or as a control.

Informed Consent – A process by which a participant or legal guardian voluntarily confirms his or her willingness to participate in a particular trial, after having been informed of all aspects of the trial that are relevant to the participant’s decision to take part in the clinical trial. Informed consent is usually documented by means of a written, signed, and dated informed consent form, which has been approved by an IRB/IEC .

Informed Consent Form – A document that describes the rights of a study participant and provides details about the study, such as its purpose, duration, required procedures, and key contacts. Risks and potential benefits are explained in the informed consent document. Institutional Review Board (IRB)/Independent Ethics Committee (IEC) – An independent body constituted of medical, scientific, and nonscientific members whose responsibility it is to ensure the protection of the rights, safety, and well-being of human subjects involved in a trial by, among other things, reviewing, approving, and providing continuing review of trials, protocols and amendments, and of the methods and material to be used to obtaining and documenting informed consent of the trial participant.

Intervention – A procedure or treatment such as a drug, nutritional supplement, gene transfer, vaccine, behavior or device modification that is performed for clinical research purposes.

Investigational New Drug Application (IND) – An IND is a request for authorization from the Food and Drug Administration (FDA) to administer an investigational drug or biological product to humans. Such authorization must be secured prior to interstate shipment and administration of any new drug or biological product that is not the subject of an approved New Drug Application or Biologics/Product License Application (21 CFR 312).

Masking/Blinding – A procedure in which the investigator administering the assessments and intervention as well as the participants in a clinical trial are kept unaware of the treatment assignment(s). Single blinding usually refers to the study participant(s) being unaware, and double blinding usually refers to the study participant(s) and any of the following being unaware of the treatment assignment(s): investigator(s), monitor, and data analyst(s).

Manual of Procedures (MOP) – A set of procedures describing study conduct. A MOP is developed to facilitate consistency in protocol implementation and data collection across study participants and clinical sites.

N ew Drug Application (NDA) – An application submitted by the manufacturer of a drug to the FDA, after the clinical trial has been completed, for a license to market the drug for a specified indication.

Observational Study Monitoring Board (OSMB)  – The safety and data monitoring body for observational studies with large or vulnerable populations or risks associated with tests or standard of care.  

Office for Human Research Protection (OHRP) – A federal government agency within the Department of Health and Human Services (DHHS) charged with the protection of human subjects participating in government funded research. It issues assurances and oversees compliance of regulatory guidelines by research institutions.

Open-Label Trial – A clinical trial in which investigators and participants know which intervention is being administered.

Pharmacokinetics – The process (in a living organism) of absorption, distribution, metabolism, and excretion of a drug or vaccine.

Phase I – clinical trials to test a new biomedical intervention in a small group of people (e.g., 20-80) for the first time to evaluate safety (e.g., to determine a safe dosage range and to identify side effects). It can include healthy participants or patients.

Phase II – clinical trials to study the biomedical or behavioral intervention in a larger group of people (several hundred) to determine efficacy and to further evaluate its safety. It is conducted in participants with the condition or disease under study and will determine common short-term side effects and risks.

Phase III – studies to investigate the efficacy of the biomedical or behavioral intervention in large groups of human subjects (from several hundred to several thousand) by comparing the intervention to other standard or experimental interventions as well as to monitor adverse effects, and to collect information that will allow the intervention to be used safely.

An NIH-defined Phase III clinical trial is a broadly based prospective Phase III clinical investigation, usually involving several hundred or more human subjects, for the purpose of evaluating an experimental intervention in comparison with a standard or controlled intervention or comparing two or more existing treatments. Often the aim of such investigation is to provide evidence leading to a scientific basis for consideration of a change in health policy or standard of care. The definition includes pharmacologic, non-pharmacologic, and behavioral interventions given for disease prevention, prophylaxis, diagnosis, or therapy. Community trials and other population-based intervention trials are also included.

Phase IV – studies conducted after the intervention has been marketed. These studies are designed to monitor effectiveness of the approved intervention in the general population and to collect information about any adverse effects associated with widespread use.

Placebo – A placebo is an inactive pill, liquid, powder, or other intervention that has no treatment value. In clinical trials, experimental treatments are often compared with placebos to assess the treatment's effectiveness.

Placebo Controlled Study  – A method of investigation in which an inactive substance/treatment (the placebo) is given to one group of participants, while the test article is given to another group. The results obtained in the two groups are then compared to see if the investigational treatment is more effective in treating the condition.

Protocol – A document that describes the objective(s), design, methodology, statistical consideration, and organization of a trial.

Protocol Amendments – A written description of a change(s) to or formal clarification of a protocol.

Protocol Deviations – Failure to conduct a study as described in the protocol. The failure may be accidental or due to negligence and in either case, the protocol deviation should be documented. This also includes failure to comply with federal laws and regulations, the institution's commitments and policies, and standards of professional conduct and practice. Examples of noncompliance include:

• failure to obtain/maintain approval for research,
• failure to obtain informed consent when required,
• failure to file adverse event reports,
• performance of an unapproved study procedure,
• performance of research at an unapproved site,
• failure to file protocol modifications and
• failure to adhere to an approved protocol.

Protocol Deviations Report – Internal document created as part of the ongoing quality control process summarizing compliance with the protocol and listing protocol deviations and/or violations.

Prospectively Assigned  – A pre-defined process (e.g., randomization) specified in an approved protocol that stipulates the assignment of research subjects (individually or in clusters) to one or more arms (e.g., intervention, placebo or other control) of the clinical trial. 

Quality Assurance (QA) – Systematic approach to ensure that the data are generated, documented (recorded), and reported in compliance with the protocol and good clinical practice (GCP) standards.

Quality Control (QC) – The internal operational techniques and activities undertaken within the quality assurance system to verify that the requirements for quality of trial related activities have been fulfilled (e.g., data and form checks, monitoring by study staff, routine reports, correction actions, etc.).

Randomization – The process of assigning clinical trial participants to treatment or control groups using an element of chance to determine the assignments in order to reduce bias.

Recruitment Plan – The plan that outlines how individuals will be recruited for the study and how the study will reach the recruitment goal.

Retention Plan – The plan that details the methods in which the study will use in order to retain study participation in the clinical trial.

Safety Monitoring Plan – A plan that outlines the oversight of a clinical trial.

Safety Officer (SO)  – An independent individual, often a clinician who is appointed by the NIA and performs data and safety monitoring activities in low-risk, single site clinical studies. The SO advises the NIA regarding participant safety, scientific integrity, and ethical conduct of a study. The SO is advisory to the Institute Director. 

Screening Log – An essential document that records all individuals who entered the screening process. The screening log demonstrates the investigator’s attempt to enroll a representative sample of participants.

Screening Process – A process designed to determine individual’s eligibility for participation in a clinical research study.

Serious Adverse Event (SAE) – Any adverse event that:

• Results in death
• Is life threatening, or places the participant at immediate risk of death from the event as it occurred
• Requires or prolongs hospitalization
• Causes persistent or significant disability or incapacity
• Results in congenital anomalies or birth defects
• Is another condition which investigators judge to represent significant hazards

Source Document – Original documents, data, and records (e.g., hospital records, clinical and office charts, laboratory notes, memoranda, participant diaries, recorded data from automated instruments, x-rays, etc.) that are used in a clinical trial.

Standard Operating Procedure (SOPs) – Detailed written instructions to achieve uniformity of the performance of a specific function across studies and patients at an individual site.

Stopping Rules –Established safety criteria that would either pause or halt a study due to reasons including but not limited to futility or risk(s) to the participants.

Stratification – Separation of a study cohort into subgroups or strata according to specific characteristics such as age, gender, etc., so that factors which might affect the outcome of the study, can be taken into account.

Unanticipated Problems (UAPs) – Unanticipated problems involving risks to subjects or others, which meet all of the following criteria:

• Unexpected in terms of nature, severity, or frequency;
• Related or possibly related to participation in the research, and;
• Suggests that the research placces subjects or others at a greater risk of harm (including physical, psychological, economic, or social harm) than was previously known or recognized.

Unmasking/Unblinding – A procedure in which one or more parties to the trial are made aware of the treatment assignment(s).

Unanticipated Adverse Device Effects (UADEs) – Any serious adverse effect on health or safety or any life-threatening problem or death caused by, or associated with, a device, if that effect, problem, or death was not previously identified in a nature, severity, or degree of incidence in the investigational plan or application (including a supplementary plan or application) or any other unanticipated serious problem associated with a device that relates to the rights, safety, or welfare of subjects.

Glossary Sources:

Clinical Trials.gov NINDS Glossary of Clinical Research Terms CenterWatch, Inc. Patient Resources: Glossary. OHRP website NIH Definitions Friedman LM, Furberg CD, DeMets DL. Fundamentals of Clinical Trials (3 ed.). Missouri: Mosby-Year Book Inc., 1996. Meinert CL. Clinical Trials: Design, Conduct, and Analysis . New York: Oxford University Press, Inc., 1986.

Return to the NIA Clinical Research Investigator's Toolbox .

Last updated: February 22, 2023

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Glossary of Clinical Trial Terms

There are a lot of words and terms about clinical research that may be new to you. This section provides definitions for words and terms you may want to know.

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Adverse Event

A negative change or medical occurrence that happens during a clinical trial or within a certain time period after the trial has ended. An adverse event may or may not be caused by the treatment being studied.

Arm assignment

The assignment of a group or subgroup of participants in a clinical trial to receive interventions, or no interventions, as specified in the study protocol.

A procedure (e.g. a blood test, scan, etc.) used to generate data required by the trial.

Background therapy

Background therapy is the current medication that is routinely taken as a standard of care for a particular condition/disease.

A type of clinical trial design in which one or more parties involved with the trial, such as the research team or participant, do not know which treatments have been assigned to which participants. See Double-blind and Single-blind below.

Control 

The control or “standard” treatment is compared against the investigational treatment. It is there to show that an approved treatment in the trial works, and the investigational treatment is compared against it.

Clinical study

A research study conducted in human volunteers to answer specific health questions. Interventional studies determine whether experimental treatments or new ways of using known therapies are safe and effective under controlled environments. 

Cross-over trial

A clinical trial where groups of volunteers are administered two or more interventions in a specific order. For example, a “two-by-two” cross-over trial design is where one group receives drug A at the beginning of the trial and then receives drug B for the rest of the trial. In the second group, participants receive drug B first and then drug A. Thus, the term “cross-over” is used to describe the order in which they are assigned; for example drug A and then drug B, or drug B and then drug A. All participants receive both drugs during the study.

Dosing discontinuation

Point/time when a patient volunteer permanently stops taking study drug for any reason. This may be at the end of the study or before the end if the patient wants to stop taking the medicine for some reason.

Double-blind

In a double-blind trial, only the study pharmacist knows what study medication a participant is receiving; the participants, doctors, nurses, and other clinical trial staff are not informed.

Early patient withdrawal (premature withdrawal) 

Point/time when a patient exits from a trial prior to the planned completion of all investigational/trial drug administration and all assessments (including follow-up).

Eligibility Criteria

The requirements that people who want to participate in a clinical study must meet. Eligibility Criteria include both inclusion criteria and exclusion criteria and are defined in the protocol.

European Medicines Agency (EMA)

European Medicines Agency. An agency of the European Union that oversees the use of medicinal products. 

The point, or time, of a volunteer’s entry into the trial, after informed consent has been obtained. The same term may also be used to define the number of participants in a clinical trial. 

Epoch 

The planned stage of the volunteers’ participation in the trial. Typical epochs are: determination of subject eligibility, wash-out of previous treatments (i.e., a period of time when previous treatments are stopped), exposure of subject to treatment, or the follow-up on subjects after treatment has ended.

Food and Drug Administration (FDA)

Food and Drug Administration. A government agency within the U.S. Department of Health and Human Services that oversees the Nation's public health by making sure that human and veterinary drugs, vaccines, biological products, medical devices, cosmetics, dietary supplements, the food supply, and any products that give off radiation are safe, effective, and secure.

Health Authority

A national or international health agency that has authority over and regulates a clinical study.

A disease, symptom, or particular set of circumstances that make a particular test, medication, procedure, or surgery advisable. For a treatment, an indication refers to the use of that treatment in treating a particular disease.

Informed consent

Informed consent is used by researchers to explain the clinical trial to potential volunteers. Its purpose is to protect the participant. It is used when somebody who is interested in participating first asks about the study and it continues throughout the study, until the study ends. The research team will review the details of the trial with the potential participant and will answer any questions. This information is also written in a document, known as the informed consent form, which is designed to be clear and easy to understand. If a person decides to enrol in a clinical trial, they will sign the informed consent form to acknowledge that they understand the details of the trial and consent to participating. The informed consent form is not a contract and the participant can withdraw from the trial at any time, and for any reason. 

Institutional Review Board (IRB)

An IRB (also known as an independent ethics committee (IEC), ethical review board (ERB) or research ethics board (REB)) is a group of doctors, scientists, advocates, researchers, and members of the community that has been formally designated to review and monitor all research involving humans. IRBs are in place to provide ethical oversight and to minimize risk to participants.

Interventional study 

Also known as a clinical trial, a type of clinical study in which participants receive one or more interventions, according to the protocol and group that they are assigned to, so that researchers can evaluate the effects of the intervention on a health condition.

Investigational drug 

The drug being evaluated in the trial; this definition is synonymous with “investigational new drug” or “investigational medicinal product.”

Medication number 

A unique number on the label of each investigational drug package that is used in a trial to dispense and track medication. The number is used to make sure the drug is supplied in the right quantities to different research centers.

Observational study

An observational study investigates health outcomes amongst groups of people in the course of their everyday life at home, work, or the doctor’s office, where assignment of treatments or other procedures is as part of their regular medical care (not assigned by an investigator).

Outcome measure

In clinical trials, a set measurement that is described in the protocol and is used to evaluate the effect of an intervention on participants.

A subdivision of a single protocol into major building blocks. These parts often are independent of each other and have different objectives or different groups of volunteers. For example, a single-dose design and a multiple-dose design may be combined into one protocol (a protocol with two parts) or the same study design could be used with different groups of patients with different severity of a disease.

Categories, defined by the Food and Drug Administration (FDA), for describing the clinical trial of a drug based on the study's characteristics, such as the objective and number of participants. There are four phases:

• Phase I trials test an experimental drug, vaccine or device in a small group of people to evaluate safety, identify side effects and determine safe dosages. 
• Phase II trials involve larger groups of people than Phase I and they are designed to assess whether an experimental treatment is safe and whether it works. This phase can last several years. 
• Phase III trials are usually large studies comparing the experimental drug or vaccine to a placebo or standard treatment, to evaluate whether the drug works and collect information to allow it to be used safely. 
• Phase IV trials are performed once a drug has reached the market, to provide additional information about the best use of the drug.

Placebos are inactive substances. In a clinical trial a placebo, made to look like the investigational treatment, is sometimes used to compare against the actual investigational treatment to evaluate effectiveness. 

Principal Investigator

The person who is responsible for the scientific and technical direction of the clinical trial at a specific clinical site. In most cases the principal investigator will be a leading physician in the disease area being studied. 

A written study plan on which the clinical trial is based. A protocol describes what types of people may or may not participate in the trial; the schedule of tests, procedures, medications, and dosages to be administered; the outcome measures that will be evaluated; and the length of the study.

Randomized allocation

A strategy in which participants are randomly assigned to study arms of a clinical trial by computer.

Randomization number 

A unique number assigned to each randomized patient that is used to identify individuals but maintain anonymity, corresponding to a specific study arm assignment.

Run-in period 

The elapsed time before a trial starts when no investigational drug is given to trial participants. During this time patients may still receive standard treatments for their disease if these treatments are allowed within the trial period.

Serious adverse event

An adverse event that is life-threatening, requires hospitalization or extended hospital stay, results in ongoing or significant incapacity, causes congenital anomalies or birth defects, or results in death.

The Sponsor is the organization or person who oversees multiple sites conducting the clinical trial. 

Study completed date

The date on which the last trial participant made the final visit to the study location (that is, "last subject, last visit") and the last samples were collected or last tests performed. 

An individual (either a healthy volunteer or a patient volunteer) whose reactions or responses to certain interventions are evaluated during a clinical trial. May also be referred to as a trial participant.

Subject number

A unique number assigned to each participant who enrols into a clinical trial.

Variable 

Information collected during a clinical trial either from direct or indirect data. For example, one variable might be “weight,” which would then be checked at specified time points throughout the trial.

Wash-out period

The period of time allowed for all of the administered drug to be eliminated from the body.

