A Three-Stage Bayesian Adaptive Phase I/II Design and Simulation Studies

Abstract

Instead of using traditional separate phase I and II trials, in this article, we propose using a parallel three-stage phase I/II design, incorporating a dose expansion approach to flexibly evaluate the safety and efficacy of dose levels, and to select the optimal dose. In the proposed design, both the toxicity and efficacy responses are binary endpoints. A 3+3-based procedure is used for initial period of dose escalation at stage 1; at this level, the dose can be expanded to stage 2 for exploratory efficacy studies of phase IIa, while simultaneously, the safety testing can advance to a higher dose level. A beta-binomial model is used to model the efficacy responses. There are two placebo-controlled randomization interim monitoring analyses at stage 2 to select the promising doses to be recommended to stage 3 for further efficacy studies of phase IIb. An adaptive randomization approach is used to assign more patients to doses with higher efficacy levels at stage 3. We examine the properties of the proposed design through extensive simulation studies by using R programming language, and also compare the new design with the conventional design and a competing adaptive Bayesian design. The simulation results show that our design can efficiently assign more patients to doses with higher efficacy levels and is superior to the two competing designs in terms of total sample size reduction.

Keywords:

• Bayesian adaptive design
• Dose expansion
• Dose finding
• Phase I/II

Mathematics Subject Classification:

• Primary 62L05
• Secondary 62F15.

Acknowledgments

This work was partially supported by Research grant 81072390 and 81001290 from National Science Foundation of China. The first author’s work was partially supported by Grant 11XCK10 from Xi’an University of Finance and Economics.