Robust time selection for interim analysis in the Bayesian phase 2 exploratory clinical trial

ABSTRACT

In phase 2 clinical trials, we expect to make a right Go or No-Go decision during the interim analysis (IA) and make this decision at the right time. The optimal time for IA is usually determined based on a utility function. In most previous research, utility functions aim to minimize the expected sample size or total cost in confirmatory trials. However, the selected time can vary depending on different alternative hypotheses. This paper proposes a new utility function for Bayesian phase 2 exploratory clinical trials. It evaluates the predictability and robustness of the Go and No-Go decision made during the IA. We can make a robust time selection for the IA based on the function regardless of the treatment effect assumptions.

KEYWORDS:

• Utility function
• robustness
• interim analysis
• Bayesian statistics
• phase 2 exploratory clinical trial

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.