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• Adverse Drug Reaction (ADR)
• Adverse Event (AE)
• Adverse Reaction (AR)
• Age of majority
• AIR (Activities Interests and Relationships)
• ALCOA (Attributable, Legible, Contemporaneous, Original, Accurate)
• ALCOA Plus, ALCOA+
• Ancillary review
• Applicable Clinical Trial (ACT)
• Applicable regulatory requirements
• Approved drug
• Aspirational benefit
• Association for Clinical and Translational Science (ACTS)
• Association for the Accreditation of Human Research Protection Programs (AAHRPP)
• Association of Clinical Research Professionals (ACRP)
• Audit report
• Audit trail
• Baseline assessment
• Billing Coverage Analysis (BCA)
• Biological Product
• Biological specimen
• Biologics License Application (BLA)
• Biomedical Research Imaging Center (BRIC)
• Biospecimen
• Biospecimen Processing Facility (BSP)
• Breach of confidentiality
• Budget justification
• Budget period
• Budget revision
• Business Associate
• Business Associate Agreement (BAA)
• Carolina Data Warehouse for Health (CDW-H)
• Case Report Form (CRF)
• Ceded review
• Centers for Disease Control and Prevention (CDC)
• Centers for Medicare & Medicaid Services (CMS)
• Centralized monitoring
• Certificate of Confidentiality (CoC)
• Certified copy
• Clinical and Translational Research Center (CTRC)
• Clinical and Translational Science Awards (CTSA) Program
• Clinical development
• Clinical investigation
• Clinical monitor
• Clinical research
• Clinical Research Accountability Unit (CRAU)
• Clinical Research Associate (CRA)
• Clinical Research Coordinator (CRC)
• Clinical Research Management System (CRMS)
• Clinical Research Support Office (CRSO)
• Clinical significance
• Clinical study
• Clinical trial
• Clinical Trial Agreement (CTA)
• ClinicalTrials.gov
• Clinical Trials Quality Assurance (CTQA) Program
• Code of Federal Regulations (CFR)
• Co-investigator
• Collaborative Institutional Training Initiative (CITI)
• Collateral benefit
• Commercial Institutional Review Board (IRB)
• Common data model
• Common Rule
• Common Terminology Criteria for Adverse Events (CTCAE)
• Compensation
• Competitive Renewal
• Computable Phenotype
• Concomitant medication
• Confidential Disclosure Agreement (CDA)
• Confidentiality
• Conflict of Interest (COI)
• Conflict of Interest Office
• Consent capacity
• Continuing noncompliance
• Continuing review
• Contract Research Organization (CRO)
• Control group
• Coordinating Center (CC)
• Corrective and Preventive Action (CAPA) Plan
• Data acquisition
• Data and Safety Monitoring Board (DSMB)
• Data and Safety Monitoring Committee (DSMC)
• Data and Safety Monitoring Plan (DSMP)
• Database Management System (DBMS)
• Data encryption
• Data Integrity
• Data management
• Data Management and Sharing Plan (DMS Plan)
• Data Management Plan (DMP)
• Data Management System (DMS)
• Data Monitoring Committee (DMC)
• Data Use Agreement (DUA)
• Delegation of Authority (DOA) Log
• Demographic data
• Department of Health and Human Services (DHHS)
• Direct benefit
• Direct cost
• Disapproval
• Discontinue
• Disease registry
• Dosage regimen
• Dose Limiting Toxicity (DLT)
• Double blinding
• Drug toxicity
• ECRT (Effort Certification and Reporting Technology)
• Electronic Case Report Form (eCRF)
• Electronic Data Capture (EDC)
• Electronic Health Record (EHR)
• Electronic Informed Consent (eIC)
• Electronic Medical Record (EMR)
• Elements of informed consent
• Eligibility criteria
• Embryonic Stem Cell Research Oversight (ESCRO) Committee
• Encounter Level Data
• Environment, Health and Safety (EHS)
• Essential document
• Exclusion criteria
• Exculpatory language
• Exempt review
• Expanded access
• Expedited review
• Experimental drug
• Experimental group
• Export Compliance Office
• Export control
• Fabrication
• Falsification
• Family Educational Rights and Privacy Act (FERPA)
• FDA Form 482
• FDA Form 483
• FDA Form 1571
• FDA Form 1572
• Feasibility assessment
• Federalwide Assurance (FWA)
• Food and Drug Administration (FDA)
• Food, Drug and Cosmetics Act
• Free text data
• Full board review
• Generalizability, Generalization
• Good Clinical Practice (GCP)
• Grant application
• Grant Number
• Greater than minimal risk
• Health literacy
• Healthy volunteer
• HIPAA authorization
• HIPAA covered entity
• HIPAA (Health Insurance Portability and Accountability Act)
• HIPAA Privacy Rule
• Humanitarian Device Exemption (HDE)
• Humanitarian Use Device (HUD)
• Human Research Protection Program (HRPP)
• Human subject
• Human Subjects Research (HSR)
• Identifiable biospecimen
• Identifiable private information
• Impartial witness
• Inclusion criteria
• Inclusion/Exclusion (I/E) criteria
• Independent Ethics Committee (IEC)
• Independent IRB
• Indirect benefit
• Indirect Facility & Administrative (F&A) costs
• Individual Conflict of Interest (COI)
• Industry Contracting (IC)
• Industry sponsored study
• Informed Consent Form (ICF)
• Informed Consent (IC)
• Institution
• Institutional Biosafety Committee (IBC)
• Institutional Conflict of Interest (COI)
• Institutional Integrity and Risk Management (IIRM)
• Institutional Official (IO)
• Institutional Privacy Office (IPO)
• Institutional Privacy Officer
• Institutional Review Board Information System (IRBIS)
• Institutional Review Board (IRB)
• Interaction
• International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9CM)
• International Council for Harmonisation (ICH)
• Intervention
• Interventional study
• Investigation
• Investigational device
• Investigational Device Exemption (IDE)
• Investigational drug
• Investigational Drug Service (IDS)
• Investigational New Drug (IND)
• Investigational New Drug (IND) safety report
• Investigational plan
• Investigational product (IP)
• Investigator
• Investigator agreement
• Investigator-initiated study
• Investigator's Brochure (IB)
• IRB application
• IRB approval
• IRB Authorization Agreement (IAA)
• IRB expiration
• IRB of record
• Just-in-Time (JIT)
• Key information
• Legally Authorized Representative (LAR)
• Legally effective informed consent
• Letter of intent
• Life-threatening adverse event
• Limited dataset
• Lineberger Comprehensive Cancer Center (LCCC)
• Local considerations
• Longitudinal study
• Long Term Follow-Up (LTFU)
• Lost to Follow Up (LTFU)
• Manual of procedures (MOP)
• Material transfer agreement (MTA)
• Medical device
• Medical monitor
• Medical record
• Medical Record Number (MRN)
• Memorandum of understanding (MOU)
• Minimal risk
• Monitoring plan
• Monitoring report
• Multicenter study
• Multisite study
• National Institutes of Health (NIH)
• New Drug Application (NDA)
• NIH National Library of Medicine (NLM)
• NIH Public Access Policy
• No Cost Extension (NCE)
• Nonclinical study
• Noncompliance
• Nondisclosure agreement (NDA)
• Nonsignificant Risk (NSR) medical device
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Using plain language definitions can make research materials easier to read and understand.

In Spring 2020, the MRCT Center launched a small pilot project with patients and participants and other stakeholders across the research industry, to develop plain language definitions of clinical research words.

The resulting Clinical Research Glossary is now available for use!

You can find other potentially helpful glossaries here .

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Phrasal verbs like “turn in your survey” can be confusing.  What it means to “turn in” is often not clear and may be better stated as “submit” or “return” .  Guidance and appropriate substitutions can be found here .

Clinical Trials

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Glossary of clinical trial terms

The glossary below will help you understand clinical research terms often used by researchers and other scientists.

Active, not recruiting

The clinical trial is happening, but researchers are not looking for more participants at this time.

Adverse event

A medical problem that happens or worsens during a clinical trial or within a certain time period after the trial is over. An adverse event may or may not be caused by the investigational treatment a person took.

Clinical trial (or research study)

A clinical trial is a research study designed to learn how our bodies respond to investigational medicines or other investigational treatments. During the clinical trial, participants are assigned to get a treatment or sometimes, no treatment. The purpose of a trial is usually to find ways to prevent, diagnose, or treat a disease or other health condition.

Clinical trial phases

Any treatment (vaccine, medicine, medical device, or procedure) must go through 3 phases of clinical trials. Each phase tests the treatment’s safety, how well it works, amount (dose), and side effects.

A disease, disorder, syndrome, illness, or injury that researchers are studying.

Controlled trial

A type of clinical trial that compares one treatment to another treatment. Often, a new investigational treatment is compared to a standard or usual treatment (called the control). The control may be a group of participants in the same trial or a group of participants from an earlier trial or study.

Eligibility criteria

A clinical trial’s requirements for people who want to join. These include inclusion criteria (factors that allow a person to join a trial) and exclusion criteria (factors that prevent a person from joining a trial). For example, a trial might only accept participants who are above or below certain ages.

The number of participants in a clinical trial. The “estimated enrollment” is the number of participants that the researchers need for the trial.

Exclusion criteria

The factors (or reasons) that prevent a person from joining a clinical trial.

Expanded access

A process regulated by the federal agencies that allows pharmaceutical companies to provide a new investigational treatment (before it’s approved) to patients with serious diseases or conditions who cannot take part in a clinical trial.

Inclusion criteria

The factors (or reasons) that allow a person to join a clinical trial.

Informed consent

Informed consent is the process in which researchers talk with people who are thinking about enrolling, or have enrolled, in a clinical trial. They will have you read an informed consent form (ICF) that describes the possible benefits and risks. It tells you that taking part in the trial is voluntary, and that you may leave the trial at any time.

The goal of the informed consent process is to protect the participants who enroll in clinical trials. The informed consent process starts when a possible participant first asks for information about a trial and continues until the trial ends.

Informed consent form (ICF)

The document used in the informed consent process.

Investigational medication

A drug or biological product that is used in a clinical trial but has not been approved by health authorities (the drug is either not available for a doctor to prescribe or is available but not approved by the health authority for the use being studied).

Institutional Review Board (IRB)

A committee of doctors, data experts, community advocates, and others who help ensure that a trial is done in an ethical manner and the rights of participants are protected. They review, approve, and check on the trial’s plan (protocol) that explains what researchers will do during the trial. For example, they will review the informed consent form. Also called an ethics committee.

Open studies

Studies that are enrolling participants now or in the future, or involve drugs that are available for expanded access (may be used by certain patients before federal agency approval).

A look-alike substance that does not contain an active drug or treatment. A placebo is made to look, taste, and be given like the actual drug being studied.

The written description of a clinical trial. It includes the trial’s goals, design, and methods. It may also include data and science-related background information.

The organization or person who starts the trial, pays for it, and has authority and control over it.

A treatment that helps provide protection to certain infections, usually given as a shot.

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Our FAQ section has answers to commonly asked questions and a glossary of words to know.

Frequently asked questions

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Clinical Research Glossary

Expand your clinical research word power with the som clinical research glossary.

Clinical research has a highly specialized vocabulary with a vast number of acronyms and abbreviations that help facilitate scientific communication. Whether you are new to clinical research or an experienced member of the research team, understanding and remembering the nuances of clinical research vocabulary can be challenging.

To ensure a consistent and clear clinical research communication, the CRSO has created the SOM Clinical Research Glossary , a comprehensive clinical research glossary in clear and plain language that aligns with industry and regulatory standards. As the glossary is intended to be broadly applicable to various types of research and audiences, its definitions provide nuances of usage. If there are variations in how key agencies are defining a term, each definition is provided.

We need your feedback

The SOM Clinical Research Glossary is intended to be a living resource that will be periodically updated with new terms and clarifications. Please let us know, if there is a word, acronym, or abbreviation you see regularly in clinical research that is not included in the glossary or if you want to propose an alternative definition.

Clinical Research Terminology 101: Language to Know

Any medications or procedures used today, as well as new data and discoveries, had to go through extensive clinical research and trials to ensure their safety and efficacy. Clinical research is a complex procedure, but understanding how it works should not be. Knowing the right clinical research terminology can go a long way toward helping you understand how the process works.

Clinical Research and Clinical Trials: Are They the Same?

You may come across both of these terms, so it is crucial that you know the difference. Clinical research is patient-oriented research conducted on human subjects or a sample that comes from humans (i.e., organs or tissue samples), in which the researcher interacts with the subjects directly.

The most common types of patient-oriented research include:

• Investigations of how human diseases work
• Design of therapeutic interventions
• Development of new techniques or technologies
• Operation of clinical trials

Clinical research also refers to behavioral and epidemiological studies as well as healthcare services research.

A clinical trial fits under the umbrella of clinical research. It is an experiment designed to answer specific questions about treatments, illnesses, medications, and more.

Volunteers: Healthy and Patient Volunteers

The volunteers chosen for the clinical research project are either healthy people who don’t have ties to the conditions related to the study or patient volunteers who are affected by the health issues being researched.

Phases of Clinical Research

Clinical research goes through many phases.

Phase I involves clinical trials with a small group of people, generally between 20 and 80, to evaluate everything from safe dosage ranges to the type of side effects that can be expected. This phase can include patient volunteers as well as healthy participants.

Phase II takes place with a larger group of volunteers, usually a few hundred, to continue establishing safety and efficacy. This phase involves people who have the condition being studied and can help determine risks and short-term side effects.

Phase III involves thousands of participants, comparing the intervention to other similar procedures while also keeping an eye on adverse effects. This is the phase where the most information is gathered to present for approval.

Phase IV takes place after the intervention has been marketed. It can help check effectiveness in the general population and provide information on side effects.

Differences Between Single-Blind and Double-Blind Studies

Clinical research terminology will include whether the trial was single-blind or double-blind.

Single-blind means that the researchers know whether a participant is receiving a placebo or the active treatment — while the participant does not know. A double-blind study is one in which neither the researcher nor the participant knows until after the trial is over.

Serious Adverse Event

A serious adverse event is any adverse health issue that occurs in a participant during the clinical trial and:

• Is life-threatening
• Results in death
• Requires hospitalization
• Causes disability or incapacity
• Results in birth defects

Serious adverse events are investigated and determined to be related or unrelated to the treatment being studied.

Intervention

An intervention can be a procedure or a treatment like a drug, supplement, vaccine, behavior modification, or device modification.

Inclusion and Exclusion Criteria

Inclusion and exclusion criteria refer to the screening requirements that a volunteer must meet to participate in the trial. Factors can be age, sex, medical history, and much more.

Good Clinical Practice

Good clinical practice is the standard for the performance, conduct, design, auditing, recording, reporting, and analysis of clinical trials. It helps ensure that the data provided is accurate and that all of the participants’ rights are respected.

Quality Assurance and Quality Control

Quality assurance is a clinical research term that means the systematic approach that makes certain data is gathered and recorded following good clinical practices and standard protocol. It refers to operational steps taken to ensure that the trial follows all quality-related activities. These operational steps can involve checking completed forms.

Informed Consent

Before a volunteer can participate in a clinical trial, they must be given all of the information on the trial, the schedules, expected treatments, and potential adverse reactions in writing. The volunteer must sign their consent.

Randomization

Researchers help eliminate bias by turning to randomization. This is the process of assigning treatments in a random fashion.

Stopping Rules

These are the rules that would prompt the stopping of the trial. The reasons a halt to the trial can occur involve everything from safety concerns to futility.

Placebos and Placebo-Controlled Studies

A placebo is an inactive liquid, pill, powder, or other intervention that provides no treatment value. During clinical trials, placebos provide a comparison against which to measure the effectiveness of treatment.

A placebo-controlled study is a trial in which a placebo is given to a group of participants while an active intervention is given to the other group.

Open-Label Trial

This type of trial is one in which all participants and investigators know about the intervention being tested.

Manual of Procedures

The manual of procedures provides the protocol for the trial. It helps to keep protocol implementation and data collection consistent throughout the length of the trial.

The Ins and Outs of Clinical Research

Clinical research terminology can seem overwhelming, but having the basics down can help you understand the research and results.

At Orlando Clinical Research Center, we welcome participants who are interested in the research studies that are currently ongoing. Learn more by contacting us today .

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Understanding Clinical Trials

Clinical research: what is it.

Your doctor may have said that you are eligible for a clinical trial, or you may have seen an ad for a clinical research study. What is clinical research, and is it right for you?

Clinical research is the comprehensive study of the safety and effectiveness of the most promising advances in patient care. Clinical research is different than laboratory research. It involves people who volunteer to help us better understand medicine and health. Lab research generally does not involve people — although it helps us learn which new ideas may help people.

Every drug, device, tool, diagnostic test, technique and technology used in medicine today was once tested in volunteers who took part in clinical research studies.

At Johns Hopkins Medicine, we believe that clinical research is key to improve care for people in our community and around the world. Once you understand more about clinical research, you may appreciate why it’s important to participate — for yourself and the community.

What Are the Types of Clinical Research?

There are two main kinds of clinical research:

Observational Studies

Observational studies are studies that aim to identify and analyze patterns in medical data or in biological samples, such as tissue or blood provided by study participants.

Clinical Trials

Clinical trials, which are also called interventional studies, test the safety and effectiveness of medical interventions — such as medications, procedures and tools — in living people.

Clinical research studies need people of every age, health status, race, gender, ethnicity and cultural background to participate. This will increase the chances that scientists and clinicians will develop treatments and procedures that are likely to be safe and work well in all people. Potential volunteers are carefully screened to ensure that they meet all of the requirements for any study before they begin. Most of the reasons people are not included in studies is because of concerns about safety.

Both healthy people and those with diagnosed medical conditions can take part in clinical research. Participation is always completely voluntary, and participants can leave a study at any time for any reason.

“The only way medical advancements can be made is if people volunteer to participate in clinical research. The research participant is just as necessary as the researcher in this partnership to advance health care.” Liz Martinez, Johns Hopkins Medicine Research Participant Advocate

Types of Research Studies

Within the two main kinds of clinical research, there are many types of studies. They vary based on the study goals, participants and other factors.

Biospecimen studies

Healthy volunteer studies.

 Goals of Clinical Trials

Because every clinical trial is designed to answer one or more medical questions, different trials have different goals. Those goals include:

Treatment trials

Prevention trials, screening trials, phases of a clinical trial.

In general, a new drug needs to go through a series of four types of clinical trials. This helps researchers show that the medication is safe and effective. As a study moves through each phase, researchers learn more about a medication, including its risks and benefits.

Is the medication safe and what is the right dose?   Phase one trials involve small numbers of participants, often normal volunteers.

Does the new medication work and what are the side effects?   Phase two trials test the treatment or procedure on a larger number of participants. These participants usually have the condition or disease that the treatment is intended to remedy.

Is the new medication more effective than existing treatments?  Phase three trials have even more people enrolled. Some may get a placebo (a substance that has no medical effect) or an already approved treatment, so that the new medication can be compared to that treatment.

Is the new medication effective and safe over the long term?   Phase four happens after the treatment or procedure has been approved. Information about patients who are receiving the treatment is gathered and studied to see if any new information is seen when given to a large number of patients.

