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Misspecification of Cox regression models with composite endpoints
1Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada.
Statistics in Medicine
|June 28, 2012
Summary
Composite endpoints in clinical trials can yield inconsistent treatment effect estimates, even with identical effects across component events. Marginal methods for analyzing multivariate failure time data offer consistent estimators and are recommended for accurate results.
Area of Science:
- Biostatistics
- Clinical Trials
- Epidemiology
Background:
- Composite endpoints are frequently used in multicenter randomized trials for cardiovascular disease, diabetes, and cancer.
- Statistical properties of treatment effect estimators based on composite endpoints have received limited attention.
Purpose of the Study:
- To investigate the statistical properties of treatment effect estimators derived from composite endpoints in multivariate time-to-event data analysis.
- To compare the consistency of composite endpoint estimators with marginal methods.
Main Methods:
- Utilized multivariate models for time-to-event data, incorporating copula functions to link marginal distributions with proportional hazards.
- Examined asymptotic and empirical properties of Cox regression estimators for time to the first event.
- Applied marginal methods for multivariate failure time data analysis.
Main Results:
- The estimator of treatment effect based on composite endpoints is often inconsistent for the common treatment effect of component events.
- The limiting value of the composite endpoint estimator is influenced by event association, stochastic ordering, and censoring.
- Marginal methods provide consistent estimators of treatment effect in this framework.
Conclusions:
- Composite endpoints may lead to biased treatment effect estimation in complex multivariate survival data.
- Marginal methods are statistically preferred for their ability to yield consistent treatment effect estimates.
- The findings have implications for the design and analysis of clinical trials using composite endpoints.
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