A Bayesian phase I–II clinical trial design to find the biological optimal dose on drug combination

ABSTRACT

In recent years, combined therapy shows expected treatment effect as they increase dose intensity, work on multiple targets and benefit more patients for antitumor treatment. However, dose -finding designs for combined therapy face a number of challenges. Therefore, under the framework of phase I–II, we propose a two-stage dose -finding design to identify the biologically optimal dose combination (BODC), defined as the one with the maximum posterior mean utility under acceptable safety. We model the probabilities of toxicity and efficacy by using linear logistic regression models and conduct Bayesian model selection (BMS) procedure to define the most likely pattern of dose–response surface. The BMS can adaptively select the most suitable model during the trial, making the results robust. We investigated the operating characteristics of the proposed design through simulation studies under various practical scenarios and showed that the proposed design is robust and performed well.

KEYWORDS:

• Bayesian model selection
• drug combination
• Phase I–II clinical trial
• utility function
• adaptive design

Acknowledgment

This work was supported by the National Natural Science Foundation of China [No.s 81973145 and 82273735]. Key R&D Program of Jiangsu Province (Social Development) (BE2020694)

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/10543406.2023.2236208

Additional information

Funding

The research was supported by National Natural ScienceFoundation of China [No. 81973145, No. 82273735]. Key R & D Program of Jiangsu Province (Social Development) [BE2020694].