title: On the use of nonparametric curves in phase I trials with low toxicity tolerance.
abstract: 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.
authors.affiliation: Division of Biostatistics, School of Public Health, Columbia University, New York, New York 10032, USA. cheung@biostat.columbia.edu
authors.forename: Ying Kuen
authors.initials: YK
authors.lastname: Cheung
mesh_terms: D001499:Bayes Theorem; D017321:Clinical Trials, Phase I as Topic; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D006801:Humans; D020714:Maximum Tolerated Dose; D013223:Statistics as Topic / Q000379:methods*