Bayesian two‐stage design for phase II oncology trials with binary endpoint. (17th February 2022)

• Record Type: Journal Article
• Authors: Chen, Lichang; Pan, Jianhong; Wu, Yanpeng; Wang, Jingxian; Chen, Fangyao; Zhao, Jun; Chen, Pingyan
• Is Part Of: Statistics in medicine. Volume 41:Number 12(2022)
• Page Start: 2291
• Page End: 2301
• Publication Date: 2022-02-17
• Subjects: Bayesian -- binary endpoint -- posterior probability -- predictive probability -- Simon's two‐stage design; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.9355
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract: In phase II oncology trials, two‐stage design allowing early stopping for futility and/or efficacy is frequently used. However, this design based on frequentist statistical approaches could not guarantee a high posterior probability of attending the pre‐specified clinically interesting rate from a Bayesian perspective. Here, we proposed a new Bayesian design enabling early terminating for efficacy as well as futility. In addition to the clinically uninteresting and interesting response rate, a prior distribution of response rate, the minimum posterior threshold probabilities and the lengths of the highest posterior density intervals were specified in the design. Finally, we defined the feasible design with the highest total effective predictive probability. We studied the properties of the proposed design and applied it to an oncology trial as an example. The proposed design ensured that the observed response rate fell within prespecified levels of posterior probability. The proposed design provides an alternative design to single‐arm two‐stage trials.