A Bayesian Decision-Theoretic Design for Simultaneous Biomarker-Based Subgroup Selection and Efficacy Evaluation. (2nd October 2022)

• Record Type: Journal Article
• Authors: Wang, Zheyu; Wang, Fujun; Wang, Chenguang; Zhang, Jianliang; Wang, Hao; Shi, Li; Tang, Zhuojun; Rosner, Gary L.
• Is Part Of: Statistics in biopharmaceutical research. Volume 14:Number 4(2022)
• Page Start: 568
• Page End: 579
• Publication Date: 2022-10-02
• Subjects: Bayesian decision-theoretic -- Biomarker -- Phase II trial -- Subgroup selection -- Two-stage design; Pharmacy -- Statistical methods -- Periodicals; Pharmaceutical biotechnology -- Statistical methods -- Periodicals; Biopharmaceutics -- Periodicals; Biometry -- Periodicals; Pharmacy -- Statistical methods; Periodicals; 615.190727
• DOI: 10.1080/19466315.2021.1873843
• Languages: English
• ISSNs: 1946-6315

Abstract

Abstract: The success of drug development of targeted therapy often hinges on an appropriate selection of the sensitive patient population, mostly based on patients' biomarker levels. At the planning stage of a Phase II study, although a potential biomarker may have been identified, a threshold value for defining sensitive patient population is often unavailable for adopting many existing biomarker-guided designs. To address this issue, we propose a two-stage design that allows for simultaneous biomarker threshold selection and efficacy evaluation while accommodating situations where the drug is efficacious in the entire patient population. The design uses a Bayesian decision-theoretic approach and incorporates the benefit and cost considerations of the study into a utility function. The operating characteristics of the proposed design under different scenarios are investigated via simulations. We also provide a discussion on the choice of the benefit and cost parameters in practice.