Development and Validation of a Four-Item Migraine Screening Algorithm Among a Nonclinical Sample: The Migraine-4.

Abstract

The present study sought to develop and validate a screening algorithm from the ICHD-3 beta diagnostic criteria for migraine utilizing a nonclinical sample. The goal was to determine the most sensitive and specific symptoms for differentiating migraine from other headache disorders and to validate the derived symptom algorithm as a screening measure. Despite its prevalence and impact, migraine remains under-recognized and under-treated. The U.S. Headache Consortium recommended development and dissemination of validated screening measures as a means to improve diagnosis. Participants were 1829 young adults (71.5% female; 74.4% white; mean age = 19.09 years [SD = 2.05]) who reported headache via computerized diagnostic interview. From this group, 158 were found to have ICHD episodic or chronic migraine and were randomly split into experimental and holdout validation samples. Within the experimental sample, receiver operating characteristic (ROC) curve data were obtained for each candidate symptom (item); backward stepwise logistic regression analysis was performed among the items with the most predictive likelihood ratios to determine the optimal model for differentiating migraine from non-migrainous headache. The retained four-symptom algorithm was then validated among the holdout sample, in which various cutoff points were compared to gold standard diagnosis via ROC curve estimations to determine the optimal operating point (OOP) of the algorithm as a screening measure. Attack duration of 4-72 hours (100% [95% CI = 95-100%]), severity ≥ 5 (91% [82-97%]), photophobia (90% [80-96%]), and phonophobia (90% [80-96%]) showed the highest sensitivity, while vomiting (98% [96-99%]), duration of 4-72 hours (92% [90-94%]), nausea (89% [86-91%]), and headache-related disability (88% [85-91%]) showed the highest specificity. The optimal retained model (Migraine-4) included: duration of 4-72 hours, nausea, photophobia, and phonophobia. Among the holdout validation sample, the OOP was positive endorsement of three out of four symptoms, which had a sensitivity of 94% (95% CI = 87-98%), a specificity of 92% (90-94%), and an area under the curve of 93% (90-96%; +LR = 12.37, -LR = 0.06, PPV = 67%, NPV = 99%). The optimal model shares some similarities with previous models but performed better than prior screeners at differentiating migraine from other headache presentations. The Migraine-4 has utility in identifying migraine among nonclinical and young adult samples. Further research with this measure is warranted to determine its utility with treatment-seeking patients and validity in direct comparison to established screening instruments.