“Johns Hopkins has a comprehensive system overseeing research that is audited by the FDA and the Association for Accreditation of Human Research Protection Programs to make certain all research participants voluntarily agreed to join a study and their safety was maximized.” Gail Daumit, M.D., M.H.S., Vice Dean for Clinical Investigation, Johns Hopkins University School of Medicine

Is It Safe to Participate in Clinical Research?

There are several steps in place to protect volunteers who take part in clinical research studies. Clinical Research is regulated by the federal government. In addition, the institutional review board (IRB) and Human Subjects Research Protection Program at each study location have many safeguards built in to each study to protect the safety and privacy of participants.

Clinical researchers are required by law to follow the safety rules outlined by each study's protocol. A protocol is a detailed plan of what researchers will do in during the study.

In the U.S., every study site's IRB — which is made up of both medical experts and members of the general public — must approve all clinical research. IRB members also review plans for all clinical studies. And, they make sure that research participants are protected from as much risk as possible.

Earning Your Trust

This was not always the case. Many people of color are wary of joining clinical research because of previous poor treatment of underrepresented minorities throughout the U.S. This includes medical research performed on enslaved people without their consent, or not giving treatment to Black men who participated in the Tuskegee Study of Untreated Syphilis in the Negro Male. Since the 1970s, numerous regulations have been in place to protect the rights of study participants.

Many clinical research studies are also supervised by a data and safety monitoring committee. This is a group made up of experts in the area being studied. These biomedical professionals regularly monitor clinical studies as they progress. If they discover or suspect any problems with a study, they immediately stop the trial. In addition, Johns Hopkins Medicine’s Research Participant Advocacy Group focuses on improving the experience of people who participate in clinical research.

Clinical research participants with concerns about anything related to the study they are taking part in should contact Johns Hopkins Medicine’s IRB or our Research Participant Advocacy Group .

Learn More About Clinical Research at Johns Hopkins Medicine

For information about clinical trial opportunities at Johns Hopkins Medicine, visit our trials site.

Video Clinical Research for a Healthier Tomorrow: A Family Shares Their Story

Clinical Research for a Healthier Tomorrow: A Family Shares Their Story

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The glossary below will assist you in understanding the words and phrases that frequently appear on ClinicalResearch.com. Although people involved in clinical research will often use these words and phrases, the definitions here describe the words and phrases only in the context of how they appear on ClinicalResearch.com.

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Institute of Medicine (US) Committee on Strategies for Small-Number-Participant Clinical Research Trials; Evans CH Jr., Ildstad ST, editors. Small Clinical Trials: Issues and Challenges. Washington (DC): National Academies Press (US); 2001.

Small Clinical Trials: Issues and Challenges.

• Hardcopy Version at National Academies Press

Appendix B Glossary of Statistical and Clinical Trials Terms

Dorland's Illustrated Medical Dictionary , 28th edition . 1994 . Philadelphia : W. B. Saunders .

Eddy, D. M. , V. Hasselblad , and R. Shacther . 1992 . Meta-Analysis by the Confidence Profile Method . San Diego : Academic Press .

Everitt, B. S. 1995 . The Cambridge Dictionary of Statistics in the Medical Sciences . Cambridge, United Kingdom : Cambridge University Press .

Hirsch, R. P. , and R. Riegelman . 1996 . Statistical Operations . Analysis of Health Research Data . Cambridge, MA : Blackwell Science .

Last, J. M. , ed. 1995 . A Dictionary of Epidemiology . Oxford : Oxford University Press .

The set of values of a test statistic for which the null hypothesis is not rejected.

A sampling method by which the sample is taken from groups or batches as they pass a specified time point, e.g., age, followed by sampling of individuals within the sampled groups.

The late clinical stage of infection with human immunodeficiency virus (HIV), recognized as a distinct syndrome in 1981.The surveillance definition includes HIV-infected persons who have less than 200 CD4 + T lymphocytes per μL or a CD4 + T lymphocyte percentage of total lymphocytes of less than 14 percent, accompanied by any of 26 clinical conditions (e.g., opportunistic infection, Kaposi's sarcoma, wasting syndrome).

A procedure in which an initial set of subjects is selected by a sampling procedure and, whenever the variable of interest of a selected subject satisfies a given criterion, additional subjects whose values are in the neighborhood of those for that subject are added to the sample.

A sampling procedure in which the selection process depends on the observed values of some variables of interest.

A term used when the effect of administering two treatments together is the sum of their separate effects.

A model in which the combined effect of several factors is the sum of the effects that would be produced by each of the factors in the absence of the others.

A procedure for summarization of a statistical measure in which the effects of differences in composition of the population being compared have been minimized by statistical methods. Examples are adjustment by regression analysis and by standardization. See standardization.

An undesirable or unwanted consequence experienced by a subject during a clinical trial irrespective of the relationship to the study treatment.

A procedure for adjusting rates, e.g., death rates, designed to minimize the effects of differences in age composition when comparing rates for different populations.

Any systematic process that consists of an ordered sequence of steps in which each step depends on the outcome of the previous one.

An explicit description of steps to be taken in patient care in specified circumstances.

(α) The probability of a Type I error. The value of a is usually 0.05. See significance level.

The hypothesis against which the null hypothesis is tested.

An extension of the analysis of variance that allows consideration of the possible effects of covariates on the response variable, in addition to the effects of the factor or treatment variables. The covariates are assumed to be unaffected by treatments, and in general, their relationship to the response is assumed to be linear.

A statistical technique that isolates and assesses the contributions of categorical independent variables to variations in the mean value of a continuous dependent variable. The total variance of a set of observations are partitioned according to different factors, e.g., sex, age, treatment groups, and compared by way of F tests. Differences between means can then be assessed.

A sampling method in which a geographical region is subdivided into smaller areas (counties, villages, city blocks, etc.), some of which are selected at random, and the chosen areas are then subsampled or completely surveyed. See cluster sampling.

A useful way of summarizing the information from a series of measurements made on an individual over time or for a doseresponse curve. Calculated by adding the areas under the curve between each pair of consecutive observations, using for example, the trapezium rule.

The sum of all the values in a set of measurements divided by the number of values in the set.

The treatment designated to be given to a patient in a clinical trial as indicated at the time of enrollment.

Statistical dependence between two or more events, characteristics, or other variables. Most often applied in the context of binary variables forming a two-by-two contingency table. A positive association between two variables exists when the occurrence of higher values of a variable is associated with the occurrence of higher values of another variable. A negative association exists when the occurrence of higher values of one variable is associated with lower values of the other variable.

The conditions under which statistical techniques give valid results.

The cumulative incidence of a disease or condition in a particular group, during a limited period of time, or under special circumstances such as an epidemic.

The loss of subjects over the period of a longitudinal study. See missing values.

An average value represents or summarizes the relevant features of a set of values, and in this sense the term includes the median and the mode.

An experimental design in which the same number of observations is taken for each combination of the experimental factors.

A graphical representation for displaying discrete data organized in such a way that each observation can fall into one and only one category of the variable. Frequencies are listed along one axis, and categories of the variable are listed along the other axis. The frequencies of each group of observations are represented by the lengths of the corresponding bars. See histogram.

A set of data collected at the beginning of a study.

The shape taken by the hazard rate for the event of death in humans. It is relatively high during the first year of life, decreases fairly soon to a minimum, and begins to climb again sometime around ages 45 to 50.

An interval of a posterior distribution such that the density at any point inside the interval is greater than the density at any point outside. For any probability level, there is generally only one such interval, which is often known as the highest posterior density region.

Statistical inference based on Bayes's theorem. The focus of the Bayesian approach is the probability distribution of any unknowns, given available information. The process deals with probabilities of hypotheses and probability distributions of parameters, which are not taken into account in classical statistical inference.

A probability distribution having the overall shape of a vertical cross-section of a bell. Examples are normal distribution and Student's t distribution.

The ratio of net present value of measurable benefits to costs. Calculation of a benefit-cost ratio is used to determine the economic feasibility or success of a program.

The probability of a Type II error.

Deviation of results or inferences from the truth or processes leading to such a deviation. Any trend in the collection, analysis, interpretation, publication, or review of data that can lead to conclusions that are systematically different from the truth. Statistical bias occurs when the extent to which the statistical method used in a study does not estimate the quantity thought to be estimated or does not test the hypothesis to be tested.

A probability distribution or a frequency distribution with two modes.

A sequence whose elements take one of only two possible values, usually denoted 0 or 1.

A variable having only two possible values, usually labeled 0 or 1. Data involving this type of variable often require specialized statistical techniques such as logistic regression.

The probability distribution of the number of occurrences of a binary event in a sample of n independent observations. The distribution is associated with two mutually exclusive outcomes, e.g., death or survival, success or failure.

The quantitative evaluation of the potency of a substance by assessing its effects on tissues, cells, live experimental animals, or humans.

The degree to which clinically important outcomes of treatment by a new preparation resemble those of a previously established preparation.

Trials carried out to compare two or more formulations of a drug containing the same active ingredient to determine whether the different formulations give rise to comparable levels in blood.

The effect of treatment for all persons who receive the therapeutic agent to which they were assigned. It measures the biological action of a treatment among compliant persons.

The criterion that an observed, presumably or putatively causal association fits previously existing biological or medical knowledge.

The application of statistical methods to the study of numerical data on the basis of observations of biological phenomena.

The application of statistical methods to biological and medical problems.

A graphical display of multivariate data designed to show any structure, pattern, or relationship between variables.

A unit of information consisting of one binary digit.

Data in which the subjects each have measurements on two variables.

The joint distribution of two random variables, x and y.

A procedure used in clinical trials to avoid the possible bias that might be introduced if the patient or doctor, or both, knew which treatment the patient would be receiving. A trial is double blind if both patient and doctor are not aware of treatment given; if either the doctor or the patient is not aware of treatment given, the trial is single blind. Also called masking.

A term used in experimental design to refer to a homogeneous grouping of experimental units designed to enable the experimenter to isolate and, if necessary, eliminate variability due to extraneous causes.

A random allocation procedure used to keep the numbers of subjects in the different groups of a clinical trial closely balanced at all times.

Varieties of tests using electrophoresis, nucleic acid base pairing, or protein-antibody interaction to detect and identify DNA or RNA in samples. The Southern blot is used to identify a specific segment of DNA in a sample. The Northern blot detects and identifies samples of RNA. The Western blot is widely used in a test for detection of human immunodeficiency virus infection.

A data-based simulation method for statistical inference that can be used to study the variability of estimated characteristics of the probability distribution of a set of observations and provide confidence intervals for parameters in situations in which these are difficult or impossible to derive in the usual way.

A procedure for guarding against an increase in the Type I error when performing multiple significance tests. To maintain the Type I error at some selected value, a, each of the m tests to be performed is judged against a significance level, a/m. This method is acceptable for a small number of simultaneous tests to be performed (up to five).

The relating of causes to the effects that they produce. A cause is termed “necessary” when it must always precede an effect. This effect need not be the sole result of the one cause. A cause is termed “sufficient” when it inevitably initiates or produces an effect. Any given cause may be necessary, sufficient, neither necessary nor sufficient, or both necessary and sufficient.

Observation with an unknown value due to the occurrence of an event (e.g., death, loss to follow-up, or termination of study) before the occurrence of the event of interest in the study.

The tendency for the sampling distribution of means to be a normal (Gaussian) distribution, even if the data do not have a Gaussian distribution, for sufficiently large numbers of subjects.

The range within which the central 90 percent of values of a set of observations lie.

A property of the distribution of a variable usually measured by statistics such as the mean, median, and mode.

In genetics, the presence in an individual of cells of different origin, such as of blood cells derived from a dizygotic cotwin.

The probability distribution of the sum of squares of a number of independent standard normal variables.

Any statistical test based on comparison of a test statistic to a chi-square distribution. The most common chi-square tests (e.g., the Mantel-Haenszel and Pearson chi-square tests) are used to detect whether two or more population distributions differ from one another. These tests usually involve counts of data and may involve comparison of samples from the distribution under study or comparison of a sample to a theoretically expected distribution.

A test applied to a two-dimensional contingency table in which one variable has two categories and the other has k ordered categories to assess whether there is a difference in the trend of the proportions in the two groups.

A procedure designed to provide insight into the structure of a clinical problem and to identify the main determinants of diagnostic and therapeutic choice. This procedure is useful to small numbers of clinical cases, even to a single patient (see n -of-1 study). The procedure has four stages: 1. Definition of the clinical problem and structuring it as a decision tree. This includes description of the patient, of the possible diagnostic and therapeutic actions, and of the possible outcomes after treatment. 2. Estimation of probabilities for diagnostic and therapeutic outcomes. 3. Performance of the requisite computations for determination of the preferred course of action. 4. Presentation of the results of the analysis in a clinically useful way.

Epidemiological study conducted in a clinical setting, usually by clinicians, with patients as the subjects of study. It uses the information from classic epidemiology to aid decision making about identified cases of disease.

A prospective study that involves human subjects, designed to determine the effectiveness of a treatment, a surgical procedure, or a therapeutic regimen administered to patients with a specific disease. Clinical trials have four phases:

Safety and pharmacologic profiles. This involves the initial introduction of a candidate vaccine or drug into a human population to determine its safety and mode of action. In drug trials, this phase may include studies of dose and route of administration. Phase I trials usually involve less than 100 healthy volunteers.

Pilot efficacy studies. This initial trial aims to examine efficacy in about 200 to 500 volunteers. The focus of vaccine trials is immunogenicity, whereas with drugs the focus is on the demonstration of safety and efficacy in comparison with those of other existing regimens. Often, subjects are randomly allocated to study and control groups.

Extensive clinical trial. This phase aims to complete assessment of safety and efficacy. It involves large numbers, possibly thousands, of volunteers from one center or many centers (a multicenter trial), usually with random allocation to study and control groups.

This phase is conducted after the national drug registration authority (the Food and Drug Administration in the United States) has approved the drug for distribution or marketing. The trial is designed to determine a specific pharmacological effect or the effects of long-term use or to establish the incidence of adverse reactions. Ethical review is required in phase IV trials.

The distinction between results in terms of their possible clinical importance rather than simply in terms of their statistical significance. For example, very small differences that have little or no clinical importance may turn out to be statistically significant. The implications of any finding in a medical investigation must be judged on both clinical and statistical grounds.

The study of indices and rating scales used to describe or measure symptoms, physical signs, and other clinical phenomena in clinical medicine.

See sequential analysis.

A set of statistical methods for constructing a sensible and informative classification of an initially unclassified set of data using the variable values observed on each individual or item.

A sampling method in which each unit (cluster) selected is a group of persons (all persons in a city block, a family, a school, or a hospital) rather than an individual.

A formal statement of desirable conduct that research workers or practitioners are expected to honor. Examples are the Hippocratic Oath, the Nuremberg Code, and the Helsinki Declaration.

A measure of the agreement among several rankings or categories.

The square of the correlation coefficient between two variables. It gives the proportion of the variation in one variable that is accounted for by the other.

A measure of spread for a set of data, defined as 100 x standard deviation / mean. Originally proposed as a way of comparing the variability in different distributions but found to be sensitive to errors in the mean.

Very high correlation between variables. See multicollinearity.

A disease(s) that coexist(s) in a study participant in addition to the index condition that is the subject of study.

The probability that event A occurs given the outcome of some other event, event B ; usually written P (A|B). Conditional probabilities obey all the axioms of probability theory. See Bayes's theorem.

The computed interval with a given probability, e.g., 95 percent, that the true value of a variable such as a mean, proportion, or rate is contained within the interval.

The upper and lower boundaries of the confidence interval.

A method of meta-analysis that uses a set of quantitative techniques that include parameters, functions, and prior distributions (in a Bayesian application). Its goal is to use evidence to derive maximum likelihood estimates and covariances (in a non-Bayesian application) or joint probability distributions (in a Bayesian application) for parameters of interest. Distributions and estimates can be used to make decisions about interventions or calculations of other parameters or to plan research to gather additional information about any parameter.

A process observed in some factorial designs in which a measure of the effect of an exposure on risk is distorted because of the association of the exposure with some other factor(s) that influences the outcome under study.

A variable that can cause or prevent the outcome of interest, is not an intermediate variable, and is associated with the factor under investigation.

A tabular cross-classification of data such that subcategories of one characteristic are indicated horizontally (in rows) and subcategories of another characteristic are indicated vertically (in columns). The simplest contingency table is the fourfold or two-by-two table analyzed by using the chi-square statistic. Three- and higher-dimensional tables are analyzed by using log-linear models.

An approach that applies Bayesian inference to determine the maximum tolerated dose in a phase I trial. The method begins by assuming a logistic regression model for the dosetoxicity relationship and a prior distribution for the parameters. After each patient's toxicity result becomes available, the posterior distribution of the parameters is recomputed and used to estimate the probability of toxicity at each of a series of dose levels.

Subjects with whom comparison is made in a case-control study, randomized controlled trial, or some other variety of epidemiological study.

A phase III clinical trial in which an experimental treatment is compared with a control treatment, the latter being either the current standard treatment or a placebo.

Statistics calculated from sample values X 1 , X 2 , . . . , X n that elicit information about some characteristic of a process that is being monitored.

The degree to which variables change together.

An index that quantifies the linear relationship between a pair of variables. The coefficient takes values between −1 and 1, with the sign indicating the direction of the relationship and the numerical magnitude indicating its strength. A value of zero indicates the lack of any linear relationship between two variables.

A square, symmetric matrix with rows and columns corresponding to variables in which the off-diagonal elements are correlations between pairs of variables and the elements on the main diagonal are unity.

An economic analysis in which the costs of medical care and the benefits of reduced loss of net earnings due to the prevention of premature death or disability are considered. The general rule for the allocation of funds in a cost-benefit analysis is that the ratio of marginal benefit (the benefit of preventing an additional case) to marginal cost (the cost of preventing an additional case) should be equal to or greater than 1.

