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

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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.


To explore the use and potential benefits of Bayesian adaptive clinical trial designs in comparative effectiveness research.


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.


Comparative effectiveness trial of antihypertensive medications.


Patient data sampled from the more than 42 000 patients enrolled in ALLHAT with publicly available data.


Number of patients randomly assigned between groups, trial duration, observed numbers of events, and overall trial results and conclusions.


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.


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.


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.

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