Adaptive Biomarker Population Selection in Phase III Confirmatory Trials with Time-to-Event Endpoints

A key component of modern drug development is to identify the patient population(s) that benefit most from the therapy. Subjects with different biomarker/genetic profiles may respond to a therapy differently. At the same time, data of populations with best efficacy may not be available due to lack of randomized data or biomarker assay when designing the phase III confirmatory trials. In this manuscript, we propose an adaptive design that performs biomarker-informed population selection at the interim analysis, so as to refine the population for primary hypothesis at the final analysis. Unlike most of the previous research work, where the same endpoint is used for interim population selection and final analysis, we propose to use a sensitive intermediate endpoint (whenever available) for population selection. Treatment effect of the intermediate endpoint is treated as a nuisance parameter to ensure type I error control. The use of a sensitive intermediate endpoint for biomarker population selection further improves study power. Simulations were conducted to evaluate the control of overall type I error, probabilities of population selection, and power.