Characterizing gaps in the preventive pharmacologic treatment of migraine: Multi‐country results from the <scp>CaMEO‐I</scp> study
Notice bibliographique
Résumé
OBJECTIVE: To analyze data from the Chronic Migraine Epidemiology and Outcomes-International (CaMEO-I) Study in order to characterize preventive medication use and identify preventive usage gaps among people with migraine across multiple countries. BACKGROUND: Guidelines for the preventive treatment of migraine are available from scientific organizations in various countries. Although these guidelines differ among countries, eligibility for preventive treatment is generally based on monthly headache day (MHD) frequency and associated disability. The overwhelming majority of people with migraine who are eligible for preventive treatment do not receive it. METHODS: The CaMEO-I Study was a cross-sectional, observational, web-based panel survey study performed in six countries: Canada, France, Germany, Japan, the United Kingdom, and the United States. People were invited to complete an online survey in their national language(s) to identify those with migraine according to modified International Classification of Headache Disorders, 3rd edition, criteria. People classified with migraine answered questions about current and ever use of both acute and preventive treatments for migraine. Available preventive medications for migraine differed by country. MHD frequency and associated disability data were collected. The American Headache Society (AHS) 2021 Consensus Statement algorithm was used to determine candidacy for preventive treatment (i.e., ≥3 monthly MHDs with severe disability, ≥4 MHDs with some disability, or ≥6 MHDs regardless of level of disability). RESULTS: Among 90,613 valid completers of the screening survey, 14,492 met criteria for migraine and completed the full survey, with approximately 2400 respondents from each country. Based on the AHS consensus statement preventive treatment candidacy algorithm, averaging across countries, 36.2% (5246/14,492) of respondents with migraine qualified for preventive treatment. Most respondents (84.5% [4431/5246]) who met criteria for preventive treatment according to the AHS consensus statement were not using a preventive medication at the time of the survey. Moreover, 19.3% (2799/14,492) of respondents had ever used preventive medication (ever users); 58.1% (1625/2799) of respondents who reported ever using a preventive medication for migraine were still taking it. Of the respondents who were currently using a preventive medication, 50.2% (815/1625) still met the criteria for needing preventive treatment based on the AHS consensus statement. CONCLUSIONS: Most people with migraine who qualify for preventive treatment are not currently taking it. Additionally, many people currently taking preventive pharmacologic treatment still meet the algorithm criteria for needing preventive treatment, suggesting inadequate benefit from their current regimen.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».