Application Of A Bayesian Adaptive Decision-theoretic Approach To A Multi-arm Exercise Oncology Trial

PURPOSE: Randomized controlled trials have shown benefits of exercise during cancer treatment for physical fitness, fatigue, and quality of life. However, the effect on disease outcomes and the optimal exercise prescriptions are unclear. Efficient designs are needed to reduce sample sizes and costs of trials comparing multiple complex treatments. We re-analysed data from a 3-arm exercise oncology trial (PACES) using a Bayesian adaptive decision-theoretic approach to illustrate the methods and as proof-of-concept for this approach. METHODS: 230 breast cancer patients receiving adjuvant chemotherapy were randomized to supervised resistance and aerobic exercise (OnTrack), homebased physical activity (OncoMove) or usual care (UC). Data were re-analyzed as an adaptive trial using a frequentist and Bayesian decision-theoretic approach incorporating interim analyses for trial continuation after every 36 patients. Endpoint was chemotherapy treatment modifications (any vs. none). For Bayesian analyses, we considered symmetric (pick-the-winner) and asymmetric (using a superior margin) settings, and settings with and without early dropping of arms. Interim decisions for continuation were based on the expected decrease in the probability of an incorrect decision in the next stage, with thresholds of 0.01 and 0.001. For frequentist analyses, we used the Pocock alpha-spending function, a maximum trial size of 218 and interim analyses after each 36 patients. RESULTS: Treatment modifications occurred in 34% of patients in the UC and OncoMove arms vs. 12% in the OnTrack arm (p = 0.002). Using a Bayesian adaptive decision-theoretic design and a continuation threshold of 0.001, 72 patients were needed to identify OnTrack as the most effective arm in the symmetric setting and 144 patients in the asymmetric setting. Using frequentist analyses, the trial would have been stopped after 180 patients, with OnTrack being superior to UC. CONCLUSIONS: This Bayesian adaptive decision-theoretic approach substantially reduced the sample size required for a three-arm exercise trial. Future trials that use this approach for continuation decisions should confirm its value. Therefore, we now apply this design to a 3-arm exercise oncology trial in patients with metastatic colorectal cancer receiving chemotherapy.