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On the Use of Nonparametric Curves in Phase I Trials with Low Toxicity Tolerance
Author(s) -
Cheung Ying Kuen
Publication year - 2002
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2002.00237.x
Subject(s) - prior probability , nonparametric statistics , bayesian probability , percentile , biometrics , computer science , statistics , econometrics , mathematics , artificial intelligence
Summary. Gasparini and Eisele (2000, Biometrics 56 , 609–615) propose a design for phase I clinical trials during which dose allocation is governed by a Bayesian nonparametric estimate of the dose‐response curve. The authors also suggest an elicitation algorithm to establish vague priors. However, in situations where a low percentile is targeted, priors thus obtained can lead to undesirable rigidity given certain trial outcomes that can occur with a nonnegligible probability. Interestingly, improvement can be achieved by prescribing slightly more informative priors. Some guidelines for prior elicitation are established using a connection between this curve‐free method and the continual reassessment method.