Adaptive dose selection using efficacy-toxicity trade-offs: illustrations and practical considerations.
The purpose of this paper is to describe and illustrate an outcome-adaptive Bayesian procedure, proposed by Thall and Cook (2004), for assigning doses of an experimental treatment to successive cohorts of patients. The method uses elicited (efficacy, toxicity) probability pairs to construct a family of trade-off contours that are used to quantify the desirability of each dose. This provides a basis for determining a best dose for each cohort. The method combines the goals of conventional Phase I and Phase II trials, and thus may be called a "Phase I-II" design. We first give a general review of the probability model and dose-finding algorithm. We next describe an application to a trial of a biologic agent for treatment of acute myelogenous leukemia, including a computer simulation study to assess the design's average behavior. To illustrate how the method may work in practice, we present a cohort-by-cohort example of a particular trial. We close with a discussion of some practical issues that may arise during implementation.
Thall
Peter F
PF
Department of Biostatistics and Applied Mathematics, The University of Texas, MD Anderson Cancer Center, Houston, USA. rex@mdanderson.org
Cook
John D
JD
Estey
Elihu H
EH
D000465:Algorithms; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000009:adverse effects / Q000627:therapeutic use; D001499:Bayes Theorem; D017321:Clinical Trials, Phase I as Topic / Q000379:methods / Q000706:statistics & numerical data*; D017322:Clinical Trials, Phase II as Topic / Q000379:methods / Q000706:statistics & numerical data*; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000188:drug therapy; D015233:Models, Statistical; D012107:Research Design; D016896:Treatment Outcome