Description
This guidance provides sponsors and review staff with the Agency’s thinking about the problems posed by multiple endpoints in the analysis and interpretation of study results and how these problems can be managed in clinical trials for human drugs, including drugs subject to licensing as biological products. Most clinical trials performed in drug development contain multiple endpoints to assess the effects of the drug and to document the ability of the drug to favorably affect one or more disease characteristics. As the number of endpoints analyzed in a single trial increases, the likelihood of making false conclusions about a drug’s effects with respect to one or more of those endpoints becomes a concern if there is not appropriate adjustment for multiplicity. The purpose of this guidance is to describe various strategies for grouping and ordering endpoints for analysis and applying some well-recognized statistical methods for managing multiplicity within a study in order to control the chance of making erroneous conclusions about a drug’s effects. Basing a conclusion on an analysis where the risk of false conclusions has not been appropriately controlled can lead to false or misleading representations regarding a drug’s effects.
Key Topics
Terms and concepts identified from this document
Scope & Applicability
Product Classes
2development program for drug and biological products
Trials of combination vaccines are a situation in which co-primary endpoints are applicable.
Stakeholders
1Target audience for recommendations on assessment of overall survival
Regulatory Context
Regulatory Activities
1Submission for drug approval
Document Types
6Cybersecurity information should be included in device labeling
Detailed plan for dissolution profile comparison
Describes findings of safety, purity, and potency
A protocol designed with multiple substudies to evaluate medical products
Basic statistical principle for clinical trials
The type of document providing recommendations for CIPN drug development.
Attributes
8Trial design should provide strong control of Type I error
The significance level, typically 0.05.; Each vertex is allocated an initial amount of alpha.
Testing could proceed with alpha allocation across multiple hypotheses
Considerations for sample size; FDA is also concerned with the risk of making a Type II error.
Statistical parameter requiring strong control when testing multiple endpoints
Threshold (alpha) below which the Type I error rate should be controlled; Endpoints are tested at the endpoint-specific significance levels.
Probability of observing a result at least as extreme as the study result assuming the null hypothesis is true; The probability value used to determine statistical significance.; The Holm procedure directs testing the smaller p-value first.
Determined during the planning of a research study
Technical Details
Substances
1Drug used in clinical trial references for renal and cardiovascular outcomes
Testing Methods
10Statistical method for managing multiplicity; A single-step procedure commonly used for multiplicity adjustment.
The graphical approach is a means for developing and evaluating multiple analysis strategies.
A resampling approach for multiple endpoints.
An Introduction to the Bootstrap
Statistical approach using bootstrap and permutation for multiple endpoints.
A single-step method that has a slight advantage in power over the Bonferroni method.
Tested after non-inferiority without multiplicity adjustment if it is the only endpoint; To test for superiority, one should first establish non-inferiority.
A primary endpoint can be tested for non-inferiority followed by superiority; Figure A1 shows a flow diagram for non-inferiority and superiority tests.
Developed to account for complex logical/hierarchical relationships among endpoints
Used when endpoints are ordered based on clinical importance
Clinical Concepts
10For studies in which the outcome or outcomes of interest (e.g., myocardial infarction or stroke) include fatal outcomes.
evaluation of a drug for the management of Type 2 Diabetes
patients with type 2 diabetes may face unique safety issues such as a risk for hypoglycemia
Normal range of HbA1c used as a response criterion in diabetes trials.
Section D.9 regarding patient mortality
correlated with female sex in VAD study
The main outcome measure in a clinical trial
The hierarchy of families of endpoints; The endpoint with inadequate power for detection is classified as a secondary endpoint.
incorporates multiple aspects of the disease into a single endpoint
reasonably likely or expected to predict a clinical benefit
Standards & References
External Standards
1Used for rheumatoid arthritis multi-component endpoints.
Specifications
3Endpoints critical to establish effectiveness for approval
Provide useful description to support primary endpoints or demonstrate additional clinically important effects
Used for research purposes or new hypotheses generation; do not need multiplicity adjustment
ICH References (2)
Statistical Principles for Clinical Trials; Discourages deterministic procedures due to high risk of bias; Notes that the use of Bayesian methods in clinical trials may be considered.
Statistical Principles for Clinical Trials: Addendum: Estimands and Sensitivity Analysis in Clinical Trials
Related CFR Sections (2)
- 21CFR314.126§ 314.126 Adequate and well-controlled studies.
(a) The purpose of conducting clinical investigations of a drug is to distinguish the effect of a drug from other influences, such as spontaneous change in the course of the disease, placebo effect, or biased observation. The characteristics described in paragraph (b) of this section have been develRead full regulation →
- 21CFR600.3§ 600.3 Definitions.
As used in this subchapter:Read full regulation →
Related MFDS Guidelines
Korean regulatory guidelines covering similar topics
See Also (8)
- Rare Diseases: Natural History Studies for Drug Development: Draft Guidance for Industry (Status: Draft)
- Upper Facial Lines: Developing Botulinum Toxin Drug Products (Status: Draft)
- Adverse Reactions Section of Labeling for Human Prescription Drug and Biological Products — Content and Format (Status: Final)
- Format and Content of the Clinical and Statistical Sections of an Application (Status: Final)
- Providing Clinical Evidence of Effectiveness for Human Drug and Biological Products. (Status: Final)
- Bioavailability and Bioequivalence Studies for Nasal Aerosols and Nasal Sprays for Local Action (Status: Draft)
- Exposure-Response Relationships — Study Design, Data Analysis, and Regulatory Applications (Status: Final)
- Clinical Studies Section of Labeling for Human Prescription Drug and Biological Products — Content and Format: Guidance for Industry (Status: Final)