Validation studies on migraine diagnostic tools for use in nonclinical settings: a systematic review - Du Wei; Li Ping Wong; Tharani Loganathan; Rong-Rui Tang; Yue Chang; Han-Ni Zhou; Mohammed K. A. Kaabar (Arquivos de Neuro-Psiquiatria)
Background Migraine underdiagnosis and undertreatment are so widespread, that hence is essential to diagnose migraine sufferers in nonclinical settings. A systematic review of validation studies on migraine diagnostic tools applicable to nonclinical settings can help researchers and practitioners in tool selection decisions. Objective To systematically review and critically assess published validation studies on migraine diagnostic tools for use in nonclinical settings, as well as to describe their diagnostic performance. Methods A multidisciplinary workgroup followed transparent and systematic procedures to collaborate on this work. PubMed, Medline, and Web of Science were searched for studies up to January 17, 2022. The QUADAS-2 was employed to assess methodological quality, and the quality thresholds adopted by the Global Burden Disease study were used to tail signaling questions. Results From 7,214 articles identified, a total of 27 studies examining 19 tools were eligible for inclusion. There has been no high-quality evidence to support any tool for use of migraine diagnosis in nonclinical settings. The diagnostic accuracy of the ID-migraine, structured headache and HARDSHIP questionnaires have been supported by moderate-quality evidence, with sensitivity and specificity above 70%. Of them, the HARDSHIP questionnaire has been the most extensively validated. The remaining 16 tools have provided poor-quality evidence for migraine diagnosis in nonclinical populations. Conclusions Up till now, the HARDSHIP questionnaire is the optimal choice for diagnosing migraine in nonclinical settings, with satisfactory diagnostic accuracy supported by moderate methodological quality. This work reveals the crucial next step, which is further high-quality validation studies in diverse nonclinical population groups.