|
Activity Number:
|
342
- Clinical Trial Design: Statistical Methods and Applications in Oncology
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
|
|
Sponsor:
|
Biopharmaceutical Section
|
|
Abstract #312189
|
|
|
Title:
|
A Generalized Framework of Optimal Two-Stage Designs for Exploratory Basket Trials
|
|
Author(s):
|
Fang Liu* and Xiaoqiang Wu and Iris Wu and Heng Zhou and Cong Chen
|
|
Companies:
|
Merck & Co., Inc and Florida State University and Merck and Merck and Merck and Company, Inc.
|
|
Keywords:
|
Efficacy Screening;
Basket Trial;
Master protocol;
Trial optimization
|
|
Abstract:
|
The primary goal of an exploratory oncology clinical trial is to identify an effective drug for further development. To expedite the drug development process and increase the chance of finding active tumor indications where the treatment works, multiple tumor cohorts are often investigated simultaneously in a basket trial. In this article, we extend the optimal basket trial design in Zhou et al. (2019) and propose a generalized framework of optimal basket trial designs in an exploratory setting where tumor indications can be homogeneous (the objective response rates of all indications are the same under both the null and alternative hypotheses) or heterogeneous (the objective response rates are not the same under at least one of the null and alternative hypotheses). The proposed design explicitly controls the global type I and type II error rates and minimizes the expected sample size while achieving the target power. In addition, we consider an optimal fixed sample size design with sample size reallocation when the sample size is fixed in a trial. Simulation studies are conducted to show the favorable operating characteristics of the proposed design under certain scenarios.
|
Authors who are presenting talks have a * after their name.
