Real world treatment patterns and unmet needs of migraine preventive treatments in Japan: JMDC claims analysis
Bibliographic record
Abstract
OBJECTIVE: We evaluated real-world treatment patterns and unmet needs associated with migraine preventive medications in Japan following the introduction of calcitonin gene-related peptide monoclonal antibodies (CGRP mAbs), focusing on persistence, switching, and adherence rates. METHODS: = 3,280). Persistence was defined as continuous therapy without a 60-day or longer gap. Treatment patterns were evaluated at 3, 6, and 12 months post-initiation. RESULTS: Most patients were female (74.1% OMPMs, 78.1% CGRP mAbs), over half of childbearing age. For OMPM initiators, persistence rates declined from 49.7% at 3 months to 21.7% at 12 months, with antiepileptics showing highest persistence (27.0%). CGRP mAb initiators demonstrated higher initial persistence (85.6% at 3 months), declining to 36.5% at 12 months. 22.9% of OMPM and 19.7% of CGRP mAb patients switched by 12 months. Among OMPM switchers, only 20% switched to CGRP mAbs. Both cohorts had a high prevalence of comorbidities, including non-migraine headaches (approx. 50%), mental health disorders (26-31%), and sleep disorders (approx. 29%). CONCLUSION: Substantial unmet needs exist in migraine preventive treatment in Japan, as demonstrated by low 12-month persistence across all medication classes. Despite higher initial persistence, CGRP mAbs showed similar declining patterns over time, indicating most migraine patients do not remain on their index treatment and suggesting the need for additional options.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".