A method that allows the hazard function to be modeled on a set of explanatory variables without making restrictive assumptions about the dependence of the hazard function on time. Estimates of the parameters in the model, i.e., β 1 , β 2 , . . ., β p , are usually obtained by maximum likelihood estimation and depend only on the order in which events occur, not on the exact time of their occurrences.

The values of a test statistic that lead to rejection of a null hypothesis. The size of the critical region is the probability of obtaining an outcome belonging to this region when the null hypothesis is true, i.e., the probability of a Type I error. See also acceptance region.

The value with which a statistic calculated from sample data is compared to determine whether a null hypothesis should be rejected. The value is related to the particular significance level chosen.

The division of data into two subsets of approximately equal size, one of which is used to estimate the parameters in some model of interest and the other of which is used to assess whether the model with these parameter values fits adequately.

A listing of the sample values of a variable together with the proportion of the observations less than or equal to each value.

An approach that involves identification of all available choices and the potential outcomes of each in a series of decisions that must be made about aspects of patient care: diagnostic procedures, therapeutic regimens, and prognostic expectations. The range of choices can be plotted on a decision tree, where at each branch or decision node the probabilities of each outcome are displayed.

A concept used in decision analysis that tells the experimenter how to conduct the statistical aspects of an experiment and what action to take for each possible outcome. See also loss function.

A graphical representation of the alternatives available at each stage in the process of decision making, where decision options are represented as branches and subsequent possible outcomes are represented as further branches. The decisions and the eventualities are presented in the order in which they are likely to occur. The junction at which a decision must be taken is called a “decision node.”

The number of independent units of information in a sample relevant to the estimation of a parameter or calculation of a statistic. For example, in a contingency table it is one less than the number of row categories multiplied by one less than the number of column categories. Also used to refer to a parameter of various families of distributions, such as chi-square, Student's t , and F distributions.

A variable whose value is dependent on the effect of another variable(s)—an independent variable(s)—in the relationship under study. In statistics, it is the variable predicted by a regression equation.

A general term for methods of summarizing and tabulating data that make their main features more transparent, for example, calculating means and variances and plotting histograms.

A measure of the extent to which a particular model differs from the saturated model for a data set.

Synonym for binary variable.

The direction of inference of a study, i.e., retrospective or prospective, or of the relationship between variables, such as a negative or a positive association indicated by a correlation coefficient.

Variables having only integer values, e.g., number of births or number of pregnancies.

A statistical analytical technique used on multivariate data that aims to assess whether or not a set of variables distinguish or discriminate between two (or more) groups of individuals. It separates sets of observed values and allocates new values from two (or more) discrete populations to the correct population with minimal probability of classification.

The complete summary of the frequencies of the values or categories of a measurement obtained for a group of persons. It tells either how many or what proportion of the group was found to have each value (or each range of values) out of all the possible values that the quantitative measure can have.

A function that gives the relative frequency with which a random variable falls at or below each of a series of values. Examples include normal distribution, lognormal distribution, chi-square distribution, t distribution, F distribution, and binomial distribution.

A clinical trial, usually undertaken at a late stage in the development of a drug, to obtain information about the appropriate magnitude of initial and subsequent doses. Most common is the parallel-dose design, in which one group of subjects is given a placebo and other groups are given different doses of the active treatment.

A plot of the values of a response variable against the corresponding values of the dose of drug received or level of exposure endured.

A relationship in which a change in amount, intensity, or duration of exposure is associated with a change—either an increase or a decrease—in the risk of a specified outcome.

A procedure of blind assignment to study and control groups and blind assessment of outcome, designed to ensure that ascertainment of outcome is not biased by knowledge of the group to which an individual was assigned. Double refers to both subjects or patients and observers or clinicians.

The variables resulting from recording of categorical variables with more than two categories into a series of binary variables.

A quantity that measures the effect of a factor on the frequency or risk of health outcome. Three such measures are attributable fractions, which measure the fraction of cases due to a factor; risk and rate differences, which measure the amount a factor adds to the risk or rate of a disease; and risk and rate ratios, which measure the amount by which a factor multiplies the risk or rate of disease.

A factor that modifies the effect of a putative causal factor under study. For example, age is an effect modifier for many conditions, and immunization status is an effect modifier for the consequences of exposure to pathogenic organisms. Effect modification is detected by varying the selected effect measure for the factor under study across levels of another factor.

The effect of a treatment relative to the effect a control treatment in the ideal situation in which all persons fully comply with the treatment regimen to which they were assigned by random allocation.

A clearly defined outcome or event associated with an individual in a medical investigation. An example is the eath of a patient.

A state of genuine uncertainty about the benefits or harms that may result from each of two or more regimens. A state of equipoise is an indication for a randomized controlled trial because there are no ethical concerns about one regimen being better for a particular patient.

The error of rejecting a true null hypothesis, i.e., declaring that a difference exists when it does not.

The error of failing to reject a false null hypothesis, i.e., declaring that a difference does not exist when in fact it does.

Either a single number (point estimate) or a range of numbers (interval estimate) which is inferred to be plausible for some parameter of interest.

The process of providing a numerical value for a population parameter on the basis of information collected from a sample. If a single figure for the unknown parameter is calculated, the process is called “point estimation.” If an interval within which the parameter is likely to fall is calculated, the procedure is called “interval estimation.”

A statistical method based on the actual, i.e., “exact,” probability distribution of the study data rather than on an approximation such as the normal or chi-square distribution, e.g., Fisher's exact test.

A study in which conditions are under the direct control of the investigator. A population is selected for a planned trial of a regimen whose effects are measured by comparing the outcome of the regimen in the experimental group with the outcome of another regimen in a control group. Clinical trials fall under this heading.

A clinical trial designed to explain how a treatment works.

A term that is used in a variety of ways in statistics but that is most commonly used to refer to a categorical variable, with a smaller number of levels, under investigation in an experiment as a possible source of variation.

A set of statistical methods for analysis of the correlations among several variables to estimate the number of fundamental dimensions that underlie the observed data and to describe and measure those dimensions.

A method of setting up an experiment or study to ensure that all levels of each intervention or classificatory factor occur with all levels of the others and that their possible interactions are investigated. The simplest factorial design is one in which each of two treatments or interventions is either present or absent so that subjects are divided into four groups: those receiving neither treatment, those receiving only the first treatment, those receiving only the second treatment, and those receiving both treatments.

The proportion of cases in which a diagnostic test indicates that a disease is absent from patients who have the disease.

The proportion of cases in which a diagnostic test indicates that a disease is present in disease-free patients.

The probability distribution of the ratio of two independent random variables, each having a chi-square distribution, divided by their respective degrees of freedom.

A scheme designed to estimate the maximum tolerated dose during a phase I clinical trial, using as few patients as possible. Using the National Cancer Institute standards for adverse drug reactions, the procedure begins patient accrual with three patients at an initial dose level and continues at each subsequent dose level until at least one toxicity of grade 3 or above is encountered. Once the latter occurs, three additional patients are entered at that level and six patients are entered into each succeeding level. The search scheme stops when at least two of six patients have toxicities of grade >3.

The test for association in a two-by-two table that is based upon the exact hypergeometric distribution of the frequencies within the table. The procedure consists of evaluating the sum of the probabilities associated with the observed table and all possible two-by-two tables that have the same row and column totals as the observed data.

The inverse of the variance-covariance matrix of a set of parameters.

A term used to describe comparisons made within a data set not specifically prescribed before the start of the study.

Refers to the value of the response variable predicted by some estimated model.

A method of summarizing a set of observations by using the minimum value, the lower quartile, the median, upper quartile, and maximum value. Forms the basis of the box-and-whisker plot.

The effects attributable to a finite set of levels of a factor that are of specific interest. For example, the investigator may wish to compare the effects of three particular drugs on a response variable.

A model that contains only factors with fixed effects.

See distribution.

A test for the equality of the variances of two populations having normal distributions, based on the ratio of the variances of a sample of observations taken from each. Commonly used in the analysis of variance, in which testing of whether particular variances are the same also tests for the equality of a set of means.

A quality, trait, or fact that is so related to another as to be dependent upon and to vary with this other.

The relationship between the true values of variables, i.e., the values obtained under the assumption that the variables were measured without error.

A plotting device used in meta-analysis to detect publication bias. The estimate of risk is plotted against sample size. If there is no publication bias, the plot is funnel-shaped. Publication bias, in which studies with significant results are more likely to be published than those with small or no significant effects, removes part of the lower left hand corner of the funnel.

A bell-shaped frequency distribution of infinite range of a random variable. All possible values of the variable are displayed on the horizontal axis. The frequency (probability) of each value is displayed on the vertical axis, producing the graph of the distribution. The properties are as follows: (1) it is a continuous, symmetrical distribution; both tails extend to infinity; (2) the arithmetic mean, mode, and median are identical; and (3) its shape is completely determined by the mean and standard deviation. Another name for normal distribution.

A class of models that arise from a natural generalization of ordinary linear regression. The function of the expected value of the response variable, y, is modeled as a linear combination of the explanatory variables, X 1 , X 2 , . . ., . X q . The other components of such models are a specification of the form of the variance of the response variable and of its probability distribution.

Degree of agreement between an empirically observed distribution and a mathematical or rhetorical distribution.

Measures of the agreement between a set of sample observations and the corresponding values predicted from some model of interest. Examples are chi-square statistic, deviance, and likelihood ratio.

A plot for diagnosing model inadequacy or revealing the presence of outliers, in which the absolute values of, e.g., the residuals from a multiple regression are plotted against the quantiles of the standard normal distribution. Outliers will appear at the top right of the plot as points that are separated from the others, whereas systematic departures from a straight line could indicate that the model is unsatisfactory.

The probability that an individual experiences an event (death, improvement, etc.) in a small time interval, given that the individual has survived up to the beginning of the interval. It is a measure of how likely an individual is to experience an event as a function of the age of the individual. The hazard function may remain constant, increase, or decrease. See also survival function and bathtub curve.

A theoretical measure of the risk of occurrence of an event, e.g., death or a new disease, at a point in time, t , defined mathematically as the limit, as Δ t approaches zero, or of the probability that an individual well at time t will experience the event by t + Δ t , divided by Δ t .

A procedure for modeling the hazard rate that does not depend on the assumptions made in Cox's proportional hazards model, namely, that the loghazard function is an additive function of both time and the vector of covariates.

Nonconstancy of the variance of a measure over the levels of the factors under study.

A graphical representation of a set of observations, in which class frequencies are represented by the areas of rectangles centered on the class interval.

Constancy of the variance of a measure over the levels of the factors under study.

The pathogenic organism responsible for acquired immunodeficiency syndrome (AIDS).

Antigens on cell surfaces that are important for foreign antigen recognition and that play a role in the coordination and activation of the immune response.

The exact probability distribution of the frequencies in a two-by-two contingency table, conditional on the marginal frequencies being fixed at their observed levels. Usually approximated by the binomial distribution.

One of (perhaps) several variables that appear as arguments in a regression equation.

A variable that takes only one of two possible values, with one (usually 1) indicating the presence of a condition and the other (usually 0) indicating the absence of the condition. Used mainly in regression analysis.

Censored observations that occur for reasons related to treatment, e.g., when treatment is withdrawn as a result of a deterioration in the physical condition of a patient.

A term used in the context of Bayesian inference to indicate a prior distribution that reflects empirical or theoretical information regarding the value of an unknown parameter.

The voluntary consent given by a patient to participate in, usually, a clinical trial after being informed of its purpose, method of treatment, procedure for assignment to treatment, benefits and risks associated with participation, and required data collection procedures and schedule.

The first phase in the examination of a data set that consists of a number of informal steps, including checking the quality of the data, calculating simple summary statistics, and constructing appropriate graphs. The general aim is to clarify the structure of the data, obtain a simple descriptive summary, and possibly get ideas for a more sophisticated analysis.

Synonym for hazard function.

A procedure in which all patients randomly allocated to a treatment in a clinical trial are analyzed together as representing that treatment, whether or not they received or completed the prescribed regimen. Failure to follow this step defeats the main purpose of random allocation and can invalidate the results.

The interdependent operation of two or more causes to produce or prevent an effect.

Analysis made before the planned end of a clinical trial, usually with the aim of detecting treatment differences at an early stage and thus preventing as many patients as possible from receiving an “inferior” treatment.

A variable that occurs in a causal pathway from an independent to a dependent variable. It causes variation in the dependent variable and is caused to vary by the independent variable. Its value is altered to block or alter the effect(s) of another factor. Such a variable is statistically associated with both the independent and the dependent variables.

A measure of spread given by the difference between the first and third quartiles of a sample.

A study in which a single group of subjects is measured several times before and after some event or manipulation. Also used to describe investigation of a single subject. See n -of-1 clinical trials.

Observations that often arise in the context of studies of time elapsed to a particular event when subjects are not monitored continuously. Instead, the prior occurrence of the event of interest is detectable only at specific times of observation, e.g., at the time of medical examination.

An investigation involving intentional change in some aspect of the status of the subjects, e.g., introduction of a preventive or therapeutic regimen, to test a hypothesis. Usually it is an experiment such as a randomized clinical trial.

A two-stage procedure in which the samples from the original bootstrap population are themselves bootstrapped. The technique can give confidence intervals of more accurate coverage than simple bootstrapping.

The successive repetition of a mathematical process, using the result of one stage as the input for the next.

A technique for estimating the variance and the bias of an estimator. If the sample size is n , the estimator is applied to each subsample of size n − 1, obtained by dropping a measurement from analysis. The sum of squared differences between each of the resulting estimates and their mean, multiplied by ( n − 1) /n, is the jackknife estimate of variance; the difference between the mean and the original estimate, multiplied by ( n − 1), is the jackknife estimate of bias.

A nonparametric method of compiling life or survival tables. This combines calculated probabilities of survival and estimates to allow censored observations, which are assumed to occur randomly. The intervals are defined as ending each time that an event, (e.g., death or withdrawal) occurs and are therefore unequal.

A chance corrected index of the agreement between, e.g., judgments and diagnoses made by two raters. Calculated as the ratio of the observed excess over chance agreement to the maximum possible excess over chance, the coefficient takes the value unity when there is perfect agreement and the value zero when observed agreement is equal to chance agreement.

Measures of the correlation between two sets of rankings. Kendall's tau statistic is a rank correlation coefficient based on the number of inversions in one ranking compared with the number of inversions in another, e.g., on S , given by S = P − Q, where P is the number of concordant pairs of observations, that is, pairs of observations such that their rankings on the two variables are in the same direction, and Q is the number of discordant pairs for which rankings on the two variables are in the reverse direction.

A distribution-free method that is the analogue of the analysis of variance of a one-way design. It tests whether the groups to be compared have the same population median.

The extent to which the peak of a unimodal probability distribution or frequency distribution departs from the shape of a normal distribution by either being more pointed (leptokurtic) or flatter (platykurtic). For a normal distribution, the value of kurtosis is zero (mesokurtic).

An approach to comparing a set of means that controls the familywise error rate at some particular level, say α. The hypothesis of the equality of the means is tested first by an α-level F test. If this test is not significant, then the procedure terminates without making detailed inferences on pairwise differences; otherwise, each pairwise difference is tested by an α-level Student's t test.

A method used to estimate parameters, particularly in regression analysis, by minimizing the difference between the observed response and the value predicted by the model. Often referred to as “ordinary least squares” to differentiate this simple version of the technique from more involved versions, such as weighted least squares and iteratively weighted least squares.

A procedure for the detection of outliers that uses the difference between the log likelihood of the complete data set and the log likelihood when a particular observation is removed. If the difference is large, then the observation involved is considered an outlier.

A function constructed from a statistical model and a set of observed data that gives the probability of the observed data for various values of the unknown model parameters. The parameter values that maximize the probability are the maximum likelihood estimates of the parameters.

The ratio of the likelihoods of the data under two hypotheses, H 0 and H 1. May be used to assess H 0 against H 1.

An ordinal scale of responses to a question or statement ordered in a hierarchical sequence, such as from “strongly agree” through “no opinion” to “strongly disagree.”

A function of a set of variables, parameters, etc., that does not contain powers or cross-products quantities.

A statistical model in which the expected value of a parameter for a given value of a factor, x , which is assumed to be equal to a + bx, where a and b are constants.

Regression analysis of data using linear models.

A relationship between two variables in which the values of one variable change at a constant rate as the value of the other variable increases.

A method used to test the hypothesis that a genetic marker of known location is on a chromosome different from that on which a gene postulated to govern susceptibility to a disease is located.

A term often used in epidemiology for the logarithm of an odds ratio. Also used in genetics for the logarithm of a likelihood ratio.

The transformation of a variable, x , obtained by taking y = log( x ). Often used when the frequency distribution of the variable, x , shows a moderate to large degree of skewness to achieve normality.

A form of regression analysis used when the response variable is a binary variable.

The logarithm of the ratio of frequencies of two different categorical outcomes, such as healthy versus sick.

The upper and lower ends of the confidence interval for the logarithm of the odds ratio.

A statistical model that uses an analysis of variance type of approach for the modeling of frequency counts in contingency tables.

The probability distribution of a variable, x, for which log ( x − a ) has a normal distribution with mean m and variance σ 2 .

A method for comparing the survival times of two or more groups of subjects that involves the calculation of observed and expected frequencies of failures in separate time intervals.

A concept used in decision analysis that assigns numerical values to making good or poor decisions.

The process applied to the results from bioassays for carcinogenicity conducted with animals at doses that are generally well above human exposure levels to assess risk in humans.

An estimate of the independent effect of (usually) a factor variable on a response variable in an analysis of variance.

A test that compares two groups of ordinal scores and that shows the probability that they form parts of the same distribution. It is a nonparametric equivalent of the t test.

An estimate of the assumed common odds ratio in a series of two-by-two contingency tables arising from different populations, e.g., occupation or country of origin.

