Among various design approaches to phase III clinical trials with a predictive biomarker, the marker-stratified all-comers design is advantageous because it allows for establishing the utility of both treatment and biomarker, but it is often criticized for requiring large sample sizes, since the design includes both marker-positive and marker-negative patients. In this paper, we propose a simple but flexible subgroup-focused design for marker-stratified trials that allows both sequential assessment across marker-defined subgroups and adaptive subgroup selection, while retaining an assessment using the entire patient cohort at the final analysis stage, possibly using established marker-based multiple testing procedures. Numerical evaluations indicate that the proposed marker-stratified design has a robustness property in preserving statistical power for detecting various profiles of treatment effects across the subgroups, while effectively reducing the number of randomized patients in the marker-negative subgroup with presumably limited treatment efficacy. In contrast, the traditional all-comers and sequential enrichment designs could suffer from low statistical power for some possible profiles of treatment effects. The latter also need long study durations and a large number of marker screened patients. We also provide an application to SWOG S0819, a trial to assess the role of cetuximab in treating non-small cell lung cancers. These evaluations indicate that the proposed subgroup-focused approach can enhance the efficiency of the marker-stratified design for definitive evaluation of treatment and biomarker in phase III clinical trials.
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