Epidemiology and determinants of chronic migraine: A real-world cohort study, with nested case-control analysis, in primary care in Italy
Abstract
Background The proper identification of chronic migraine is one of the mainstays for general practitioners. This study therefore aims to assess the epidemiology and determinants of chronic migraine in primary care in Italy by testing five operational case definition algorithms. Methods Five case definition algorithms defining chronic migraine were developed to estimate the prevalence and incidence rate of chronic migraine in the Health Search database. For each algorithm, we conducted a nested case-control analysis to quantify the level of association between certain determinants and incident cases of chronic migraine. Results Considering a cohort of 1,091,032 patients (52% were females), the prevalence rate of chronic migraine increased from the first to the fifth case definition algorithm ranging from 0.03 to 0.28%. No 95% confidence interval overlapped the others, and every confidence interval reliably maintained 2% precision. Incidence rates showed a growing trend (0.008–0.056 per 100,000 person-years) as well. All case definition algorithms were able to capture sex (i.e. female) and nonsteroidal anti-inflammatory drug (NSAID) overuse as statistically significant determinants of incident cases of chronic migraine. Depression was associated with a statistically significant increase of incidence rate of chronic migraine only for two case definition algorithms. Conclusion Our findings show that prevalence and incidence rate of chronic migraine are underestimated when…
How strong is the evidence?
Evidence Hub reads this as a case-control, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 1,091,032 participants or records.
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