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A comparison of methods for analyzing a binary composite endpoint with partially observed components in randomized
Tra My Pham1, Ian R White1, Brennan C Kahan1
1MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK.
Statistics in Medicine
|September 30, 2021
Summary
Deriving composite endpoints from observed components can bias results, even with random missing data. Multiple imputation of missing components is the preferred method for accurate analysis in clinical trials.
Area of Science:
- Biostatistics
- Clinical Trials
- Epidemiology
Background:
- Composite endpoints are frequently used in randomized controlled trials.
- Partially observed components in composite endpoints complicate data analysis.
- Current methods for handling missing data include deriving the composite endpoint, complete record analysis (CRA), and multiple imputation (MI).
Purpose of the Study:
- To compare methods for analyzing composite endpoints with partially observed components.
- To evaluate the bias introduced by deriving composite endpoints.
- To determine the most appropriate method for handling missing data in composite endpoints.
Main Methods:
- Mathematical comparison of endpoint derivation, CRA, and MI.
- Simulation studies to assess method performance.
- Reanalysis of a published trial (TOPPS) using the compared methods.
Main Results:
- Deriving composite endpoints can lead to data missing not at random, even if components are missing completely at random.
- Treatment effect estimates from derived composite endpoints are biased.
- CRA results excluding participants with missing data are valid.
- MI of components is necessary for missing at random mechanisms.
Conclusions:
- Deriving composite endpoints from observed components is generally not recommended due to potential bias.
- Multiple imputation of missing components is the preferred approach for analyzing composite endpoints with missing data.
- While imputation models carry risks, MI offers a more robust solution compared to endpoint derivation.
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