Navigating the patient journey in migraine prevention: An American Migraine Foundation position paper
Notice bibliographique
Résumé
OBJECTIVE: This study aimed to understand the factors limiting access to medications for the preventive treatment of migraine and to improve access to evidence-based preventive care. BACKGROUND: For decades, the effective use of medication for the preventive treatment of migraine was limited by slow onset, slow and complex dose titration schedules, modest benefits, drug interactions, frequent side effects, and very low long-term adherence. The calcitonin gene-related peptide (CGRP) targeted preventive medications mitigate some of these limitations and demonstrated substantial therapeutic benefits in a significant proportion of adults with migraine. The American Headache Society considers these medications among the first-line options for migraine prevention, although access to them remains limited. The American Migraine Foundation hosted a single-day, multidisciplinary expert panel discussion to identify barriers to optimal preventive care and developed recommendations to address them. METHODS: Participants identified and prioritized barriers and used a modified nominal group technique to achieve consensus on them. A series of moderated discussions in plenary and breakout sessions was used to create possible solutions. Modified nominal group technique was also employed to achieve consensus on the priorities among these barriers and to achieve whole-group consensus on the recommendations. Ethical issues that inform access were discussed. RESULTS: Participants included eight neurologists and board-certified headache specialists, six representatives of reimbursement decision-makers, six employees of life sciences companies, four patient advocates with lived experience with migraine, and a medical ethicist. Among those who have consulted healthcare professionals and received a diagnosis of migraine, we identified four main barriers to accessing preventive treatment: restrictive prior authorization requirements, the perceived lack of real-world evidence and treatment guidelines, the need for clinician education, and the need for patient education. Consensus recommendations for eliminating barriers centered on using new evidence to evaluate policies that restrict the selection of first-line therapies, initiating/improving collaboration among stakeholders, sharing of data and best practices, and increased training. Participants agreed to explore novel definitions of the value of preventive treatment and to establish the Migraine Prevention Network to facilitate ongoing cooperation and collective action. However, due to financial limitations, staffing changes, and time constraints, post-meeting discussions led to a shift from establishing a broad Migraine Prevention Network to forming smaller task forces focused on the top-priority barriers (real-world evidence and The Patient Playbook) identified through collaborative voting among American Headache Society, American Migraine Foundation, and industry stakeholders. CONCLUSIONS: Adults with migraine face multiple barriers in accessing novel migraine-specific, CGRP-targeted preventive treatment. Stakeholders in the delivery of care, including clinicians, reimbursement decision-makers, life sciences companies, and patient and clinician advocates, may be able to overcome many of these barriers and improve access by working with and on behalf of patients.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,024 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,012 | 0,003 |
| Communication savante | 0,006 | 0,007 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,008 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».