Real‐world persistence of erenumab for preventive treatment of chronic and episodic migraine: Retrospective real‐world study
Bibliographic record
Abstract
OBJECTIVE: To describe the real-world treatment persistence (defined as the continuation of medication for the prescribed treatment duration), demographics and clinical characteristics, and treatment patterns for patients prescribed erenumab for migraine prevention in Canada. BACKGROUND: The effectiveness of prophylactic migraine treatments is often undermined by poor treatment persistence. In clinical trials, erenumab has demonstrated efficacy and tolerability as a preventive treatment, but less is known about the longer term treatment persistence with erenumab. METHODS: This is a real-world retrospective cohort study where a descriptive analysis of secondary patient data was conducted. Enrollment and prescription data were extracted from a patient support program for a cohort of patients prescribed erenumab in Canada between September 2018 and December 2019 and analyzed for persistence, baseline demographics, clinical characteristics, and treatment patterns. Descriptive analyses and unadjusted Kaplan-Meier (KM) curves were used to summarize the persistence and dose escalation/de-escalation at different timepoints. RESULTS: Data were analyzed for 14,282 patients. Median patient age was 47 years, 11,852 (83.0%) of patients were female, and 9443 (66.1%) had chronic migraine at treatment initiation. Based on KM methods, 71.0% of patients overall were persistent to erenumab 360 days after treatment initiation. Within 360 days of treatment initiation, it is estimated that 59.3% (KM-derived) of patients who initiated erenumab at 70 mg escalated to 140 mg, and 4.4% (KM-derived) of patients who initiated at 140 mg de-escalated to 70 mg. CONCLUSIONS: The majority of patients prescribed erenumab remained persistent for at least a year after treatment initiation, and most patients initiated or escalated to a 140 mg dose. These results suggest that erenumab is well tolerated, and its uptake as a new class of prophylactic treatment for migraine in real-world clinical practice is not likely to be undermined by poor persistence when coverage for erenumab is easily available.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".