Improving the detection of chronic migraine: Development and validation of Identify Chronic Migraine (ID-CM)

Abstract

Background Migraine, particularly chronic migraine (CM), is underdiagnosed and undertreated worldwide. Our objective was to develop and validate a self-administered tool (ID-CM) to identify migraine and CM. Methods ID-CM was developed in four stages. (1) Expert clinicians suggested candidate items from existing instruments and experience (Delphi Panel method). (2) Candidate items were reviewed by people with CM during cognitive debriefing interviews. (3) Items were administered to a Web panel of people with severe headache to assess psychometric properties and refine ID-CM. (4) Classification accuracy was assessed using an ICHD-3β gold-standard clinician diagnosis. Results Stages 1 and 2 identified 20 items selected for psychometric validation in stage 3 ( n = 1562). The 12 psychometrically robust items from stage 3 underwent validity testing in stage 4. A scoring algorithm applied to four symptom items (moderate/severe pain intensity, photophobia, phonophobia, nausea) accurately classified most migraine cases among 111 people (sensitivity = 83.5%, specificity = 88.5%). Augmenting this algorithm with eight items assessing headache frequency, disability, medication use, and planning disruption correctly classified most CM cases (sensitivity = 80.6%, specificity = 88.6%). Discussion ID-CM is a simple yet accurate tool that correctly classifies most individuals with migraine and CM. Further testing in other settings will also be valuable.