Bayesian Dose-Finding for Combined Drugs with Discrete and Continuous Doses

• Activity Number: 178
• Type: Contributed
• Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Lin Huo*+ and Ying Yuan and Guosheng Yin
• Companies: Novartis Oncology and UT MD Anderson Cancer Center and University of Hong Kong
• Keywords: Bayesian adaptive design ; Combined drugs ; Continual reassessment method ; Maximum tolerated dose ; Maximum tolerated dose ; Two-stage design

Abstract

The trend of treating patients with combined drugs has grown in cancer clinical trials. To enhance patient response, a new agent is often investigated together with an existing standard of care (SOC) agent. Often, a certain amount of dosage of the SOC is administered in order to maintain at least some therapeutic effects. For clinical trials involving a continuous-dose SOC and a discrete-dose agent, we propose a two-stage Bayesian adaptive dose-fnding design. The first stage takes a continual reassessment method to locate the appropriate dose for the discrete-dose agent while fixing the continuous-dose SOC at the minimal therapeutic dose. In the second stage, we make a fine dose adjustment by calibrating the continuous dose to achieve the target toxicity rate as closely as possible. Dose assignment is based on the posterior estimates of the joint toxicity probabilities of combined doses. As the toxicity data accumulate during the trial, we adaptively assign each cohort of patients to the most appropriate dose combination. We conduct extensive simulation studies to examine the operating characteristics and demonstrate the design's good performance with practical scenarios.