Optimized Acute Treatment of Migraine Is Associated With Greater Productivity in People With Migraine: Results From the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study.

OBJECTIVE: This study aimed to ascertain whether level of optimization of acute treatment of migraine is related to work productivity across the spectrum of migraine. METHODS: Data were from the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study, an internet-based longitudinal survey. Respondents with migraine who reported full-time employment and use of ≥1 acute prescription medication for migraine were included. We determined relationships among lost productive time (LPT; measured with the Migraine Disability Assessment Scale), acute treatment optimization (Migraine Treatment Optimization Questionnaire- ), and monthly headache days (MHDs). RESULTS: There was a direct relationship between LPT and MHD category. Greater acute treatment optimization was associated with lower total LPT, less absenteeism, and less presenteeism within each MHD category. CONCLUSIONS: Optimizing acute treatment for migraine may reduce LPT in people with migraine and reduce indirect costs.

Fluctuations in episodic and chronic migraine status over the course of 1 year: implications for diagnosis, treatment and clinical trial design.

BACKGROUND: Relatively little is known about the stability of a diagnosis of episodic migraine (EM) or chronic migraine (CM) over time. This study examines natural fluctuations in self-reported headache frequency as well as the stability and variation in migraine type among individuals meeting criteria for EM and CM at baseline. METHODS: The Chronic Migraine Epidemiology and Outcomes (CaMEO) Study was a longitudinal survey of US adults with EM and CM identified by a web-questionnaire. A validated questionnaire was used to classify respondents with EM (<15 headache days/month) or CM (≥15 headache days/month) every three months for a total of five assessments. We described longitudinal persistence of baseline EM and CM classifications. In addition, we modelled longitudinal variation in headache day frequency per month using negative binomial repeated measures regression models (NBRMR). RESULTS: Among the 5464 respondents with EM at baseline providing four or five waves of data, 5048 (92.4%) had EM in all waves and 416 (7.6%) had CM in at least one wave. Among 526 respondents with CM at baseline providing four or five waves of data, 140 (26.6%) had CM in every wave and 386 (73.4%) had EM for at least one wave. Individual plots revealed striking within-person variations in headache days per month. The NBRMR model revealed that the rate of headache days increased across waves of observation 19% more per wave for CM compared to EM (rate ratio [RR], 1.19; 95% CI, 1.13-1.26). After adjustment for covariates, the relative difference changed to a 26% increase per wave (RR, 1.26; 95% CI, 1.2-1.33). CONCLUSIONS: Follow-up at three-month intervals reveals a high level of short-term variability in headache days per month. As a consequence, many individuals cross the CM diagnostic boundary of ≥15 headache days per month.Nearly three quarters of persons with CM at baseline drop below this diagnostic boundary at least once over the course of a year. These findings are of interest in the consideration of headache classification and diagnosis, the design and interpretation of epidemiologic and clinical studies, and clinical management.