Incorporating Surrogate Information for Adaptive Subgroup Enrichment Design with Sample Size Reestimation

• Activity Number: 200 - Statistical Challenges and Opportunities for Expedited Oncology Drug Development
• Type: Topic-Contributed
• Date/Time: Tuesday, August 10, 2021 : 1:30 PM to 3:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Qing Li* and Jianchang Lin and Mengya Liu and Liwen Wu
• Companies: Takeda Pharmaceuticals and Takeda Pharmaceuticals and Takeda Pharmaceuticals and University of Pittsburgh
• Keywords: Adaptive design; Subgroup enrichment design; Surrogate endpoint; Sample size re-estimation; Modified conditional power

Abstract

Adaptive subgroup enrichment design is an efficient design framework that allows accelerated development for investigational treatments while also having flexibility in population selection within the course of the trial. The adaptive decision at the interim analysis is commonly made based on the conditional probability of trial success. However, one of the critical challenges for such adaptive designs is immature data for interim decisions, particularly in the targeted subgroup with a limited sample size at the first stage of the trial. In this talk, we will talk about how to improve the interim decision making by incorporating information from surrogate endpoints when estimating conditional power at the interim analysis, by predicting the primary treatment effect based on the observed surrogate endpoint and prior knowledge or historical data about the relationship between endpoints. Modified conditional power is developed to select the patient population to be enrolled after the interim analysis and sample size re-estimation. Operating characteristics will be discussed through simulations. We also demonstrate the application of our proposed design using an oncology example.