Weibull Failure-Time Mixture Models for Evaluating Efficacy in the Presence of a Biomarker

Abstract

A predictive marker is a marker that predicts the differential efficacy of a particular therapy based on marker status. Standard statistical methods compare treatments, not validate prediction. We propose a failure-time mixture model that achieves both objectives. We also explain how to evaluate efficacy in biomarker subpopulations. We use the maximum likelihood method to estimate the mixture model. We explain the computational aspects of the model and discuss the underlying statistical inference. We discuss sample size determination. We illustrate the methodology with a computer-generated data set The proposed mixture model is simple and capable of assisting investigators seeking to design marker-based clinical trials in their analyses.