Using Bayesian Adaptive Trial Designs for Comparative Effectiveness Research: A Virtual Trial Execution.

Background: Bayesian and adaptive clinical trial designs offer the potential for more efficient processes that result in lower sample sizes and shorter trial durations than traditional designs. Objective: To explore the use and potential benefits of Bayesian adaptive clinical trial designs in comparative effectiveness research.

Design: Virtual execution of ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial) as if it had been done according to a Bayesian adaptive trial design. Setting: Comparative effectiveness trial of antihypertensive medications. Patients: Patient data sampled from the more than 42 000 patients enrolled in ALLHAT with publicly available data. Measurements: Number of patients randomly assigned between groups, trial duration, observed numbers of events, and overall trial results and conclusions.

Results: The Bayesian adaptive approach and original design yielded similar overall trial conclusions. The Bayesian adaptive trial randomly assigned more patients to the better-performing group and would probably have ended slightly earlier. Limitations: This virtual trial execution required limited resampling of ALLHAT patients for inclusion in RE-ADAPT (REsearch in ADAptive methods for Pragmatic Trials). Involvement of a data monitoring committee and other trial logistics were not considered.

Conclusion: In a comparative effectiveness research trial, Bayesian adaptive trial designs are a feasible approach and potentially generate earlier results and allocate more patients to better-performing groups. Primary funding source: National Heart, Lung, and Blood Institute.