A multiple comparison procedure for dose‐finding trials with subpopulations

Identifying subgroups of patients with an enhanced response to a new treatment has become an area of increased interest in the last few years. When there is knowledge about possible subpopulations with an enhanced treatment effect before the start of a trial it might be beneficial to set up a testing strategy, which tests for a significant treatment effect not only in the full population, but also in these prespecified subpopulations. In this paper, we present a parametric multiple testing approach for tests in multiple populations for dose‐finding trials. Our approach is based on the MCP‐Mod methodology, which uses multiple comparison procedures (MCPs) to test for a dose–response signal, while considering multiple possible candidate dose–response shapes. Our proposed methods allow for heteroscedastic error variances between populations and control the family‐wise error rate over tests in multiple populations and for multiple candidate models. We show in simulations that the proposed multipopulation testing approaches can increase the power to detect a significant dose–response signal over the standard single‐population MCP‐Mod, when the specified subpopulation has an enhanced treatment effect.