Covariate adjustment in randomized trials: An overview

Abstract

This article aims to provide a practical overview of the various methods of covariate adjustment in randomized clinical trials leading to recommendation for future practice. Topics covered are baseline adjustment for a quantitative outcome (analysis of covariance), consequences of covariate adjustment for different types of outcome (quantitative, binary, time-to-event), surveys of covariate adjustment as done in published trials, regulatory guidance on covariate adjustment, how big is the gain in statistical power (a simulation study), some pertinent examples in cardiovascular trials, center-adjusted analyses (are they worthwhile?), a brief mention of some alternative approaches to covariate adjustment, other uses of covariates (eg risk models). We conclude that modest gains in statistical power are achieved by adjustment for covariates that influence prognosis.