A calculated test statistic that uses a standard normal deviate rather than a chi-square value. The test, used to control for confounding, examines the null hypothesis that the variables are independent by looking at just one of the four cells.

A regression test of the odds ratio against a numerical variable representing ordered categories of exposure. It may be used to analyze the results of a case-control study.

A stochastic process such that the conditional probability distribution for the state at any future instant, given the present state, is unaffected by any additional knowledge of the past history of the system. See also random walk.

Procedure intended to keep a participant(s) in a study from knowing some fact(s) or observation(s) that might bias or influence that participant's actions or decisions regarding the study. See also blinding.

The process of making a study group and a comparison group comparable with respect to extraneous factors. Often used when selecting cases and controls in retrospective studies to control variation in a response variable due to sources other than those immediately under investigation.

The value for an unknown parameter that maximizes the probability of obtaining exactly the data that were observed.

The highest possible dose of a drug that can be given with acceptable toxicity to the patient. This dose is usually determined in a phase I clinical trial and is the dose recommended for use in future studies.

A form of the chi-square test for matched-pairs data. It is a special case of the Mantel-Haenszel test.

The expected value of the square of the difference between an estimator and the true value of a parameter. If the estimator is unbiased, then the mean squared error is simply the variance of the estimator. For a biased estimator the mean squared error is equal to the sum of the variance and the square of the bias.

The ratio of two mean squares in analysis of variance.

The name used in the context of analysis of variance for estimators of particular variances of interest. For example, in the analysis of a one-way design, the within-groups mean square estimates the assumed common variance in k groups.

Systematic error arising from inaccurate measurements (or classification) of a study variable(s) for subjects.

Errors in reading, calculating, or recording a numerical value. The difference between the observed values of a variable recorded under similar conditions and some fixed true value.

The range of possible values for a measurement, e.g. the set of possible responses to a question.

Numerical indices quantifying the strength of the statistical dependence of two or more qualitative variables.

A measure of central tendency. It is the value in a set of ranked observations that divides the data into two parts of equal size. When there is an odd number of observations, the median is the middle value. When there is an even number of observations, the median is calculated as the average of the two central values.

The process of using statistical methods to combine the results of two or more independent studies to yield an overall answer to a question of interest. The rationale behind this approach is to provide a test with more power than that provided by the separate studies themselves.

A method for allocation of patients to treatments in clinical trials that is usually an acceptable alternative to random allocation. The procedure ensures balance between the groups to be compared on prognostic variables, by allocating with a high degree of probability the next patient to enter the trial to whatever treatment would minimize the overall imbalance between the groups on the prognostic variables, at that stage of the trial.

A method of estimation that finds estimates of the parameters of some model of interest by minimizing the chi-squared statistic for the assessment of differences between the observed values and those predicted by the model.

Observations missing from a set of data. These occur for a variety of reasons, e.g., subjects drop out of the study, subjects do not appear for one or other of the scheduled visits, or there is an equipment failure. Otherwise known as “missing completely at random.”

A model usually encountered in the analysis of longitudinal data in which some of the parameters are considered to have fixed effects and some are considered to have random effects. For example, in a clinical trial with two treatment groups in which the response variable is recorded for each subject at a number of visits, the treatments would usually be regarded as having fixed effects and the subjects would usually be regarded as having random efffects.

One of the measures of central tendency. It is the most frequently occurring value in a set of observations.

Method for finding solutions to mathematical and statistical problems by simulation.

A clinical trial conducted simultaneously in a number of participating hospitals or clinics, with all centers following a universal study protocol and with independent random allocation within each center.

In multiple regression analysis, a situation in which at least some of the independent variables are highly correlated directly or indirectly with each other. Such a situation can result in inaccurate estimates of the parameters in the regression model.

Method of analysis that explains individual outcomes in terms of both individual and environmental or aggregate variables.

A probability distribution or frequency distribution with several modes. Multimodality is often taken as an indication that the observed distribution results from the mixing of the distributions of relatively distinct groups of observations.

The probability distribution associated with the classification of each of a sample of individuals into one of several mutually exclusive and exhaustive categories. When the number of categories is two, the distribution is called binomial.

Procedures for detailed simultaneous examination of the differences between a set of means, usually after a general hypothesis that they are all equal has been rejected. Examples are Bonferroni correction, Duncan's multiple-range test, Dunnett's test, and Tukey's method. No single technique is best in all situations, and a major distinction between techniques is how they control the possible inflation of the Type I error.

The correlation between the observed values of the dependent variable in a multiple regression and the values predicted by the estimated regression equation. Often used as an indicator of how useful the explanatory variables are in predicting the response.

A term used to describe the variety of outcome measures used in many clinical trials. There are a number of ways to measure treatment success, e.g, length of patient survival, percentage of patients experiencing tumor regression, or percentage of patients surviving for 2 years. The aim in using a variety of such measures is to gain better knowledge of the differences between the treatments being compared.

A statistical model in which a continuous response variable, y, is regressed on a number of explanatory variables, X 1 , X 2 , . . ., X q . The model is E ( y ) = β 0 + β 1 X 1 + . . . + β q X q where E denotes the expected value. The parameters in the model, the regression coefficients β 0 , β 1 , β q , are generally estimated by least squares estimation. Each coefficient gives the change in the response variable corresponding to a unit change in the appropriate explanatory variable, conditional on the other variables remaining constant.

For events A and B that are independent, the probability that both occur is the product of the separate probabilities, i.e., P ( A and B ) = P ( A ) P ( B ), where P denotes probability.

A model in which the combined effect of a number of factors, when applied together, is the product of their separate effects.

An analytical method that allows the simultaneous study of two or more dependent variables.

A procedure for testing the equality of the mean vectors of more than two populations. The technique is analogous to the analysis of variance of univariate data, except that the groups are compared on q response variables simultaneously. In the univariate case, F tests are used to assess the hypotheses of interest. In the multivariate case, no single test statistic that is optimal in all situations can be constructed.

Data for which each observation consists of values for more than one random variable, e.g., measurements of blood pressure, temperature, and heart rate for a number of subjects.

The simultaneous probability distribution of a set of random variables.

A method for assessing the effect of explanatory variables on a set of two or more correlated binary response variables.

The probability that a person having a negative result or a diagnostic test does not have the disease.

A multiple-comparison test used to investigate in more detail the differences existing between a set of means, as indicated by a significant F test in an analysis of variance.

A variation of a randomized controlled trial in which a sequence of alternative treatment regimens is randomly allocated to a single patient. The outcomes of successive regimens are compared, with the aim being determination of the optimum regimen for the patient.

A variable that gives the appropriate label of an observation after allocation to one of several possible categories, for example, gender (male or female), marital status (married, single, or divorced), or blood group (A, B, AB, or O).

A line chart showing scales for the variables involved in a particular formula in such a way that corresponding values for each variable lie on a straight line that intersects all the scales.

A trial in which a series of consecutive patients receive a new treatment and those who respond (according to some predefined criterion) continue to receive it. Patients who fail to respond receive an alternative treatment. The two groups are then compared on one or more outcome variables.

A term used for failure to provide the relevant information being collected in a survey for a variety of reasons. A large number of nonrespondents may introduce bias into the final results.

The dose level of a compound below which there is no evidence of an effect on the response of interest.

A normal distribution with mean np and variance np (1 − p ) that acts as an approximation to a binomial distribution as n , the number of trials, increases. The term p represents the probability of a “success” of any trial.

A probability distribution of a random variable, x , that is assumed by many statistical methods. The properties of a normal distribution are as follows: (1) it is a continuous, symmetrical distribution; both tails extend to infinity; (2) the arithmetic mean, mode, and median are identical; and (3) its shape is determined by the mean and standard deviation. Synonym for Gaussian distribution.

The probability distribution of a test statistic when the null hypothesis is true.

The statistical hypothesis that one variable has no association with another variable or set of variables or that two or more population distributions do not differ from one another.

In clinical treatment regimens, the number of patients with a specified condition who must follow the specified regimen for a prescribed period to prevent the occurrence of a specified complication(s) or an adverse outcome(s) of the condition.

Tests that assess the differences between treatment groups and that take account of the possible heterogeneous nature of the response treatment. They may lead to the identification of subgroups of patients for whom the experimental therapy might have the most or the least benefit.

The ratio of the probability of the occurrence of an event to that of the nonoccurrence of the event.

The ratio of the odds for a binary variable in two groups of subjects. For example, if the two possible states of the variable are labeled “success” and “failure,” then the odds ratio is a measure of the odds of a success in one group relative to that in the other.

A form of matching often used when control subjects are more readily obtained than cases. A number, m (m > 1), of controls are attached to each case, with these being known as the matched set. The theoretical efficiency of such matching in estimating, e.g., relative risk, is m/(m+1), so one control per case is 50 percent efficient, whereas four controls per case is 80 percent efficient. Increasing the number of controls beyond 5 to 10 brings rapidly diminishing returns.

A statistical significance test based on the assumption that the data have only one possible direction of variability. The choice between a one-sided test and a two-sided test must be made before any test statistic is calculated.

See analysis of variance.

A measurement that allows a sample of individuals to be ranked with respect to some characteristic but for which differences at different points of the scale are not necessarily equivalent. For example, anxiety might be rated on a scale of “none,” “ mild, ” “moderate,” and “severe,” with the values 0, 1, 2, and 3 respectively, being used to label the categories.

All the possible results that may stem from exposure to a causal factor or from preventive or therapeutic interventions; all identified changes in health status arising as a consequence of the handling of a health problem.

Observations that differ so widely from the rest of the data as to lead one to suspect that a gross error may have been committed in measurement or recording.

A situation that may arise when the matching procedure partially or completely obscures evidence of a true causal association between the independent and dependent variables. The matching variable may be an intermediate cause in the causal chain, or it may be strongly affected by or a consequence of such an intermediate cause.

A design that can reduce selection bias in situations in which it is not possible to use random allocation of subjects to treatments. In the experimental groups, the new treatment is made available to all subjects, although some may not receive it. In the control groups, the experimental treatment is generally not available to subjects, although some subjects may receive it in special circumstances.

In a clinical trial, two samples of observations with the characteristic feature that each observation in one sample has one and only one matching observation in the other sample. One member of each pair receives the experimental regimen, and the other member of each pair receives a suitably designated control regimen.

A simple experimental setup in which two different groups of patients, e.g., treated and untreated patients, are studied concurrently.

One of the assumptions made in the analysis of covariance, namely, that the slope of the regression line relating the response variable to the covariate is the same in all treatment groups.

A hypothesis concerning the parameter(s) of a distribution, e.g., the hypothesis that the mean for a population equals the mean for a second population when the populations are each assumed to have a normal distribution.

Procedures for testing hypotheses about parameters in a population described by a specified distributional form, often a normal distribution. Student's t test is an example of such a method.

The correlation between a pair of variables after adjusting for the effect of a third variable.

An index for examining the linear relationship between a response variable and a group of explanatory variables while controlling for another group of variables.

A mode of analysis involving assumptions about the direction of causal relationships between linked sequences and configurations of variables. This allows the analyst to construct and test the appropriateness of alternative models (in the form of a path diagram) of the causal relations that may exist within the array of variables.

See correlation coefficient.

A measurement combining persons and time, used as denominator in person-time incidence and mortality rates. It is the sum of individual units of time that the persons in the study population have been exposed to the conditions of interest. The most frequently used person-time is person-years.

See person-time.

A phenomenon in which patients given only inert substances often show subsequent clinical improvement compared with patients who received the actual treatment.

A term for those patients in a clinical trial who report side effects normally associated with the active treatment while receiving a placebo.

A procedure in clinical trials in which the response to treatment is either positive (a success) or negative (a failure). One of the two treatments is selected at random and used on the first patient; thereafter, the same treatment is used on the next patient whenever the response of the previously treated patient is positive and the other treatment is used whenever the response is negative.

See estimate.

A distribution function used to describe the occurrence of rare events or to describe the sampling distribution of isolated counts in a continuum of time or space. This distribution is used to model person-time incidence rates.

A linear model in which powers and possibly cross-products of explanatory variables are included, e.g., y = β 0 + β 1 x + β 2 x 2 .

The probability that a person having a positive result on a diagnostic test actually has a particular disease.

The probability of rejecting the null hypothesis when it is false. Power gives a method of discriminating between competing tests of the same hypothesis, with the test with the higher power being preferred. It is also the basis of procedures for estimating the sample size needed to detect an effect of a particular magnitude.

A term applied to the likely spread of estimates of a parameter in a statistical model. Measured by the standard error of the estimator, which can be decreased, and hence precision is increased, by using a larger sample size.

The variables that appear on the right side of the equation defining, e.g., multiple regression or logistic regression, and that aim to predict or explain the response variable.

Probability distribution that summarizes information about a random variable or parameter known or assumed at a given time point before further information about empirical data is obtained. It is used in the context of Bayesian inference.

For a discrete random variable, a mathematical formula that gives the probability of each value of the variable. Examples are binomial distribution and Poisson distribution. For a continuous random variable, a curve described by a mathematical formula that specifies, by way of areas under the curve, the probability that the variable falls within a particular interval. Examples are normal distribution and exponential distribution.

A sample obtained by a method in which every individual in a finite population has a known, but not necessarily equal, chance of being included in the sample.

The probability of the observed data (or data showing a more extreme departure from the null hypothesis) when the null hypothesis is true.

A technique most commonly used in bioassays, particularly toxilogical experiments in which sets of animals are subject to known levels of a toxin, and a model is required to relate the proportions surviving at a particular dose to the dose. In this type of analysis the probit transformation of a proportion is modeled as a linear function of the dose or, more commonly, the logarithm of the dose. Estimates of the parameters in the models are found by maximum likelihood estimation.

A transformation used in the analysis of dose-response curve.

See Cox's proportional hazards model.

A model for investigating the dependence of an ordinal variable on a set of explanatory variables. In the most commonly used version of the model, the cumulative probabilities, P ( y ≤ k ), where y is the response variable with categories 1 ≤ 2 ≤ 3 ... ≤ c , are modeled as linear functions of the explanatory variables via the logistic transformation. The name proportional odds arises since the odds ratio of having a score of k or less for two different sets of values of the explanatory variables does not depend on k.

The proportion of cases of disease prevented by the vaccine, usually estimated as PE = (ARU − ARV)/ ARU, where ARV and ARU are the attack rates of the disease under study among the vaccinated and unvaccinated cohorts, respectively. For example, if the rate of disease is 100 per 10,000 in an unvaccinated group but only 30 per 10,000 in a comparable vaccinated group, the PE is 70 percent.

A formal document outlining the proposed procedures for carrying out a clinical trial. The main features of the document are study objectives, patient selection criteria, treatment schedules, methods of patient evaluation, trial design, procedures for dealing with protocol violations, and plans for statistical analysis.

Deliberate or accidental failure of patients to follow one or other aspects of a protocol for a clinical trial. For example, the patients may not have taken their prescribed medication. Such patients are said to show noncompliance.

A sampling procedure used with spatial data in which sample areas (the quadrants) are taken and the number of objects or events of interest occurring in each is recorded.

Divisions of a probability distribution or frequency distribution into equal, ordered subgroups, e.g., quartiles or percentiles.

A three-parameter nonlinear logistic regression model.

The values that divide a frequency distribution or probability distribution into four equal parts.

A function that is used as the basis for the estimation of parameters when it is not possible (or desirable) to make a particular distributional assumption about the observations, with the consequence that it is not possible to write down their likelihood. The function depends on the assumed relationship between the mean and the variance of the observations.

The set of four variate values that divide a frequency distribution or a probability distribution into five equal parts.

A sample in which the units are not selected completely at random, but are selected in terms of a certain number of units in each of a number of categories, e.g., 10 men over age 40 or 25 women between ages 30 and 35.

A diagram used to display the odds ratios calculated from a number of different clinical trials of the same treatment(s). The diagram consists of a plot of y = Δ ̂ / SE ( Δ ̂ ) against x = 1/ SE ( Δ ̂ ), where Δ ̂ is the logarithm of the odds ratio from a particular study and SE is standard error. Often useful in meta-analysis.

Allocation of individuals to groups, e.g., for experimental and control regimens, by chance. It follows a predetermined plan that is usually devised with the aid of a table of random numbers. The control and experimental groups should be similar at the start of the investigation, and the investigator's personal judgment and prejudices should not influence allocation.

The effects attributable to an infinite set of levels of a factor, only a randomsample of which occurs in the data.

Procedures for determining statistical significance directly from data, without recourse to some particular sampling distribution. The data are divided repeatedly between treatments, and for each division the relevant test statistic e.g., t or F is calculated to determine the proportion of the data permutations that provide as large a test statistic as that associated with the observed data. If that proportion is smaller than some significance level ?, the results are significant at the ? level.

A clinical trial that involves the formation of treatment groups by the process of random allocation.

A design originally introduced to overcome some of the perceived ethical problems facing clinicians entering patients in randomized clinical trials. After the patient's eligibility is established, the patient is randomized to one of two treatments, treatments A and B. The risks, benefits, and treatment options are discussed with patients randomized to receive treatment A, and the patients are asked if they are willing to receive the therapy. Those who do not agree receive treatment B or some alternative treatment. The same procedure is followed for patients who were randomized to receive treatment B.

Either a set of n independent and identically distributed random variables or a sample of n individuals selected from a population in such a way that each sample of the same size is equally likely.

A variable, the values of which occur according to some specified probability distribution.

The variation in a data set unexplained by identifiable sources.

The path traversed by a particle that moves in steps, with each step being determined by chance in regard to direction or magnitude, or both. Random walk may be applied to sequential sampling.

The difference between the largest and the smallest observations in a data set.

The range of differences between two treatments being compared in a clinical trial within which it is not possible to make a definite choice of treatment.

Correlation coefficients that depend only on the ranks of the variables, not on their observed values. Examples are Kendall's tau statistics and Spearman's rho correlation coefficient.

