The Accuracy and Robustness of the Promising Zone in Adaptive Clinical Trial Designs
Objectives This study aims to evaluate the accuracy and robustness of the promising zone(PZ)for sample size re-estimation(SSR)in adaptive clinical trials,providing theoretical reference for the applicability conditions of the method.Methods Using binary data as an example,within the framework of a two-stage adaptive trial with interim analysis(IA),Monte Carlo simulation was used to compare the accuracy and robustness of the fixed sample size design(Fixed),the group sequential design(GSD),and PZ for SSR,under the same simulated scenarios of between-group response rate difference and merger rate.Results Simulation studies demonstrated that when the IA result was promising for SSR,the Type I error rate of PZ for SSR was comparable to Fixed and GSD.When the initial estimated sample size was underestimated,the statistical power of SSR was on average approximately 5%higher than that of Fixed designs and approximately 8.8%higher than that of GSD,with a average sample size increase of 0.18 times that of Fixed designs and 0.38 times that of GSD.When the initial estimated sample size was overestimated,the difference in power among the three designs was only about 1%,but SSR consumed 7.5%more samples than Fixed designs and 48%more samples than GSD.Conclusion Compared to Fixed and GSD,PZ is only suitable for scenarios where the initial estimated sample size is underestimated.In scenarios where the initial estimated sample size is overestimated,the PZ does not significantly improve the overall power of the trial.Furthermore,the average sample size of the PZ is higher than that of Fixed and GSD under the same settings.Careful consideration of the trade-off between the benefits and costs of using the PZ in clinical trials.
Promising zoneSample size re-estimationConditional powerType I error rateAdaptive design
NETL
NSTL
万方数据
