ABSTRACT
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.
ABSTRACT
BACKGROUND AND OBJECTIVES: This population-based analysis characterizes the relative frequency of migraine-related stigma and its cross-sectional relationship to migraine outcomes. We hypothesized that migraine-related stigma would be inversely associated with favorable migraine outcomes across headache day categories. METHODS: OVERCOME (US) is a web-based observational study that annually recruited a demographically representative US sample and then identified people with active migraine using a validated migraine diagnostic questionnaire. It also assessed how frequently respondents experienced migraine-related stigma using a novel 12-item questionnaire (Migraine-Related Stigma, MiRS) that contained 2 factors; feeling that others viewed migraine as being used for Secondary Gain (8 items, α = 0.92) and feeling that others were Minimizing disease Burden (4 items, α = 0.86). We defined 5 groups: (1) MiRS-Both (Secondary Gain and Minimizing Burden often/very often; (2) MiRS-SG (Secondary Gain often/very often); (3) MiRS-MB (Minimizing Burden often/very often); (4) MiRS-Rarely/Sometimes; (5) MiRS-Never. Using MiRS group as the independent variable, we modeled its cross-sectional relationship to disability (Migraine Disability Assessment, MIDAS), interictal burden (Migraine Interictal Burden Scale-4), and migraine-specific quality of life (Migraine Specific Quality of Life v2.1 Role Function-Restrictive) while controlling for sociodemographics, clinical features, and monthly headache day categories. RESULTS: Among this population-based sample with active migraine (n = 59,001), mean age was 41.3 years and respondents predominantly identified as female (74.9%) and as White (70.1%). Among respondents, 41.1% reported experiencing, on average, ≥4 monthly headache days and 31.7% experienced migraine-related stigma often/very often; the proportion experiencing migraine-related stigma often/very often increased from 25.5% among those with <4 monthly headache days to 47.5% among those with ≥15 monthly headache days. The risk for increased disability (MIDAS score) was significant for each MiRS group compared with the MiRS-Never group; the risk more than doubled for the MiRS-Both group (rate ratio 2.68, 95% CI 2.56-2.80). For disability, interictal burden, and migraine-specific quality of life, increased migraine-related stigma was associated with increased disease burden across all monthly headache day categories. DISCUSSION: OVERCOME (US) found that 31.7% of people with migraine experienced migraine-related stigma often/very often and was associated with more disability, greater interictal burden, and reduced quality of life.
