title: Bayesian decision procedures based on logistic regression models for dose-finding studies.
abstract: Early-phase clinical trials, conducted to determine the appropriate dose of an experimental drug to take forward to later trials, are considered. The objective is to find the dose associated with some low probability of an adverse event. A Bayesian model is presented, and a decision-theoretic procedure for finding the optimal doses for each of a series of cohorts of subjects is derived. The procedure is flexible and can easily be conducted using standard statistical software. The results of simulations investigating the properties of the procedure are presented.
authors.affiliation: MPS Research Unit, The University of Reading, Earley Gate, UK.
authors.forename: J
authors.initials: J
authors.lastname: Whitehead
authors.forename: D
authors.initials: D
authors.lastname: Williamson
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000379:methods*; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D064420:Drug-Related Side Effects and Adverse Reactions; D008432:Mathematical Computing; D008954:Models, Biological; D012044:Regression Analysis