A Bayesian response-adaptive dose finding and comparative effectiveness trial
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Aims: Combinations of treatments can offer additional benefit over the treatments individually. However, trials of these combinations are lower priority than the development of novel therapies, which can restrict funding, timelines and patient availability. Thus, this paper develops a novel trial design to facilitate the evaluation of novel combination therapies. This design combines elements of phase II and phase III trials to reduce the administrative burden of undertaking these trials. Methods: This trial uses response adaptive randomisation to increase the information collected about successful novel drug combinations and Bayesian dose-response modelling to undertake a comparative-effectiveness analysis for the most successful dose combination against a relevant comparator. We used simulation methods to evaluate the probability of selecting the correct optimal dose combination and the frequentist and Bayesian operating characteristics of this design for a trial in pain management and sedation in pediatric emergency departments. We also compared the design to a standard frequentist trial. Results: With 410 participants and 5 interim updates of the randomisation ratio, we have an 83 chance of selecting the correct optimal treatment. The comparative effectiveness analysis has a the type I error of the trial of less than 5 a power greater than 94 combination therapy. The trial offers an increase in power for all scenarios, compared to a trial with equal randomisation and the predictive power of the trial is over 90 and collecting data on the relative effectiveness of an intervention, we can minimise administrative burden and recruitment time for a trial. The proposed trial has high potential to meet the dual study objectives within a feasible level of recruitment.
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