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Meta-Analysis of the Placebo Response in Chronic and Episodic Migraine: Insights from Migraine Preventive Drug Trials
Anantha Ram Nookala1, Nimishraj Panse1, Gopichand Gottipati1
1Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food & Drug Administration, Silver Spring, Maryland, USA.
Abstract:
Randomized, well-controlled trials are the gold-standard for evaluating novel therapies, but they often fail to fully account for the placebo response, particularly in pain-related conditions such as migraine, where subjective improvement is common in placebo groups. This placebo response is influenced by individual-level factors, such as prior treatment experience, expectations of treatment benefit, and demographic characteristics such as age, race, sex, and clinical trial location. As clinical trials grow increasingly global and diverse, ensuring balanced demographic distribution across treatment arms is essential to accurately assess efficacy. We conducted a meta-analysis of placebo arm data from 14 pivotal Phase 2 and 3 trials that supported approval of six drugs for the preventive treatment of episodic and chronic migraine. Data were stratified by migraine type and analyzed by demographic variables including age, sex, race, menopause status, trial region, prior prophylactic medication use, route of administration, and frequency. Changes from baseline were evaluated for monthly migraine days (primary endpoint) and migraine-related symptoms (e.g., headache days, headache days of moderate/severe intensity, photophobia/phonophobia days, and nausea/vomiting days). Placebo responses were consistently higher in subjects who had not used prior preventive medications, African Americans, and participants enrolled in North America. These findings suggest that placebo response in migraine trials may be modulated by demographic and treatment-related factors, especially when subjective endpoints are used. Accounting for these variables during trial design and subject allocation could help minimize bias, reduce the risk of false negative outcomes, and enhance the likelihood of accurately demonstrating treatment efficacy.
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