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Curve-Free and Model-Based Continual Reassessment Method Designs

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Gasparini and Eisele (2000, Biometrics56, 609-615) present a development of the continual reassessment method of O'Quigley, Pepe, and Fisher (1990, Biometrics46, 33–48). They call their development a curve-free method for Phase I clinical trials. However, unless we are dealing with informative prior information, then the curve-free method coincides with the usual model-based continual reassessment method. Both methods are subject to arbitrary specification parameters, and we provide some discussion on this. Whatever choices are made for one method, there exists equivalent choices for the other method, where “equivalent” means that the operating characteristics (sequential dose allocation and final recommendation) are the same. The insightful development of Gasparini and Eisele provides clarification on some of the basic ideas behind the continual reassessment method, particularly when viewed from a Bayesian perspective. But their development does not lead to a new class of designs and the comparative results in their article, indicating some preference for curve-free designs over model-based designs, are simply reflecting a more fortunate choice of arbitrary specification parameters. Other choices could equally well have inversed their conclusion. A correct conclusion should be one of operational equivalence. The story is different for the case of informative priors, a situation that is inherently much more difficult. We discuss this. We also mention the important idea of two-stage designs (Moller, 1995, Statistics in Medicine14, 911–922; O'Quigley and Shen, 1996, Biometrics52, 163–174), arguing, via a simple comparison with the results of Gasparini and Eisele (2000), that there is room for notable gains here. Two-stage designs also have an advantage of avoiding the issue of prior specification altogether.

Keywords: Clinical trial; Curve-free continual reassessment method; Dose finding; Maximum tolerated dose; Phase I designs

Document Type: Research Article


Affiliations: Department of Mathematics, University of California at San Diego, La Jolla, California 92093, U.S.A., Email:

Publication date: 2002-03-01

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