Practical Subgroup Identification Strategies in Late-Stage Clinical Trials

The chapter discusses practical considerations arising in subgroup exploration exercises in late-stage clinical trials. Subgroup identification strategies are commonly applied to characterize the efficacy profile of an experimental treatment based on the results of a failed trial with a non-significant outcome in the overall patient population. Considering this setting, we present a comprehensive overview of relevant considerations related to the selection of clinically candidate biomarkers, choice of statistical models, including the role of covariate adjustment in subgroup investigation, and selection of subgroup search parameters. The subgroup identification methods considered in the chapter rely on the SIDES family of subgroup search algorithms. We discuss applications of this methodology to failed clinical trials and its key features such as biomarker screening, complexity control and Type I error rate control. The statistical methods and considerations discussed in the chapter will be illustrated using a Phase III clinical trial for the treatment of benign prostate hypertrophy.