A Simulation Study to Compare Methods for Subgroup Identification and Subgroup Effect Inference in Clinical Trials

Abstract

Identifying subgroups, which respond differently to a treatment, both in terms of efficacy and safety, is an important part of drug development. In early phase exploratory clinical trials the well-known challenges of subgroup analyses, like multiplicity and lack of power, are further amplified by the low sample size and because relatively limited clinical prior information on the drug is available. In this thesis some novel strategies for subgroup identification and treatment effect estimation in selected subgroups are compared in a simulation study motivated by real clinical trial situations.