The intent of most phase I oncology trials is to determine the maximum-tolerated dose (MTD) of an experimental treatment. One of the main considerations apart from determining the MTD is determining an appropriate schedule for administration of the treatment. Historically, schedules have been fixed prior to the start of dose finding. Recently, an increasing number of trials have been designed to determine the MTDs during a phase I component and subsequently determine a schedule during a phase II component. In this paper, we propose a Bayesian design for dose-schedule finding by jointly modeling binary toxicity and efficacy outcomes. Assuming the probability of toxicity follows an order constraint between schedules, we apply a Bayesian isotonic transformation approach to estimating the constrained parameters. We select a dose-schedule combination based on the joint posterior distribution of toxicity and efficacy. Using simulation studies for a hypothetical and a practical cancer clinical trial, we demonstrate that the proposed design performs well under different clinical scenarios.
Li, Yisheng; Bekele, Benjamin; Ji, Yuan; and Cook, John D., "Dose-Schedule Finding in Phase I/II Clinical Trials Using Bayesian Isotonic Transformation" (May 2006). UT MD Anderson Cancer Center Department of Biostatistics Working Paper Series. Working Paper 26.