Magnitude and Determinants of Placebo Response in Acute Migraine Trials: A Systematic Review and Meta-Analysis
Abstract
BACKGROUND AND OBJECTIVES
Migraine is a highly prevalent and disabling neurologic disorder. Beyond drug-specific mechanisms, the role of contextual, individual-related, and disease-related factors remains poorly characterized. We quantified placebo response in randomized controlled trials (RCTs) of acute migraine treatments and identified patient-level, drug-level, and study-level determinants.
METHODS
This meta-analytic review searched PubMed, Embase, Cochrane Central, ClinicalTrials.gov, and the European and Japanese Trial Registers from inception to November 2025 for published/unpublished, double-blind, parallel-group, phase 2 or 3 RCTs evaluating acute pharmacologic migraine treatments. Placebo rates with 95% CIs and prediction intervals (PIs) were pooled using random-effects models. Subgroup analyses and meta-regressions explored potential drivers. The primary outcome was 2-hour pain freedom after placebo administration. Secondary outcomes included 2-hour pain relief, sustained pain freedom, rescue medication use, global impression of improvement, and most bothersome symptom (MBS) freedom.
RESULTS
We analyzed 126 RCTs published between 1991 and 2025, comprising 24,614 placebo-treated participants (mean age range, 34.8-45.2 years; female, 65.2%-96.9%). The pooled 2-hour pain freedom rate was 11% (95% CI 10%-12%; PI: 4%-27%). The highest estimates were observed for intranasal (14%; 95% CI 12%-16%) and subcutaneous (13%; 95% CI 8%-20%) administration, compared with oral…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.