title: A Bayesian Dose-finding Design for Drug Combination Trials with Delayed Toxicities.
abstract: We propose a Bayesian adaptive dose-finding design for drug combination trials with delayed toxicity. We model the dose-toxicity relationship using the Finney model, a model widely used in drug-drug interaction studies. The intuitive interpretations of the Finney model facilitate incorporating the available prior dose-toxicity information from single-agent trials into combination trials through prior elicitation. We treat unobserved delayed toxicity outcomes as missing data and handle them using Bayesian data augmentation. We conduct extensive simulation studies to examine the operating characteristics of the proposed method under various practical scenarios. Results show that the proposed design is safe and able to select the target dose combinations with high probabilities.
authors.affiliation: Department of Biostatistics, The University of Texas MD Anderson Cancer Center, TX, syliu@mdanserson.org.
authors.forename: Suyu
authors.initials: S
authors.lastname: Liu
authors.affiliation: Department of Biostatistics, The University of Texas MD Anderson Cancer Center, TX, jning@mdanserson.org.
authors.forename: Jing
authors.initials: J
authors.lastname: Ning
keywords: Adaptive design; Combining drugs; Late-onset toxicity; Maximum tolerated dose; Missing data; Phase I trial