A default method to specify skeletons for Bayesian model averaging continual reassessment method for phase I clinical trials

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• 作者：Haitao Pan and Ying Yuan
• 刊名：Statistics in Medicine
• 出版年：2017
• 出版时间：30 January 2017
• 年：2017
• 卷：36
• 期：2
• 页码：266-279
• 全文大小：626K
• ISSN：1097-0258

文摘

The Bayesian model averaging continual reassessment method (CRM) is a Bayesian dose-finding design. It improves the robustness and overall performance of the continual reassessment method (CRM) by specifying multiple skeletons (or models) and then using Bayesian model averaging to automatically favor the best-fitting model for better decision making. Specifying multiple skeletons, however, can be challenging for practitioners. In this paper, we propose a default way to specify skeletons for the Bayesian model averaging CRM. We show that skeletons that appear rather different may actually lead to equivalent models. Motivated by this, we define a nonequivalence measure to index the difference among skeletons. Using this measure, we extend the model calibration method of Lee and Cheung (2009) to choose the optimal skeletons that maximize the average percentage of correct selection of the maximum tolerated dose and ensure sufficient nonequivalence among the skeletons. Our simulation study shows that the proposed method has desirable operating characteristics. We provide software to implement the proposed method. Copyright