Treatment effect heterogeneity for univariate subgroups in clinical trials: Shrinkage, standardization, or else.

ABSTRACT: Treatment effect heterogeneity is a well-recognized phenomenon in randomized controlled clinical trials. In this paper, we discuss subgroup analyses with prespecified subgroups of clinical or biological importance. We explore various alternatives to the naive (the traditional univariate) subgroup analyses to address the issues of multiplicity and confounding. Specifically, we consider a model-based Bayesian shrinkage (Bayes-DS) and a nonparametric, empirical Bayes shrinkage approach (Emp-Bayes) to temper the optimism of traditional univariate subgroup analyses; a standardization approach (standardization) that accounts for correlation between baseline covariates; and a model-based maximum likelihood estimation (MLE) approach. The Bayes-DS and Emp-Bayes methods model the variation in subgro

SUBMITTER: Varadhan R 

PROVIDER: S-EPMC5226126 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature