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.