A Bayesian Dose-Finding Design for Drug Combination Trials with Delayed Toxicities

• Activity Number: 1
• Type: Invited
• Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Ying Yuan*+ and Suyu Liu and Jing Ning
• Companies: MD Anderson Cancer Center and MD Anderson Cancer Center and MD Anderson Cancer Center
• Keywords: Missing data ; Combining drugs ; Dose finding ; Maximum tolerated dose

Abstract

Late-onset toxicity is an important issue in the emerging era of the development of novel molecularly targeted agents. We propose a Bayesian adaptive dose-finding design for combination trials with delayed toxicities. 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 through prior elicitation. To accommodate delayed toxicities, we treat the unobserved delayed toxicity outcomes as missing data and use Bayesian data augmentation to handle the resulting missing data. 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. The proposed design satisfactorily addresses the delayed toxicities and allows for fast, continuous accrual.