Effective sample size for computing prior hyperparameters in Bayesian phase I–II dose-finding

Abstract

Background:

The efficacy–toxicity trade-off based design is a practical Bayesian phase I–II dose-finding methodology. Because the design’s performance is very sensitive to prior hyperparameters and the shape of the target trade-off contour, specifying these two design elements properly is essential.

Purpose:

The goals are to provide a method that uses elicited mean outcome probabilities to derive a prior that is neither overly informative nor overly disperse, and practical guidelines for specifying the target trade-off contour.

Methods:

A general algorithm is presented that determines prior hyperparameters using least squares penalized by effective sample size. Guidelines for specifying the trade-off contour are provided. These methods are illustrated by a clinical trial in advanced prostate cancer. A new version of the efficacy–toxicity program is provided for implementation.

Results:

Together, the algorithm and guidelines provide substantive improvements in the design’s operating characteristics.

Limitations:

The method requires a substantial number of elicited values and design parameters, and computer simulations are required to obtain an acceptable design.

Conclusion:

The two key improvements greatly enhance the efficacy–toxicity design’s practical usefulness and are straightforward to implement using the updated computer program. The algorithm for determining prior hyperparameters to ensure a specified level of informativeness is general, and may be applied to models other than that underlying the efficacy–toxicity method.