Navigating the patient journey in migraine prevention: An American Migraine Foundation position paper
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".