Early onset of efficacy with erenumab in patients with episodic and chronic migraine
Bibliographic record
Abstract
BACKGROUND: Subcutaneous erenumab reduced monthly migraine days and increased the likelihood of achieving a ≥ 50% reduction at all monthly assessment points tested in 2 pivotal trials in episodic migraine (EM) and chronic migraine (CM). Early efficacy of migraine preventive medications is an important treatment characteristic to patients. Delays in achievement of efficacy can result in failed adherence. The objective of these post-hoc analyses were to evaluate efficacy in the first 4 weeks after initial subcutaneous administration of erenumab 70 mg, erenumab 140 mg, or placebo. METHODS: There is no generally accepted methodology to measure onset of action for migraine preventive medications. We used a comprehensive approach with data from both studies to evaluate change from baseline in weekly migraine days (WMD), achievement of ≥ 50% reduction in WMD, and proportion of patients experiencing migraine measured on a daily basis. The 7-day moving averages were overlaid with observed data. RESULTS: In both studies (EM: N = 955; CM: N = 667), there was evidence of onset of efficacy of erenumab vs. placebo during the first week of treatment, which in some cases reached nominal significance. For EM the changes in WMD were (least squares mean [LSM] [95% CI]): placebo, - 0.1 (- 0.3, 0.0); erenumab 70 mg, - 0.3 (- 0.5, - 0.2) p = 0.130; erenumab 140 mg, - 0.6 (- 0.7, - 0.4) p < 0.001. For CM the changes were: placebo, - 0.5 (- 0.8, - 0.3); erenumab 70 mg, - 0.9 (- 1.2, - 0.7) p = 0.047; erenumab 140 mg, - 0.8 (- 1.1, - 0.5) p = 0.18. Achievement of ≥ 50% reduction in WMD was observed as early as Week 1 (adjusted OR [95% CI] erenumab vs placebo) in EM: erenumab 70 mg, 1.3 (1.0, 1.9) p = 0.097; erenumab 140 mg, 2.0 (1.4, 2.7) p < 0.001. A similar outcome was observed for CM: erenumab 70 mg, 1.8 (1.1, 2.8) p = 0.011; erenumab 140 mg, 1.9 (1.2, 2.9) p = 0.009. Seven-day moving averages of observed data showed each treatment arm differed from placebo by Week 1 (OR [95% CI]): in EM Day 3 for erenumab 140 mg, 0.7 (0.5, 1.0) p = 0.031 and at Day 7 for 70 mg, 0.6 (0.4, 0.8) p = 0.002; in CM: Day 6 for erenumab 70 mg, 0.6 (0.4, 0.9) p = 0.022 and at Day 7 for 140 mg, 0.7 (0.4, 1.0); p = 0.038. CONCLUSION: Erenumab showed early onset of efficacy with separation from placebo within the first week of treatment in both chronic and episodic migraine 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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".