Statistics based only on the rank of the sample observations, e.g., Kendall's tau statistics.

The value obtained by dividing one quantity by another: a general term of which rate, proportion, percentage, etc., are subsets. It is an expression of the relationship between a numerator and a denominator in which the two are usually separate and distinct quantities, with neither being included in the other.

A plot of the sensitivity ( y axis) of a diagnostic test against the complement of its specificity ( x axis) that ascertains the balance between specificity and sensitivity corresponding to various cutoffs.

A general term for methods of analysis that are concerned with estimating the parameters in some postulated relationship between a response variable and one or more explanatory variables. Examples are linear regression, logistic regression, and multiple regression.

See multiple regression.

Procedures designed to investigate the assumptions underlying a regression analysis (e.g., normality or homogeneity of variance) or to examine the influence of particular datum points or small groups of datum points on the estimated regression coefficients.

Diagrammatic presentation of a regression equation, usually drawn with the independent variable, x , as the abscissa and the dependent variable, y , as ordinate.

The ratio of the observed survival for a given group of patients to the survival that group would have experienced on the basis of the life table for the population for which the diagnosis was made.

The degree to which the results obtained by a measurement procedure can be replicated.

The closeness of results obtained on the same test material under changes of reagents, conditions, techniques, apparatus, laboratories, and so on.

The difference between the observed value of a response variable ( yi ) and the value predicted by some model of interest ( yi ). Examination of a set of residuals, usually by informal graphical techniques, allows the assumptions made in the model-fitting exercise (e.g., normality and homogeneity of variance) to be checked.

Potential confounding by factors or variables not yet considered in the analysis, which may be directly observable or not.

The systematic component of the difference between information provided by survey respondent and the “truth.”

The number of completed or returned survey instruments (questionnaires, interviews, etc.) divided by the total number of persons who would have been surveyed.

The variable of primary importance in medical investigations, since the major objective is usually to study the effects of a treatment or other explanatory variables on this variable.

A method of estimation in which estimators of parameters are derived by maximizing the restricted likelihood rather than the likelihood itself.

The estimate of the proportion of subjects misclassified by a rule derived from a discriminant analysis, obtained by reclassifying the training set by using the rule.

A method of regression analysis designed to overcome the possible problem of multicollinearity among the explanatory variables. Such multicollinearity makes it difficult to estimate the separate effects of variables on the response. This form of regression may result in increased precision.

A method of analysis for ordinal variables that proceeds from the assumption that the ordered categorical scale is an approximation to an underlying, but not directly measurable, continuous variable. Numerical values called ridits are calculated for each category. These values are estimates of the probability that a subject's value on the underlying variable is less than or equal to the midpoint of the corresponding interval.

The qualitative or quantitative estimation of the likelihood of adverse effects that may result from exposure to specified health hazards or from the absence of beneficial influences.

Methods of estimation that work well not only under ideal conditions but also under conditions representing a departure from an assumed distribution or model.

A general class of statistical procedures designed to reduce the sensitivity of the parameter estimates to failures in the assumption of the model. For example, least squares estimation is known to be sensitive to outliers, but the impact of such observations can be reduced by basing the estimation process not on a sum-of-squares criterion but on a sum-of-absolute values criterion.

Statistical procedures and tests that work well even when the assumptions on which they are based are moderately violated. An example is Student's t test.

A method based on the Poisson distribution which states that if in n trials zero events of interest are observed, a 95 percent confidence (with limits of 0 and 3) bound on the underlying rate is 3/ n.

A period of observation before the formation of treatment groups by random allocation, during which subjects acquire experience with the major components of a study protocol. Those subjects who experience difficulty complying with the protocol are excluded, whereas the group of proven compliers is randomized into the trial.

In a series of observations, the occurrence of an uninterrupted sequence of the same value. For example, in the series 1111222433333 there are four “runs”, with the single value, 4, being regarded as a run of length unity.

A test frequently used to detect serial correlations. The test consists of counting the number of runs or sequences of positive and negative residuals and comparing the result with the expected value under the null hypothesis of independence.

The process of deciding, before a study begins, how many subjects should be studied. It takes into account the incidence or prevalence of the condition being studied, the estimated or putative relationship among the variables in the study, the power that is desired, and the allowable Type I error.

The difference between the sample result and the population characteristic being estimated. In practice, the sampling error can rarely be determined because the population characteristic is not usually known. With appropriate sampling procedures, it can be kept small and the investigator can determine its probable limits of magnitude.

The variation shown by different samples of the same size from the same population.

Zero frequencies that occur in the cells of contingency tables because of inadequate sample size.

A model that contains all main effects and all possible interactions between factors. Such a model contains the same number of parameters as observations and results in a perfect fit for a data set.

A graphic method of displaying the distribution of two variables in relation to each other.

The bias that may be introduced into clinical trials and other types of medical investigations whenever a treatment is chosen by the individual involved or is subject to constraints that go unobserved by the researcher.

Half the difference between the upper and lower quartiles.

An index of the performance of a diagnostic test, calculated as the percentage of individuals with a disease who are correctly classified as having the disease, i.e., the conditional probability of having a positive test result given that the disease is present.

Administration of antigen to induce a primary immune response.

A method of analysis in which a statistical test of significance is conducted repeatedly over time as the data are collected. After each observation, the cumulative data are analyzed and one of the following three decisions is taken: stop the data collection, reject the null hypothesis, and claim statistical significance; stop the data collection, do not reject the null hypothesis, and state that the results are not statistically significant; continue the data collection since the accumulated data are inadequate to draw a conclusion. Three types of sequential analysis are: open-ended sequential analysis, used in studies that continue indefinitely until sufficient evidence to reject or fail to reject the null hypothesis has accumulated; closed-ended sequential analysis, in which the maximum size of the sample has been set and as data are accumulated and analyzed there is an option to terminate the study before data from the planned sample size have accumulated; and group sequential analysis, in which interim analysis is undertaken at planned numbers of intervals, with each interval having accumulated data for a specified number of samples.

A term in regression analysis that refers to the contribution of variables as they are added to the model in a particular sequence. It is the difference in the residual sum of squares before and after adding a variable.

A hereditary, genetically determined hemolytic anemia, one of the hemoglobinopathies, occurring almost exclusively in African Americans, characterized by arthralgia, acute attacks of abdominal pain, ulcerations of the lower extremities, and sickle-shaped erythrocytes in the blood.

The level of probability at which it is agreed that the null hypothesis will be rejected, conventionally set at 0.05.

A statistical procedure that, when applied to a set of observations, results in a p value relative to some hypothesis. Examples include Student's t test, z test, and Wilcoxon's signed rank test.

A test that can be used when combining results of several studies, e.g., in meta-analysis. The test considers the direction of results of individual studies, whether the associations demonstrated are positive or negative.

Coefficients that range from zero to unity and that are used to measure the similarity of the variable values of two observations from a set of multivariate data. Most commonly used on binary variables.

A form of confounding in which the presence of a confounding variable changes the direction of an association. It may occur in meta-analysis because the sum of the data or results from a number of different studies may be affected by confounding variables that have been excluded by design features from some studies but not others.

Censored observations that occur in clinical trials in which all the patients enter the study at the same time point and in which the study is terminated after a fixed time period.

The lack of symmetry in a probability distribution.

A collection of measurements or observations on one or more variables taken at specified locations and for which the spatial organization of the data is of primary interest.

An index of the performance of a diagnostic test, calculated as the percentage of individuals without the disease who are classified as not having the disease, i.e., the conditional probability of a negative test result given that the disease is absent.

The most commonly used measure of the spread of a set of observations. Equal to the square root of the variance.

A set of techniques used to remove as much as possible the effects of differences in age or other confounding variables when comparing two or more populations. The common method uses weighted averaging of rates specific for age, sex, or some potential confounding variable(s) according to some specified distribution of these variables.

A normal distribution with zero mean and unit variance.

A random variable having a standard normal distribution.

Variable values transformed to zero mean and unit variance.

A numerical characteristic of a sample, e.g., sample mean and sample variance.

An estimate of the probability of the observed or greater degree of association between independent and dependent variables under the null hypothesis. The level of statistical significance is usually stated by the p value.

A procedure that is intended to decide whether a hypothesis about the distribution of one or more populations or variables should be rejected or accepted.

A method of displaying data resembling a histogram in which each observation is split into two parts, with multiples of 10 along the “stem” and the integers forming the “leaves.” The stems are arranged in a column, and the leaves are attached to the relevant stem.

A process that incorporates some element of randomness, in a series of random variables, xt, where t assumes values in a certain range T . In most cases xt is an observation at time t and T is a time range.

Procedures that allow interim or sequential analyses in clinical trials at predefined times and that specify the conditions or criteria under which the trial shall be terminated while preserving the Type I error at some prespecified level.

A method for comparing the survival experiences of two groups of subjects given different treatments when the groups are stratified by age or some other prognostic variable.

A randomization procedure in clinical trials in which strata are identified and subjects are randomly allocated to treatments within each stratum without sacrificing the advantages of random allocation.

Zero frequencies occurring in the cells of contingency tables that arise because it is theoretically impossible for an observation to fall in the cell.

The probability distribution of the ratio of a standard normal variable to the square root of a variable with a chi-square distribution. The shape of the distribution varies with n, and as n gets larger the shape of the t distribution approaches that of the standard normal distribution.

Significance tests for assessing hypotheses about population means. One version, known as single-sample t test, is used in situations in which it is required to test whether the mean for a population takes a particular value. Another version, known as independent-samples t test, is applied when independent samples are available from each population and is designed to test the equality of the means for the two populations.

The analysis of particular subgroups of patients in a clinical trial to assess possible treatment-subgroup interactions. Analysis of many subgroups for treatment effects can increase overall Type I error rates.

End points in clinical trials that can be measured only by subjective clinical rating scales.

In clinical trials it refers to an outcome measure that an investigator considers to be highly correlated with an endpoint of interest but that can be measured at lower expense or at an earlier time. In some cases, ethical issues may suggest the use of a surrogate endpoint.

The probability that the survival time of an individual is longer than some particular value. A plot of this probability against time is called a survival curve and is a useful component in the analysis of such data.

A probability distribution or frequency distribution that is symmetrical about some central value.

Procedures for allocating treatments to patients in a clinical trial that attempts to emulate random allocation by using some systematic scheme, such as giving treatment A to those people with birth dates on even dates and treatment B to those with birth dates on odd days.

A term often used in a clinical laboratory to describe the difference in results caused by a bias of an assay.

The collection of individuals, items, measurements, etc., about which it is required to make inferences. At times it is used to indicate the population from which a sample is drawn, and at times it is used to denote any reference population about which inferences are required.

The distribution of a quotient of independent random variables, the numerator of which is a standardized normal variate and the denominator of which is the positive square root of the quotient of a chi-square-distributed variate and its number of degrees of freedom.

A statistic used to assess a particular hypothesis in relation to some population. The essential requirement of such a statistic is a known distribution when the null hypothesis is true.

A term usually applied to ordinal variables to indicate observations that take the same value on a variable.

Covariates whose values change over time. Examples are age and weight.

Covariates whose values remain constant over time. An example is a pretreatment measurement of some characteristic.

A measure traditionally used to compare treatments in bioequivalence trials. It is the time at which a patient's highest recorded values occur.

The sum of the squared deviations of all the observations from their mean.

A simple rule for approximating the integral of a function, f ( x ), between two limits.

The ratio of the number of subjects allocated to the two treatments in a clinical trail. Equal allocation is most common in practice, but it may be advisable to allocate patients randomly in other ratios when a new treatment is compared with an old one, or when one treatment is much more difficult or expensive to administer.

An instance in which a patient assigned to receive a particular treatment in a clinical trial is exposed to one of the other treatments during the course of the trial.

Analyzing the results of a clinical trial by the treatment received by a patient rather than by the treatment allocated at randomization as in intent-to-treat analysis.

Synonym for clinical trial.

Movement in one direction of the values of a variable over a period of time.

A study in which the subjects, observers, and analysts are blinded as to which subjects received what interventions.

Data for which sample values larger (truncated on the right) or smaller (truncated on the left) than a fixed value are either not recorded or not observed.

Test that uses a statistic that, under the null hypothesis, has the t distribution to test whether two means differ significantly or to test linear regression or correlation coefficients.

The daily dose of a compound required to halve the probability of remaining tumorless at the end of a standardized lifetime.

An allocation procedure for forming treatment groups in a clinical trial in which the probability of assigning a patient to a particular treatment is a function of the observed differences in outcomes for patients already enrolled in the trial.

A contingency table with two rows and two columns formed from cross classification of two binary variables.

A sampling scheme involving two distinct phases: first, information about particular variables of interest is collected for all members of the sample, and second, information about other variables is collected for a subsample of the individuals in the original sample.

A procedure most often used in the assessment of quality assurance before, during, and after the manufacture of, e.g., a drug product. This would involve randomly sampling a number of packages of some drug and then sampling a number of tablets from each of these packages.

A procedure sometimes used in clinical trials in which results are first examined after only a fraction of the planned number of subjects in each group have completed the trial. The relevant test statistic is calculated and the trial is stopped if the difference between the treatments is significant at stage 1 level. Otherwise, additional subjects in each treatment group are recruited, the test statistic is calculated again, and the groups are compared at stage 2 level α 2 , where α and α 2 are chosen to give an overall significance level of α.

A statistical significance test based on the assumption that the data are distributed in both directions from some central value(s).

The error that results when the null hypothesis is falsely rejected.

The error that results when the null hypothesis is falsely accepted.

A requirement that all of a number of diagnostic tests yield positive results before declaring that a patient has a particular complaint.

An estimator that for all sample sizes has an expected value equal to the parameter being estimated. If an estimator tends to be unbiased as the sample size increases, it is referred to as “asymptotically unbiased.”

The probability distribution of a random variable having constant probability over an interval. The most commonly encountered uniform distribution is one in which the parameters α and β take the values 0 and 1, respectively.

A probability distribution or frequency distribution having only a single mode.

Synonym for standard normal variable.

Data involving a single measurement for each subject or patient.

An approach to the analysis of two-way and higher-order factorial designs when there are an unequal number of observations in each cell. The analysis is based on cell means, using the harmonic mean of all cell frequencies as the sample size for all cells.

A probability distribution or frequency distribution shaped more or less like a letter U, although not necessarily symmetrical. The distribution has its greatest frequencies at the two extremes of the range of the variable.

In economics, utility means preference for or desirability of a particular outcome.

A method in clinical decision analysis in which the outcome refers to being or becoming healthy rather than sick or disabled.

A term used for the prior distribution in Bayesian inference in the situation in which there is complete ignorance about the value of a parameter.

The extent to which a measuring instrument is measuring what was intended.

A part of data editing in which one checks that only allowable values or codes are given for the answers to questions asked of subjects.

An expression of the degree to which a measurement measures what it intends to measure.

The degree to which the inference drawn from a study, especially generalizations extending beyond the study sample, are warranted after taking into account the study methods, the representativeness of the study sample, and the nature of the population from which it is drawn.

Any attribute, phenomenon, or event that can have different values from time to time.

A variable that causally precedes the association of the outcome under study.

See confounding.

Independent variable other than the “hypothetical causal variable” that has a potential effect on the dependent variable and that is subject to control by analysis.

A (potentially) confounding variable that has not been brought under control by design or analysis.

A measure of the variation shown by a set of observations, defined by the sum of squares of the deviation from the mean divided by the number of degrees of freedom in the set of observations. In a population, the second moment about the mean.

Variances of random-effect terms in linear models. For example, in a simple mixed model for longitudinal data, both subject effects and error terms are random, and estimation of their variances is of some importance. In the case of a balanced design, estimation of these variances is usually achieved directly from the appropriate analysis of variance table by equating mean squares to their expected values. When the data are unbalanced, a variety of estimation methods might be used, although maximum likelihood estimation and restricted maximum likelihood estimation are most often used.

A symmetric matrix in which the off-diagonal elements are the covariances (sample or population) of pairs of variables and the elements on the main diagonal are the variances (sample or population) of the variables.

An indicator of the effect that the other explanatory variables have on the variance of a regression coefficient of a particular variable, given by the reciprocal of the square of the multiple correlation coefficient of the variable with the remaining variables.

Synonym for F distribution.

Synonym for F test.

Transformation designed so that the variance of the transformed variable is independent of parameters.

A matrix having only one row or column.

A graphical representation of the extent to which two or more quantities or concepts are mutually inclusive and mutually exclusive.

The exposure level to some toxic agent corresponding to an acceptably small risk of suffering an ill effect. From a regulatory perspective, this typically means an increased risk of no more than 10 6 or 10 4 above the background.

A possible source of bias in clinical trials involving volunteers, but not involving random allocation, because of the known propensity of volunteers to respond better to treatment than other patients.

A test for the hypothesis that a vector of parameters, θ' = [θ 1 , θ 2 , . . . , θ m ], is the null vector. The test statistic is, W = θ ̂ 'V − 1 θ ̂ where θ ̂ ' contains the estimated parameter values and V is the asymptotic variance-covariance matrix of θ ̂ . Under the hypothesis, W has an asymptotic chi-square distribution with degrees of freedom equal to the number of parameters.

Dose-response model of the form P ( d ) = 1 − exp(− b d m ), where P ( d ) is the probability of response due to a continuous dose rate d ; and b and m are constants. The model is useful for extrapolating from high- to low-dose exposures, e.g., from animals to human.

A value determined by assigning weights to individual measurements. Each value is assigned a nonnegative coefficient (weight); the sum of the products of each value by its weight divided by the sum of the weights is the weighted average.

A version of the kappa coefficient that allows disagreements between raters to be differentially weighted to allow differences in how serious such disagreements are judged to be.

A method of estimation in which estimates arise from minimizing a weighted sum of squares of the differences between the response variable and its predicted value in terms of the model of interest. Often used when the variance of the response variable is thought to change over the range of values of the explanatory variable(s), in which case the weights are generally taken as the reciprocals of the variance.

