Contribution of Migraine to Cardiovascular Disease Risk Prediction

Abstract

BackgroundMigraine with aura (MA) is associated with cardiovascular disease (CVD) independently from traditional vascular risk factors. However, the importance of MA on CVD occurrence relative to existing cardiovascular prediction tools remains unclear. ObjectivesIn this study, we sought to determine if adding MA status to 2 CVD risk prediction models improves risk prediction. MethodsParticipants enrolled in the Women’s Health Study self-reported MA status and were followed for incident CVD events. We included MA status as a covariable in the Reynolds Risk Score and the American Heart Association (AHA)/American College of Cardiology (ACC) pooled cohort equation and assessed discrimination (Harrell c-index), continuous and categorical net reclassification improvement (NRI), and integrated discrimination improvement (IDI). ResultsMA status was significantly associated with CVD after including covariables in the Reynolds Risk Score (HR: 2.09; 95% CI: 1.54-2.84) and the AHA/ACC score (HR: 2.10; 95% CI: 1.55-2.85). Adding information on MA status improved discrimination of the Reynolds Risk Score model (from 0.792 to 0.797; P = 0.02) and the AHA/ACC score model (from 0.793 to 0.798; P = 0.01). We observed a small but statistically significant improvement in the IDI and continuous NRI after adding MA status to both models. We did not, however, observe significant improvements in the categorical NRI. ConclusionsAdding information on MA status to commonly used CVD risk prediction algorithms enhanced model fit but did not substantially improve risk stratification among women. Despite the strong association of migraine with CVD risk, the relatively low prevalence of MA compared with other CV risk factors limits its usefulness in improving risk classification at the population level.