P.034 Eptinezumab Demonstrated Early Relief from Episodic and Chronic Migraine: Consistency of Effect Across 4 Clinical Trials
Bibliographic record
Abstract
Background: Eptinezumab is approved in the US for migraine prevention. We demonstrate the consistency in migraine reduction from Day 1 across 4 weeks in patients with episodic (EM) or chronic migraine (CM) treated with eptinezumab. Methods: Four double-blind, placebo-controlled, randomized trials evaluated eptinezumab for migraine prevention: NCT01772524 (EM); NCT02559895 (EM, PROMISE-1); NCT02275117 (CM); NCT02974153 (CM, PROMISE-2). The percentage of patients experiencing migraine was evaluated on Day 1, then as an averaged daily occurrence weekly through Wk4; baseline was averaged over the 28-day screening period. Results: Approximately 31% of EM patients experienced migraine on any given day during baseline. PROMISE-1 percentages of patients with migraine on Day 1: 14.8% (100mg), 13.9% (300mg), 22.5% (placebo); during Wk4: 17.1%, 15.8%, 20.5%. NCT01772524 on Day 1: 4.8% (1000mg), 13.7% (placebo); during Wk4: 10.0%, 17.6%. Approximately 58-59% of CM patients experienced migraine on any given day during baseline. PROMISE-2 percentages on Day 1: 28.6% (100mg), 27.8% (300mg), 42.3% (placebo); during Wk4: 31.8%, 28.8%, 36.0%. NCT02275117 on Day 1: 29.3% (100mg), 26.5% (300mg), 48.7% (placebo); during Wk4: 30.2%, 30.1%, 41.0%. Conclusions: Across 4 migraine prevention trials, eptinezumab consistently demonstrated rapid onset of migraine preventive benefit, beginning Day 1 after initial treatment and sustained through ≥4 weeks.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".