Misspecification of Cox regression models with composite endpoints
Article first published online: 27 JUN 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 31, Issue 28, pages 3545–3562, 10 December 2012
How to Cite
Wu, L. and Cook, R. J. (2012), Misspecification of Cox regression models with composite endpoints. Statist. Med., 31: 3545–3562. doi: 10.1002/sim.5436
- Issue published online: 23 NOV 2012
- Article first published online: 27 JUN 2012
- Manuscript Accepted: 17 APR 2012
- Manuscript Received: 24 MAY 2011
- composite endpoint;
- Cox regression;
- model misspecification;
- randomized clinical trial
Researchers routinely adopt composite endpoints in multicenter randomized trials designed to evaluate the effect of experimental interventions in cardiovascular disease, diabetes, and cancer. Despite their widespread use, relatively little attention has been paid to the statistical properties of estimators of treatment effect based on composite endpoints. We consider this here in the context of multivariate models for time to event data in which copula functions link marginal distributions with a proportional hazards structure. We then examine the asymptotic and empirical properties of the estimator of treatment effect arising from a Cox regression model for the time to the first event. We point out that even when the treatment effect is the same for the component events, the limiting value of the estimator based on the composite endpoint is usually inconsistent for this common value. We find that in this context the limiting value is determined by the degree of association between the events, the stochastic ordering of events, and the censoring distribution. Within the framework adopted, marginal methods for the analysis of multivariate failure time data yield consistent estimators of treatment effect and are therefore preferred. We illustrate the methods by application to a recent asthma study. Copyright © 2012 John Wiley & Sons, Ltd.