Multiplicity Control in Oncology Clinical Trials With a Binary Surrogate Endpoint-Based Drop-The-Losers Design.

Abstract

Typical phase 1 oncology studies identify the maximum tolerated dose as the "optimal" dose for subsequent phases. With the advancement of molecular targeted agents and immunotherapies, however, evaluating two or more doses has become increasingly critical for dose selection. Such evaluation is often done in phase 2 studies in a randomized manner. In this article, we evaluate the strategy of applying an adaptive phase 2/3 seamless design for dose selection in oncology studies. Specifically, we consider the "drop-the-losers" design, where multiple treatment arms and a control arm are administered during the initial stage, and a more effective arm is identified for later stages by a binary surrogate endpoint such as overall response. We derive the theoretical type I error inflation scale and conduct simulation studies to illustrate the impact of various factors on the type I error inflation in such designs. Furthermore, we demonstrate the findings through the design of a lung cancer trial and introduce a software that implements the proposed design.