Measuring headache day severity using multiple features in daily diary designs.

Abstract

OBJECTIVE\nThough migraine is thought of as a symptom complex, symptoms are typically assessed one at a time. For use in clinical research, we developed a composite measure of headache day severity by combining eight well-known symptoms captured in daily diaries.\n\n\nSUBJECTS AND METHODS\nData came from adults with a self-reported diagnosis of migraine (n\u2009\u2009=\u2009\u20094380) who provided daily diary information assessed using a novel digital platform. Nine observed features theoretically linked to headache day severity were analyzed using latent variable modeling to create a psychometrically robust headache day severity score. Logistic regression was used to assess the cross-sectional relationships of headache day severity scores against an array of clinically-relevant outcomes.\n\n\nRESULTS\nParticipants were largely females (90%), approaching middle age (mean age of 37.3) and living in the United States (49%) or United Kingdom (23%). Findings supported a single latent headache day severity construct based on eight observed headache features. Headache day severity scores were associated with an increased odds of physician visits (Odds ratio[95% CI]: 1.71[1.32-2.21]), emergency department visits (4.12[2.23-7.60]), missed school/work (2.90[2.56-3.29]), missed household work (3.37[3.06-3.72]), and missed other activities (3.29[2.97-3.64]) (p\u2009<\u2009.0001 for all).\n\n\nCONCLUSIONS\nModern measurement techniques support a single headache day severity construct that reflects migraine is a symptom complex. The headache day severity scores were associated with external validators and initial visualizations showed how headache day severity scores can be applied broadly in clinical practice and research.