title: Bayesian sample sizes for exploratory clinical trials comparing multiple experimental treatments with a control.
abstract: In this paper, a Bayesian approach is developed for simultaneously comparing multiple experimental treatments with a common control treatment in an exploratory clinical trial. The sample size is set to ensure that, at the end of the study, there will be at least one treatment for which the investigators have a strong belief that it is better than control, or else they have a strong belief that none of the experimental treatments are substantially better than control. This criterion bears a direct relationship with conventional frequentist power requirements, while allowing prior opinion to feature in the analysis with a consequent reduction in sample size. If it is concluded that at least one of the experimental treatments shows promise, then it is envisaged that one or more of these promising treatments will be developed further in a definitive phase III trial. The approach is developed in the context of normally distributed responses sharing a common standard deviation regardless of treatment. To begin with, the standard deviation will be assumed known when the sample size is calculated. The final analysis will not rely upon this assumption, although the intended properties of the design may not be achieved if the anticipated standard deviation turns out to be inappropriate. Methods that formally allow for uncertainty about the standard deviation, expressed in the form of a Bayesian prior, are then explored. Illustrations of the sample sizes computed from the new method are presented, and comparisons are made with frequentist methods devised for the same situation.
authors.affiliation: Department of Mathematics and Statistics, Lancaster University, Lancaster, U.K.
authors.forename: John
authors.initials: J
authors.lastname: Whitehead
authors.forename: Faye
authors.initials: F
authors.lastname: Cleary
authors.forename: Amanda
authors.initials: A
authors.lastname: Turner
mesh_terms: D000959:Antihypertensive Agents / Q000008:administration & dosage / Q000494:pharmacology; D001499:Bayes Theorem; D001539:Bendroflumethiazide / Q000008:administration & dosage / Q000494:pharmacology; D015982:Bias; D001794:Blood Pressure / Q000187:drug effects; D004305:Dose-Response Relationship, Drug; D015507:Drugs, Investigational; D023381:Endpoint Determination; D006801:Humans; D006973:Hypertension / Q000188:drug therapy; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data*; D018401:Sample Size; D035501:Uncertainty
chemical_list: D000959:Antihypertensive Agents; D015507:Drugs, Investigational; D001539:Bendroflumethiazide
keywords: Bayesian design; clinical trial; multiple treatments; phase II trial; sample size calculation