Abstract C53: Dose-finding designs for combination therapies involving molecularly targeted agents

Abstract

Abstract Purpose: Novel therapies are challenging current drug development standards. Agents with specific biologic targets, unknown dose-efficacy curves, limited toxicity profiles, and in combination therapy require novel statistical designs. We compared the operating characteristics of three model based designs incorporating both toxicity and a measure of efficacy to identify the optimal dose region for combination therapies. Methods: Three designs were considered: continuation ratio model with a trinary outcome, bivariate logistic model treating toxicity and efficacy as independent outcomes, and bivariate probit model allowing for dependent toxicity and efficacy outcomes. All designs utilized a model-based methodology to adaptively determine dose escalation/de-escalation, based on the data observed to date in the trial. The model parameters were estimated using Markov chain Monte Carlo approach in a Bayesian framework. The target threshold for toxicity was set at 33%; the minimum and maximum sample sizes were set at 30 and 45, respectively, for the simulated trials; and the cohort size was 3 with at least nine patients needed to be treated at the proposed combination dose level. The performance of the designs was evaluated in simulation studies under six clinically relevant scenarios. Results: As expected, the ability to correctly identify an optimal dose region was sensitive to the changes in the toxicity and/or efficacy across the dose level combinations. Considering 50% as a benchmark for the recommendation rate for the optimal dose or region (dose levels within 10% of the maximum efficacious dose level), at least one of the three models performed well in recommending the optimal dose region except when the dose-efficacy surface was non-monotone or the dose-toxicity surface was close to the target rate of 33%. All three models worked well in not recommending any dose combination when the starting dose level combination was too toxic. The median sample size across all scenarios ranged from 27–33. Conclusions: Despite favorable operating characteristics, the implementation of these new designs in practice is challenging for a variety of reasons. Adoption of novel designs require a multi-pronged approach that provides a) clinically obvious advantages, b) practical design framework with a transparent decision making process, c) timely access to both toxicity and preliminary efficacy data, and d) portable user-friendly software, or very attentive statisticians. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):C53.