Tests designed to ensure that manufacturers control the variation in the weights of the tablet forms of the drugs that they produce.

Another name for the Mann-Whitney test.

A distribution-free method for testing the difference between two populations by using matched samples. The test is based on the absolute differences of the pairs of observations in the two samples ranked according to size, with each rank being given the sign of the original difference.

A test for detecting outliers in multivariate data that assumes that the data arise from a multivariate normal distribution.

A test used to answer questions about the toxicities of substances and at what dose level any toxicity occurs. The test assumes that the mean response of the variate is a monotonic function of dose.

An adjustment proposed by Yates in the chi-square calculation for a two-by-two contingency table that subtracts 0.5 from the positive discrepancies (observed – expected) and adding 0.5 to the negative discrepancies before these values are squared in the calculation of the usual chi-square statistic. This brings the distribution based on the discontinuous frequencies closer to the continuous chi-square distribution from which the published tables for testing chi-square values are derived.

A modified double-blind randomized controlled trial design for the formation of treatment groups in a clinical trial. The essential feature is randomization before informed consent procedures, which is claimed to be needed only for the group allocated to receive the experimental regimen.

A test for assessing hypotheses about population means when their variances are known. If the null hypothesis is true, z has a standard normal distribution.

• Cite this Page Institute of Medicine (US) Committee on Strategies for Small-Number-Participant Clinical Research Trials; Evans CH Jr., Ildstad ST, editors. Small Clinical Trials: Issues and Challenges. Washington (DC): National Academies Press (US); 2001. Appendix B, Glossary of Statistical and Clinical Trials Terms.
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Research Types Explained: Basic, Clinical, Translational

“Research” is a broad stroke of a word, the verbal equivalent of painting a wall instead of a masterpiece. There are important distinctions among the three principal types of medical research — basic, clinical and translational.

Whereas basic research is looking at questions related to how nature works, translational research aims to take what’s learned in basic research and apply that in the development of solutions to medical problems. Clinical research, then, takes those solutions and studies them in clinical trials. Together, they form a continuous research loop that transforms ideas into action in the form of new treatments and tests, and advances cutting-edge developments from the lab bench to the patient’s bedside and back again.

Basic Research

When it comes to science, the “basic” in basic research describes something that’s an essential starting point. “If you think of it in terms of construction, you can’t put up a beautiful, elegant house without first putting in a foundation,” says David Frank, MD , Associate Professor of Medicine, Medical Oncology, at Dana-Farber Cancer Institute. “In science, if you don’t first understand the basic research, then you can’t move on to advanced applications.”

Basic medical research is usually conducted by scientists with a PhD in such fields as biology and chemistry, among many others. They study the core building blocks of life — DNA, cells, proteins, molecules, etc. — to answer fundamental questions about their structures and how they work.

For example, oncologists now know that mutations in DNA enable the unchecked growth of cells in cancer. A scientist conducting basic research might ask: How does DNA work in a healthy cell? How do mutations occur? Where along the DNA sequence do mutations happen? And why?

“Basic research is fundamentally curiosity-driven research,” says Milka Kostic, Program Director, Chemical Biology at Dana-Farber Cancer Institute. “Think of that moment when an apple fell on Isaac Newton’s head. He thought to himself, ‘Why did that happen?’ and then went on to try to find the answer. That’s basic research.”

Clinical Research

Clinical research explores whether new treatments, medications and diagnostic techniques are safe and effective in patients. Physicians administer these to patients in rigorously controlled clinical trials, so that they can accurately and precisely monitor patients’ progress and evaluate the treatment’s efficacy, or measurable benefit.

“In clinical research, we’re trying to define the best treatment for a patient with a given condition,” Frank says. “We’re asking such questions as: Will this new treatment extend the life of a patient with a given type of cancer? Could this supportive medication diminish nausea, diarrhea or other side effects? Could this diagnostic test help physicians detect cancer earlier or distinguish between fast- and slow-growing cancers?”

Successful clinical researchers must draw on not only their medical training but also their knowledge of such areas as statistics, controls and regulatory compliance.

Translational Research

It’s neither practical nor safe to transition directly from studying individual cells to testing on patients. Translational research provides that crucial pivot point. It bridges the gap between basic and clinical research by bringing together a number of specialists to refine and advance the application of a discovery. “Biomedical science is so complex, and there’s so much knowledge available.” Frank says. “It’s through collaboration that advances are made.”

For example, let’s say a basic researcher has identified a gene that looks like a promising candidate for targeted therapy. Translational researchers would then evaluate thousands, if not millions, of potential compounds for the ideal combination that could be developed into a medicine to achieve the desired effect. They’d refine and test the compound on intermediate models, in laboratory and animal models. Then they would analyze those test results to determine proper dosage, side effects and other safety considerations before moving to first-in-human clinical trials. It’s the complex interplay of chemistry, biology, oncology, biostatistics, genomics, pharmacology and other specialties that makes such a translational study a success.

Collaboration and technology have been the twin drivers of recent quantum leaps in the quality and quantity of translational research. “Now, using modern molecular techniques,” Frank says, “we can learn so much from a tissue sample from a patient that we couldn’t before.”

Translational research provides a crucial pivot point after clinical trials as well. Investigators explore how the trial’s resulting treatment or guidelines can be implemented by physicians in their practice. And the clinical outcomes might also motivate basic researchers to reevaluate their original assumptions.

“Translational research is a two-way street,” Kostic says. “There is always conversation flowing in both directions. It’s a loop, a continuous cycle, with one research result inspiring another.”

Learn more about research at Dana-Farber .

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Home » FDA-NIH Want Your Input on a New Resource for Terminology in Clinical Research

FDA-NIH Want Your Input on a New Resource for Terminology in Clinical Research

Consider the tomato. Or as some would call it, the “tomahto.” The whole tomato-tomahto debate has entered the language as an example of a difference so small, it doesn’t change anything.  For example, people will generally know what you are referring to no matter how you pronounce it.  But what if one group of people thought a tomato was a red plant suitable for making delicious curries and burger toppings, while other thought a tomahto was a green fruit only found in the southern Australia?  This misunderstanding would certainly cause some considerable confusion at the family barbeque.

I choose the example above since it provides a good analogy for a problem that NIH and FDA have identified in the clinical research space: critical terms are not being used consistently across the clinical research landscape.  This is specifically problematic when discussing innovative clinical trial designs and certain studies using real world data to generate real world evidence. What are some of the perils of having a modern-day Tower of Babel when it comes to clinical research? For starters, if different words mean different things to people, and are operationalized differently in different trials, how can we compare results from or pool data from different trials?   Inconsistent usage of terms can also pose specific challenges in understanding the intended meaning and impact of terms.  Problems from inconsistently terms can also cause major headaches when trying to describe a study design, communicating the goals of a planned study, or interpreting and describing research results.

To avoid the pitfalls that inconsistent use of terms can lead to, NIH and FDA created an inter-agency team of experts to study the issue and develop a resource that could be used to assist the research community in effectively communicating about clinical trials.  As a result of the team’s efforts, NIH and FDA have released a glossary of terms related to clinical research for public comment.  Right off the bat, we should make clear that this glossary is not intended to cover the entire landscape of clinical research.  The glossary contains 37 terms the team identified as being inconsistently used within the scientific community. 

The NIH and FDA are most interested in hearing community feedback on the utility of the glossary in its goal of promoting effective communications.  In addition, we want to hear from you about how we did.  Did we leave any words out that we should have included? Did we include any words that aren’t necessary?  Comments on the draft glossary will be accepted until June 24, 2024.  For more information, including how to view the glossary and how to provide comments, please visit: https://osp.od.nih.gov/comment-form-fda-nih-resource-on-terminology-for-clinical-research/

The NIH and the FDA encourage all interested parties to review the glossary and provide feedback to ensure the glossary meets its directed effect. Having a resource that defines these often inconsistently used terms will help ensure that valuable clinical research is not lost in translation.

Lyric Jorgenson, PhD

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Associate Director for Clinical Research

The National Institute of Allergy and Infectious Diseases (NIAID), one of the largest institutes in the National Institutes of Health (NIH), and part of the Department of Health and Human Services (HHS), conducts and supports basic and applied research to better understand, treat, and ultimately prevent infectious, immunologic, and allergic diseases.

The Division of AIDS (DAIDS) within NIAID seeks an exceptional and visionary leader to serve as the associate director for clinical research,   reporting to the Director of DAIDS. 

DAIDS was formed in 1986 to develop and implement the national research agenda to address the HIV/AIDS epidemic. Toward that end, DAIDS supports a global research portfolio to advance biological knowledge of HIV/AIDS and its related co-infections and co-morbidities. 

With the ultimate goal of ending the HIV epidemic, DAIDS develops and supports the infrastructure and biomedical research needed to 1) reduce HIV incidence through the development of effective biomedical prevention strategies, including vaccines that are safe and desirable; 2) develop novel approaches for the treatment and cure of HIV infection; 3) develop interventions to treat and/or prevent co-infections and co-morbidities of greatest significance; 4) engage scientific and community stakeholders to implement effective interventions equitably; 5) implement strategies to foster diversity, equity, inclusion, and accessibility activities to include growing a diverse, talented, and trained workforce; and 6) foster new extramural partnerships to address topics of significant mutual interest.

DAIDS supports the world’s largest HIV clinical trials networks with an annual budget of over $296 million. The scope of clinical trials that DAIDS directs is extensive and includes prevention of HIV acquisition studies using interventions such as oral pills, vaginal rings, vaccines, monoclonal antibodies, and long-acting medications in multiple vulnerable populations, including women, children, and LGBTQ youth and adults. Therapeutic trials include interventions to treat and/or cure HIV in all ages, from infants to adults, as well as treatment of the co-infections and co-morbidities that most impact the health of people living with HIV. Currently, DAIDS has 90 ongoing trials with more than 52,000 participants, with a target enrollment of more than 120,000. 

Responsibilities of the associate director for clinical research position include the following:

• Strategically prioritize and coordinate funding of DAIDS' diverse portfolio of competing clinical studies in prevention and treatment, ensuring adherence to NIAID-wide clinical research policies
• Ensure the ethical and safe execution of all DAIDS-funded clinical research and oversee all stages of the clinical trials including protocol development, review, and approval through protocol review committees and initiation and completion of the trial by the clinical trials networks including data review by data safety monitoring boards and implementation of their recommendations
• Oversee the maintenance of the clinical trials infrastructure to ensure that the networks are current, incorporating mandated changes to policies so that they are positioned to quickly and efficiently pivot to address future public health emergencies in the United States and abroad while maintaining ongoing studies in HIV prevention and treatment 
• Play a key role in designing and implementing future directions and renewals of DAIDS’ clinical trial networks

Qualifications

• U.S. citizenship is required.  
• For the full list of required qualifications, please review the vacancy announcement. 

Preferred Candidates will have:

• Clinical knowledge for this position should include expertise in infectious diseases, especially HIV and/or other infections such as tuberculosis, hepatitis B, and hepatitis C, and an in-depth understanding of the non-infectious co-morbidities such as cardiovascular disease, liver disease, and multi-morbidities that affect people living with HIV.
• Strong understanding of community outreach and biomedical ethics 
• Knowledge of how to assemble stakeholder groups to advance a shared vision. 
• Experience dealing with complex safety and data issues, including those arising during the evaluation of interventions, products, or devices that might involve significant scientific controversy or have far-reaching implications for clinical research.
• Demonstrated, active role in the development of scientific or regulatory guidelines for clinical research evaluation across NIAID, NIH, and relevant government agencies.

Visit www.USAJobs.gov and access the detailed vacancy announcement # NIH-SR-DH-24-12450582 beginning September 20, 2024 . Applications must be submitted online by 11:59 p.m. on September 24, 2024 . All information provided by applicants will remain confidential and will be reviewed only by authorized officials of NIAID.

In your curriculum vitae, please include a description of your leadership, mentoring, and outreach activities, especially those involving women and persons from other groups that are underrepresented in biomedical research, to promote inclusive excellence in the biomedical research workforce.

For questions about the application process, email Susie Yi-Miller at  [email protected] . 

Applications from women, persons from underrepresented groups, and persons with disabilities are strongly encouraged to apply. This position is subject to a background investigation.

HHS, NIH, and NIAID are equal opportunity employers dedicated to diversity, equity, and inclusion. NIH is dedicated to building a diverse community through its training and employment programs.

• Open access
• Published: 28 August 2024

Comparison of gepant effects at therapeutic plasma concentrations: connecting pharmacodynamics and pharmacokinetics

• Deirdre M. Boucherie 1 ,
• Ruben Dammers 2 ,
• Arnaud Vincent 2 ,
• A. H. Jan Danser 1 &
• Antoinette MaassenVanDenBrink 1  

The Journal of Headache and Pain volume  25 , Article number:  141 ( 2024 ) Cite this article

Metrics details

Orally administered second-generation gepants are effective for the treatment of migraine. The intranasal administration of the third-generation gepant zavegepant might have additional benefits including a rapid onset of action, but it is not clear yet to which extent this has clinical relevance.

We examined the effect of zavegepant on the relaxations induced by calcitonin gene-related peptide (CGRP) in human isolated middle meningeal arteries. Furthermore, we connected the pharmacodynamics and pharmacokinetics of gepants by combining data from clinical and basic research.

We showed that 10 nM zavegepant potently antagonized the functional response to CGRP. We also showed that all gepants are effective at inhibiting functional responses to CGRP at their therapeutic plasma concentrations.

Conclusions

The relatively low predicted potency of zavegepant to inhibit CGRP-induced relaxation at therapeutic systemic plasma concentrations may point to the relevance of local delivery to the trigeminovascular system through intranasal administration. This approach may have additional benefits for various groups of patients, including overweight patients.

Peer Review reports

Calcitonin gene-related peptide (CGRP) plays a crucial role in the pathophysiology of migraine. During a migraine attack, the levels of the potent vasodilatory neuropeptide CGRP are elevated, and infusion of CGRP may induce migraine-like attacks in patients with migraine [ 25 , 26 , 30 , 37 ]. Upon stimulation of the trigeminal ganglion, CGRP is released from trigeminal neurons, thereby activating nociceptive pain pathways and inducing intracranial vasodilation [ 25 ].

This knowledge on the role of CGRP in the pathogenesis of migraine has led to the development of drugs directed against CGRP and its receptor, i.e., CGRP(-receptor) targeting monoclonal antibodies and small-molecule CGRP receptor antagonists called gepants. In the early twenty-first century, several small-molecule CGRP receptor antagonists were developed, the majority of which had moderate affinity for the CGRP receptor [ 42 ]. These discoveries paved the way for the first generation of gepants that were advanced into clinical trials, namely olcegepant and telcagepant. Although the first-generation gepants were effective for the acute treatment of migraine attacks, their development was ceased. Telcagepant induced liver toxicity [ 33 ], whereas the low bioavailability of olcegepant and, therefore, its intravenous administration were considered a clinical limitation [ 45 , 49 ]. The second-generation gepants ubrogepant, rimegepant, and atogepant are administered orally and were developed for either the acute treatment of attacks (ubrogepant), preventive treatment (atogepant), or both (rimegepant). These gepants are effective and do not exhibit any liver toxicity [ 50 ]. All three second-generation gepants have received approval from the FDA and EMA.

The third-generation gepant zavegepant (formerly named vazegepant) was developed for the acute treatment of migraine as an intranasal formulation. Intranasal administration can induce rapid effects as a drug can move across a single layer of epithelial cells into the bloodstream, leading to several benefits over oral formulations including a shorter time to reach the maximum plasma concentration and, thus, a faster onset of treatment effects and rapid pain relief [ 16 , 46 ]. Additionally, intranasal delivery could potentially provide advantages for patients with severe nausea or vomiting [ 38 ]. Finally, it cannot be excluded that intranasal delivery would exert a direct trigeminovascular effect [ 23 , 35 , 41 ], although we are not aware of any data that could substantiate or refute this hypothesis. Zavegepant is currently in late-stage development and appears both efficacious and safe, also in terms of hepatotoxicity [ 16 , 38 ]. Whether an intranasal formulation is more efficacious than oral administration and whether all gepants are equally efficacious and safe remain to be determined, as head-to-head trials for gepants have not been performed. Moreover, information on which group of patients would benefit from which gepant or administration method is highly relevant as gepants enter the market.

Our group has previously studied and compared the vascular effects of the then available gepants in coronary and intracranial arteries in a preclinical setting [ 18 , 21 , 27 , 28 , 43 , 47 ]. In the current study, we aimed to characterize the functional response to CGRP in the absence or presence of the newest gepant zavegepant in human middle meningeal arteries (HMMA). With the middle meningeal artery being innervated by trigeminal nerve endings, this vascular bed is a relevant proxy for functional responses of the trigeminovascular system. Our second aim was to compare the blocking effect of gepants at therapeutic concentrations on CGRP-induced relaxation calculated from clinical gepant plasma levels. If the systemic concentrations of gepants are related to efficacy, which we assume to be similar across all gepants [ 19 , 29 , 40 ], we would expect a similar blocking effect towards CGRP for all gepants. The method utilized here enables the connection of in vitro pharmacodynamics to clinical pharmacokinetics.

Characterisation of zavegepant in human isolated middle meningeal arteries

HMMAs were obtained from 6 patients (2 females, 4 males; 52 ± 19 years of age) undergoing neurosurgery at Erasmus MC University Medical Center, Rotterdam, the Netherlands. All patients that were planned for pterional or temporal approaches indicated for tumour surgery, aneurysm surgery, or trauma surgery were eligible for HMMA harvesting. HMMAs were harvested by excision from the dura only if they did not experience any trauma by the craniotomy. Immediately upon dissection, the HMMAs were stored at 4 °C in Medium 199 (Westburg, the Netherlands) and rapidly transported to the laboratory. The surrounding dura and connective tissue were gently removed and the HMMA was stored overnight at 4 °C in oxygenated (95% O 2 , 5% CO 2 ) high-glucose Krebs buffer (119 mM NaCl, 4.7 mM KCl, 1.25 mM CaCl 2 , 1.2 mM MgSO 4 , 1.2 mM KH 2 PO 4 , 25 mM NaHCO 3 , and 11.1 mM glucose; pH = 7.4).

