Online Program Home
  My Program

Abstract Details

Activity Number: 467 - Bayesian Methods and Applications in Clinical Trials (II)
Type: Contributed
Date/Time: Wednesday, August 2, 2017 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract #322514 View Presentation
Title: BOP2: Bayesian Optimal Designs for Phase II Clinical Trials with Simple and Complex Endpoints
Author(s): Heng Zhou* and Ying Yuan
Companies: MD Anderson Cancer Center and M.D. Anderson Cancer Center
Keywords: Bayesian adaptive design ; early stopping ; ordinal endpoint ; co-primary endpoints ; immunotherapy
Abstract:

We propose a flexible Bayesian optimal phase II (BOP2) design that is capable of handling simple (e.g., binary) and complicated (e.g., ordinal, nested and co-primary) endpoints under a unified framework. We use a Dirichlet-multinomial model to accommodate different types of endpoints. At each interim, the go/no-go decision is made by evaluating a set of posterior probabilities of the events of interest, which is optimized to minimize the number of patients under the null hypothesis. Unlike most existing Bayesian designs, the BOP2 design explicitly controls the type I and II error rates, thereby bridging the gap between Bayesian designs and frequentist designs. In addition, the stopping boundary of the BOP2 design can be enumerated prior to the onset of the trial. These features make the BOP2 design accessible to a wide range of users and regulatory agencies, and particularly easy to implement in practice. Simulation studies show that the BOP2 design has favorable operating characteristics with higher power and lower risk of incorrectly terminating the trial than some existing Bayesian phase II designs.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2017 program

 
 
Copyright © American Statistical Association