Optimal single-arm two-stage designs with consideration of dependency on efficacy and safety

In phase II clinical trials on cancer, it is of great interest to establish the efficacy and safety of a new treatment simultaneously. Existing hypotheses may not achieve this goal effectively. We introduce two new sets of hypotheses that consider the association between the two factors, then construct the optimal two-stage designs for the hypotheses. The proposed designs strictly control the maximum type I error rate at the given nominal level alpha, maintain the minimum power at least the given I - beta, and have the smallest expected total sample size under the null hypothesis. Furthermore, an algorithm is provided to compute these designs. R-codes are given in the Supplemental Material.

Automated summary

In phase II clinical trials on cancer, it is crucial to establish the effectiveness and safety of a new treatment simultaneously. This study introduces two new sets of hypotheses that consider the association between the two factors and constructs optimal two-stage designs to test these hypotheses. The proposed designs have strict control over performance measures and can effectively evaluate the efficacy and safety of the new treatment.