For functional measurements the arteries were cut into 2-mm segments and mounted using Ø 40 μm stainless-steel wires in Mulvany myograph organ baths (Danish Myo Technology, Aarhus, Denmark) filled with high-glucose oxygenated Krebs buffer at 37 °C. Tension data were recorded using LabChart data acquisition (AD Instruments, Oxford, UK). After 30 min of equilibration, the tension of the arteries was normalized to 90% of the estimated diameter at 100 mmHg transmural pressure [ 44 ]. To assess viability and to obtain an internal standard for the contractile capacity per segment, the segments were contracted with 30 mM KCl, washed, and subsequently contracted with 100 mM KCl. Next, the segments were incubated with or without 10 nM zavegepant (zavegepant hydrochloride HY-132131, Bio-Connect, the Netherlands) dissolved in dimethyl sulfoxide and diluted in milliQ for 30 min prior to constructing a concentration–response curve for human αCGRP (Polypeptide Group, Baar, Switzerland; 0.01 nM – 1 µM, half logarithmic steps). After thorough washing, endothelial function was assessed with substance P (MCE, HY-P0201; 10 – 100 nM) after precontraction with U46619 (Sigma-Aldrich, D8174; 10 – 100 nM). CGRP-induced relaxation was expressed as a percentage of the precontraction to 30 mM KCl. Using nonlinear regression in Prism 8 (GraphPad Software, San Diego, CA, USA), pEC 50 values and the pK B were calculated for each experiment to assess potency. In case that the concentration–response curve with zavegepant did not reach a plateau, the pEC 50 was interpolated from a nonlinear regression that was restricted to the E max obtained with the corresponding control segment. A paired t-test was performed for pEC 50 values and KCl responses.

Analysis of gepant potency

Data collection.

We collected data from the literature for the following gepants: rimegepant, ubrogepant, atogepant, and zavegepant, all of which were previously or currently in clinical development. Data on clinical pharmacokinetics, plasma-protein binding, and the (proposed) clinical dose were collected. Pharmacodynamic data on the potency of the aforementioned gepants, excluding zavegepant, were sourced from prior studies conducted within the same laboratory at the Erasmus MC University Medical Center in Rotterdam, the Netherlands using the same methodology [ 27 , 28 , 43 , 47 ]. The original data on the pharmacological characterization of zavegepant are presented in the current paper.

Analysis of pharmacokinetic data

First, we transformed the data on therapeutic plasma concentrations of gepants and calculated total and plasma protein-corrected values. For a schematic overview of the analysis, see Fig.  1 . Pharmacokinetic data (i.e., C max ) from the highest approved dose were used, because these data were accessible for all gepants and this approach would thus enhance comparability. C max values were first converted to nanomolar concentrations to facilitate comparing pharmacokinetic data between the gepants. Next, C max values were corrected for plasma-protein binding to obtain the free fraction C max . For subsequent calculations, we used both the values of the total C max (bound and unbound) and the free fraction C max (corrected for plasma-protein binding), as a small deviation in the amount of plasma-protein binding affects the free fraction to a major extent, and we considered therefore the comparison between data more balanced when presenting both total and plasma protein-corrected values.

Schematic overview of calculations of the potency of the gepants at their therapeutic plasma concentrations

Connecting pharmacodynamics and pharmacokinetics

We then calculated the potency of the gepants at these plasma concentrations to block CGRP-induced relaxation (see Fig.  1 ). To this end, we combined the abovementioned pharmacokinetic data with pharmacodynamic data on the potency of gepants (i.e., pEC 50 , pK B , or pA 2 values, whichever were available). We used potency data obtained with 10 nM of each gepant. The pharmacodynamic data were used to calculate the pEC 50 values that CGRP would have in the presence of gepant levels corresponding to the C max. The pEC 50 of CGRP in the absence of an antagonist served as a control. Subsequently, we interpolated relaxation that would occur in response to 100 nM CGRP in the presence of the C max . To achieve this, the shift to the right was calculated by subtracting the calculated pEC 50 from the control pEC 50 . The concentration of 100 nM CGRP was used in the analysis because this concentration induces almost the maximum relaxation in the absence of a gepant and was included in all pharmacological characterizations. To enhance the accuracy of the interpolation, our analysis focused solely on gepants with C max values and pharmacological characterizations within the nanomolar range, thereby excluding telcagepant and olcegepant. This approach reduced the need for assumptions, particularly considering that Schild plot data in HMMA were not available for all gepants.

Functional responses of the human middle meningeal artery to CGRP in the absence or presence of zavegepant

We aimed to characterise the functional response to human αCGRP in the absence or presence of 10 nM zavegepant in HMMA. Prior to the construction of the concentration–response curve to CGRP, the HMMA segments were challenged with 30 mM KCl and 100 mM KCl, which did not differ between the groups (30 mM KCl: control 6.92 ± 5.11 mN, zavegepant 7.47 ± 3.44 mN; KCl 100 mM: control 5.49 ± 4.99 mN, zavegepant 5.82 ± 3.17 mN). All HMMA segments had functional endothelium (substance P-induced relaxation: control 72.3 ± 6.2% of precontraction obtained with U46619, zavegepant 62.8 ± 32.9%). CGRP induced a functional vasorelaxant response with an E max of 75.1 ± 11.6%. Zavegepant at 10 nM significantly shifted the concentration–response curve to CGRP to the right (control pEC 50 : 8.40 ± 0.09; 10 nM zavegepant pEC 50 : 6.38 ± 0.07; p  = 0.0001; mean ± SEM; Fig.  2 ). Zavegepant did not induce vasocontraction. The pK B for 10 nM zavegepant was 10.02 ± 0.07. The pA 2 value could not be calculated because we used only one concentration of zavegepant.

The effect of 10 nM zavegepant on the αCGRP-induced relaxation of human middle meningeal arteries ( n  = 6). The results are expressed as the mean ± SEM

Comparison of the potency of gepants at therapeutic concentrations to block CGRP-induced relaxation

In the second part of our analysis, we calculated the potency of gepants at their therapeutic plasma concentrations to block relaxation induced by 100 nM CGRP. To this end, we performed calculations based on both clinical pharmacokinetics and in vitro pharmacodynamics (see Supplemental Table  1 ). Concerning the clinical pharmacokinetics, the median total C max ranged from 24 nM for zavegepant to 1,420 nM for rimegepant and the median free fraction C max ranged from a median of 2.4 nM (zavegepant) to 57 nM (rimegepant) (Table  1 ; Fig.  3 A-B).

Gepant plasma concentrations, pEC 50 of CGRP, and interpolated CGRP-induced relaxation in the absence or presence of therapeutic gepant plasma concentrations, based on values of total C max (bound and unbound; A, C, E) and free fraction C max (corrected for plasma-protein binding; B, D, F). A-B) Maximum plasma concentration (C max ) measured in clinical trials. C-D) pEC 50 of CGRP in the absence or presence of gepants at their therapeutic plasma concentrations (C max ). E–F) Relaxation induced by 100 nM CGRP in the presence of a therapeutic concentration of the gepants, as a percentage of the relaxation induced by 100 nM CGRP in the absence of a gepant. All data are presented as median with range

Next, we used the C max to calculate the potency of each gepant to block CGRP-induced relaxation at their therapeutic concentrations by means of the pEC 50. While the median pEC 50 of CGRP in the absence of a gepant was 8.4 (range 8.2–8.7), the median pEC 50 of CGRP in the presence of a gepant ranged from 3.4 (atogepant) to 6.0 (zavegepant) for the total C max and from 5.2 (atogepant) to 7.0 (zavegepant) for the free fraction C max (Table  1 ; Fig.  3 C-D), demonstrating a clear shift to the right for all gepants at therapeutic concentrations.

Then, we interpolated CGRP-induced relaxation when a gepant at a therapeutic concentration (i.e., C max ) would be present. With the response to 100 nM CGRP in the absence of a gepant set to 100%, all gepants were able to block CGRP-induced vasorelaxation (Fig.  3 E-F). Atogepant was most potent for both the calculations based on total C max and free fraction C max : 100 nM CGRP would induce 0% (total C max ) or 4.5% (free fraction C max ) relaxation in the presence of atogepant, followed by rimegepant (0.9% and 12.4%), ubrogepant (3.2% and 18.6%), and zavegepant (13.2% and 48.2%).

Demographics and clinical characteristics of the trial populations

Clinical pharmacokinetic data were mainly obtained from small samples of healthy volunteers, with the exception of rimegepant, which was measured both in healthy volunteers and lactating women (Table  2 ). The age of the participants, sex distribution, and body mass index were not reported for any of the studies.

Our first objective was to characterize the response to CGRP in the absence or presence of zavegepant, the only intranasally administered gepant, in HMMAs. Our results demonstrated that 10 nM zavegepant potently antagonizes the functional response to CGRP. Our second aim was to compare the blocking effect of therapeutic gepant concentrations on CGRP-induced relaxation. Our comparison revealed that all approved gepants effectively block the response to CGRP at their respective therapeutic plasma concentrations, with atogepant exhibiting the most potent inhibitory effect and zavegepant demonstrating the least inhibitory effect.

Although no head-to-head trials have been performed, several meta-analyses of gepants have been published recently that corroborate the assumption of similar efficacy across gepants. For the preventive gepants atogepant and rimegepant, the primary endpoint of reduction in mean monthly migraine days compared with placebo varied between -0.8 [-1.56; -0.04] (OR [95% CI]) for rimegepant 75 mg and -1.35 [-1.85; -0.85] for atogepant 60 mg [ 29 ]. For the acutely acting gepants rimegepant, ubrogepant, and zavegepant, two-hour pain relief versus placebo was between 1.16 [1.06–1.24] (RR [95% CI]) for zavegepant 10 mg and 1.37 [1.27–1.46] for rimegepant 75 mg in a meta-analysis [ 19 ]. In a preliminary meta-analysis of rimegepant and zavegepant, the percentage of patients experiencing two-hour pain relief was very similar for rimegepant 75 mg and zavegepant 10 mg (58.0% [56.0–60.2] versus 59.5% [56.4–62.5]) [ 40 ]. No comparison was available with data on two-hour pain freedom of the acute gepants. Intranasal delivery facilitates rapid absorption through the nasal mucosa, which leads to a fast onset of action, and might also make it suitable for patients experiencing nausea and vomiting. However, based on the similar efficacy observed among gepants, it is still debated whether the intranasal delivery of zavegepant offers additional therapeutic advantages compared to the orally administered gepants [ 19 , 29 , 38 , 40 , 46 ]. Notably, comparing clinical efficacy does not take into account that zavegepant exhibits a lower systemic concentration compared to the other gepants. These lower concentrations are confirmed by a lower blocking effect of CGRP in our analyses. If systemic concentrations were linked to efficacy, the therapeutic efficacy of zavegepant should have been inferior to that of the orally administered gepants. Given the fact that the efficacy is similar across gepants, we propose that the intranasal formulation of zavegepant could offer several benefits when compared to orally administered gepants.

The similar efficacy of zavegepant may indicate that its intranasal administration has not only a systemic effect, but rather a local effect. Indeed, the findings from the current study corroborate this hypothesis. Trigeminal nerve endings innervate the HMMA, which renders it a good proxy for the trigeminovascular system [ 35 ]. The nasal cavity is also largely lined with trigeminal nerve endings [ 35 ]. In HMMA, we show here that zavegepant has a relatively low potency to block CGRP-induced relaxation at its therapeutic plasma concentration (i.e., C max ). Therefore, these findings may indicate the relevance of local delivery directly to the trigeminovascular system through intranasal administration (Fig.  4 ).

Local delivery of zavegepant directly to the trigeminovascular system through intranasal administration may improve pharmacokinetics, in addition to systemic absorption via the nasal mucosa. The nasal cavity is largely lined with trigeminal nerve endings. Created with BioRender.com

The trigeminal nerve innervates both the HMMA and nasal cavity, but not via the same afferents. The HMMA is mainly, but not exclusively, innervated by the ophthalmic branch (V1), whereas the trigeminal nerve endings lining the nasal cavity are from the maxillary branch (V2) [ 20 , 35 ]. Previous research has shown that activation of different branches of the trigeminal nerve is relevant in migraine, which may demonstrate general trigeminal activation during a migraine attack. CGRP measured in saliva (mandibular branch/V3) is related to the different migraine phases [ 3 ] and has shown promise as a predictor for therapeutic responses to rizatriptan [ 15 ] and erenumab [ 2 ]. In the forehead model (V1) CGRP-mediated trigeminovascular reactivity is related to the treatment response of erenumab [ 17 ]. During a migraine attack, accompanying symptoms such as nasal congestion and rhinorrhoea are present in some migraine patients [ 5 ], which may hint at activation of V2. In addition, V1 is not the only branch supplying the dura mater; collaterals from V2 and V3 also provide dural innervation to small regions [ 20 ]. Future research should investigate the exact role of each part of the trigeminal nerve during a migraine attack.

If zavegepant is indeed directly delivered to the trigeminovascular system, this might have additional advantages. As it is expected that gepants distribute to adipose tissues given their lipophilicity, their plasma concentrations would be lower in overweight patients with migraine, possibly leading to reduced efficacy [ 14 ]. However, if zavegepant is indeed delivered directly to the trigeminal nerve endings, this could be beneficial for this group of patients [ 1 ]. One of the current questions concerning gepants, is which gepant will benefit which group of patients. Although evidence on the effect of sex, body mass index, or genetic background on the efficacy or side effects of gepants is lacking, it is known that results from the trials cannot be generalized to all patient populations [ 1 ]. Whether local delivery directly to the trigeminovascular system may circumvent pharmacokinetic differences between these patient populations has yet to be revealed.

In theory, intranasal delivery of zavegepant could not only be beneficial, but affect the nasal mucosa. CGRP induces vasodilation of the nasal mucosa, but the exact role of this functional response in sickness and health is not known [ 7 , 39 ]. The zavegepant clinical trials have shown side effects including taste disorder, nasal discomfort, and throat irritation, but no nasal congestion or mucosal disorder have been reported thus far [ 36 ]. Real-world studies are needed to assess whether intranasal delivery of zavegepant induces long-term nasal side effects.

Despite ongoing debate on whether the main effect of gepants is peripheral or central, our current analysis underscores the importance of their peripheral action. Although some research suggests that intranasal delivery allows medications to bypass the blood–brain barrier via the olfactory nerve [ 23 , 31 ,  34 , 41 ], this has not been demonstrated for the gepants. Localization of gepants has been observed at the trigeminovascular system and dura, which fall outside the protection of the blood–brain barrier [ 22 ]. A minor extent of blood–brain barrier crossing (1.4%) has been revealed for oral telcagepant in rhesus monkeys [ 48 ]. Although evidence is lacking, it is likely that these results are generalizable for all gepants. As estimated from our current analysis, free fraction concentrations of gepants in the central nervous system are likely in the picomolar range, which is insufficient to potently block CGRP-induced functional responses. Considering the abundant expression of CGRP in the central nervous system and the absence of reported central side effects with any gepant, this further suggests that the medication class primarily exerts its action at a peripheral site [ 13 , 32 ].

This study has several limitations. First, even though our calculations are based on large amounts of data, all calculations can only approximate in vitro results. These calculations are rather a way to extract more value from available data without using large amounts of scarce material. Our comparison is meant to make a general comparison and to be hypothesis-generating. The clinical data being reported in many different statistical formats and being based on studies with a low number of participants also reduces the accuracy of the comparison between gepants. Second, data from the clinical studies on pharmacokinetics were mainly obtained from healthy volunteers participating in phase 1 trials, and the sex and body mass index of participants were not mentioned in every publication. Responses to CGRP might be different in patients with migraine due to a potentially altered balance and expression of CGRP and its receptors in the trigeminovascular system as compared with controls.

In conclusion, the present study applied a novel method to connect pharmacodynamics and pharmacokinetics of gepants by combining data from clinical and basic research. Using this hypothesis-generating approach, we show that all gepants are effective at inhibiting functional responses to CGRP at their therapeutic plasma levels. The relatively low predicted potency of zavegepant to inhibit CGRP-induced relaxation at its therapeutic systemic plasma concentration may point to the relevance of local delivery to the trigeminovascular system through intranasal delivery, which should be further investigated in future studies.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Calcitonin gene-related peptide

Maximum plasma concentration

Human middle meningeal artery

The negative logarithm of the molar concentration that produces a twofold shift to the right in the agonist dose–response curve

Negative logarithm of the molar concentration of an agonist that would induce half of the maximum response

The negative logarithm of the molar concentration that would occupy 50% of the receptors at equilibrium

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DMB and AMvdB designed the study. Human tissues were provided by RD and AV. DMB performed experiments and analyses, designed the figures, and drafted the manuscript. DMB, RD, AV, AHJD, and AMvdB critically reviewed the manuscript. All authors have read and agreed to the published version of the manuscript.

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DMB, RD, AV, and AHJD declare no conflict of interest. AMvdB received personal fees (fees as advisor or speaker, consultancy, any other) from Allergan-Abbvie, Lilly, Lundbeck, Novartis and Teva. She received research support from Novartis, Satsuma and Tonix, as well as independent research support from the Dutch Research Council and the Netherlands Organisation for Health Research and Development.

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Boucherie, D.M., Dammers, R., Vincent, A. et al. Comparison of gepant effects at therapeutic plasma concentrations: connecting pharmacodynamics and pharmacokinetics. J Headache Pain 25 , 141 (2024). https://doi.org/10.1186/s10194-024-01846-8

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