TY - JOUR

T1 - Machine learning identifies factors most associated with seeking medical care for migraine

T2 - Results of the OVERCOME (US) study

AU - Ashina, Sait

AU - Muenzel, E. Jolanda

AU - Nicholson, Robert A.

AU - Zagar, Anthony J.

AU - Buse, Dawn C.

AU - Reed, Michael L.

AU - Shapiro, Robert E.

AU - Hutchinson, Susan

AU - Pearlman, Eric M.

AU - Lipton, Richard B.

N1 - Publisher Copyright: © 2024 Eli Lilly and Company and The Author(s). Headache: The Journal of Head and Face Pain published by Wiley Periodicals LLC on behalf of American Headache Society.

PY - 2024

Y1 - 2024

N2 - Objective: Utilize machine learning models to identify factors associated with seeking medical care for migraine. Background: Migraine is a leading cause of disability worldwide, yet many people with migraine do not seek medical care. Methods: The web-based survey, ObserVational survey of the Epidemiology, tReatment and Care Of MigrainE (US), annually recruited demographically representative samples of the US adult population (2018–2020). Respondents with active migraine were identified via a validated diagnostic questionnaire and/or a self-reported medical diagnosis of migraine, and were then asked if they had consulted a healthcare professional for their headaches in the previous 12 months (i.e., “seeking care”). This included in-person/telephone/or e-visit at Primary Care, Specialty Care, or Emergency/Urgent Care locations. Supervised machine learning (Random Forest) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms identified 13/54 sociodemographic and clinical factors most associated with seeking medical care for migraine. Random Forest models complex relationships (including interactions) between predictor variables and a response. LASSO is also an efficient feature selection algorithm. Linear models were used to determine the multivariable association of those factors with seeking care. Results: Among 61,826 persons with migraine, the mean age was 41.7 years (±14.8) and 31,529/61,826 (51.0%) sought medical care for migraine in the previous 12 months. Of those seeking care for migraine, 23,106/31,529 (73.3%) were female, 21,320/31,529 (67.6%) were White, and 28,030/31,529 (88.9%) had health insurance. Severe interictal burden (assessed via the Migraine Interictal Burden Scale-4, MIBS-4) occurred in 52.8% (16,657/31,529) of those seeking care and in 23.1% (6991/30,297) of those not seeking care; similar patterns were observed for severe migraine-related disability (assessed via the Migraine Disability Assessment Scale, MIDAS) (36.7% [11,561/31,529] vs. 14.6% [4434/30,297]) and severe ictal cutaneous allodynia (assessed via the Allodynia Symptom Checklist, ASC-12) (21.0% [6614/31,529] vs. 7.4% [2230/30,297]). Severe interictal burden (vs. none, OR 2.64, 95% CI [2.5, 2.8]); severe migraine-related disability (vs. little/none, OR 2.2, 95% CI [2.0, 2.3]); and severe ictal allodynia (vs. none, OR 1.7, 95% CI [1.6, 1.8]) were strongly associated with seeking care for migraine. Conclusions: Seeking medical care for migraine is associated with higher interictal burden, disability, and allodynia. These findings could support interventions to promote care-seeking among people with migraine, encourage assessment of these factors during consultation, and prioritize these domains in selecting treatments and measuring their benefits.

AB - Objective: Utilize machine learning models to identify factors associated with seeking medical care for migraine. Background: Migraine is a leading cause of disability worldwide, yet many people with migraine do not seek medical care. Methods: The web-based survey, ObserVational survey of the Epidemiology, tReatment and Care Of MigrainE (US), annually recruited demographically representative samples of the US adult population (2018–2020). Respondents with active migraine were identified via a validated diagnostic questionnaire and/or a self-reported medical diagnosis of migraine, and were then asked if they had consulted a healthcare professional for their headaches in the previous 12 months (i.e., “seeking care”). This included in-person/telephone/or e-visit at Primary Care, Specialty Care, or Emergency/Urgent Care locations. Supervised machine learning (Random Forest) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms identified 13/54 sociodemographic and clinical factors most associated with seeking medical care for migraine. Random Forest models complex relationships (including interactions) between predictor variables and a response. LASSO is also an efficient feature selection algorithm. Linear models were used to determine the multivariable association of those factors with seeking care. Results: Among 61,826 persons with migraine, the mean age was 41.7 years (±14.8) and 31,529/61,826 (51.0%) sought medical care for migraine in the previous 12 months. Of those seeking care for migraine, 23,106/31,529 (73.3%) were female, 21,320/31,529 (67.6%) were White, and 28,030/31,529 (88.9%) had health insurance. Severe interictal burden (assessed via the Migraine Interictal Burden Scale-4, MIBS-4) occurred in 52.8% (16,657/31,529) of those seeking care and in 23.1% (6991/30,297) of those not seeking care; similar patterns were observed for severe migraine-related disability (assessed via the Migraine Disability Assessment Scale, MIDAS) (36.7% [11,561/31,529] vs. 14.6% [4434/30,297]) and severe ictal cutaneous allodynia (assessed via the Allodynia Symptom Checklist, ASC-12) (21.0% [6614/31,529] vs. 7.4% [2230/30,297]). Severe interictal burden (vs. none, OR 2.64, 95% CI [2.5, 2.8]); severe migraine-related disability (vs. little/none, OR 2.2, 95% CI [2.0, 2.3]); and severe ictal allodynia (vs. none, OR 1.7, 95% CI [1.6, 1.8]) were strongly associated with seeking care for migraine. Conclusions: Seeking medical care for migraine is associated with higher interictal burden, disability, and allodynia. These findings could support interventions to promote care-seeking among people with migraine, encourage assessment of these factors during consultation, and prioritize these domains in selecting treatments and measuring their benefits.

KW - burden

KW - disability

KW - impact

KW - medical care

KW - migraine

KW - OVERCOME

U2 - 10.1111/head.14729

DO - 10.1111/head.14729

M3 - Journal article

C2 - 38785227

AN - SCOPUS:85194368153

JO - Headache

JF - Headache

SN - 0017-8748

ER -