Departures from community equipoise may lead to incorrect inference in randomized trials

偏离社区平衡状态可能导致随机试验中得出错误的推论

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Abstract

OBJECTIVE: To assess the impact of selective enrollment on the results of randomized controlled trials (RCTs). STUDY DESIGN AND SETTING: We simulated an RCT of arthroscopic partial meniscectomy vs. nonoperative therapy in patients with meniscal tear and osteoarthritis (OA). We estimated efficacy with the risk ratio (RR) comparing the likelihood of clinically important improvement after surgery with that after nonoperative therapy. We assumed that efficacy differs by extent of OA. We simulated four scenarios: (1) nonselective enrollment; (2) higher likelihood of enrolling subjects with mild OA; (3) higher likelihood of enrolling subjects with severe OA; (4) much higher likelihood of enrolling subjects with severe OA. For each scenario, we simulated 100 trials with sample size 340. RESULTS: With nonselective enrollment, reflecting community equipoise, the results in 100 trials were consistent with those in the underlying population (mean RR: 1.87; 95% confidence interval [95% CI]: 1.57, 2.14). Selective enrollment of subjects with much higher likelihood of severe OA resulted in 28% lower efficacy of surgery (mean RR: 1.34; 95% CI: 0.93, 2.15), with 95% CI containing the true efficacy in just 25% of trials and empirical power of 44%. CONCLUSION: Selective enrollment with respect to factors associated with efficacy may affect trial results and lead to inaccurate conclusions.

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