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Adaptive prior variance calibration in the Bayesian continual reassessment method

Authors


Correspondence to: Jin Zhang, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, U.S.A.

E-mail: zhjin@umich.edu

Abstract

The use of the continual reassessment method (CRM) and other model-based approaches to design Phase I clinical trials has increased owing to the ability of the CRM to identify the maximum tolerated dose better than the 3 + 3 method. However, the CRM can be sensitive to the variance selected for the prior distribution of the model parameter, especially when a small number of patients are enrolled. Although methods have emerged to adaptively select skeletons and to calibrate the prior variance only at the beginning of a trial, there has not been any approach developed to adaptively calibrate the prior variance throughout a trial. We propose three systematic approaches to adaptively calibrate the prior variance during a trial and compare them via simulation with methods proposed to calibrate the variance at the beginning of a trial. Copyright © 2012 John Wiley & Sons, Ltd.

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