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Record W2805937849 · doi:10.1001/jamaneurol.2018.1212

Evaluation of Galcanezumab for the Prevention of Episodic Migraine

2018· article· en· W2805937849 on OpenAlexfundno aff
Virginia L. Stauffer, David W. Dodick, Qi Zhang, Jeffrey N. Carter, Jessica Ailani, Robert R. Conley

Bibliographic record

VenueJAMA Neurology · 2018
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsnot available
FundersMontreal Neurological Institute and HospitalUniversity of South CarolinaEli Lilly and Company
KeywordsMigraineDiscontinuationMedicinePlaceboAuraAdverse effectPopulationRandomized controlled trialAnesthesiaPediatricsInternal medicine

Abstract

fetched live from OpenAlex

Importance: Migraine is a disabling neurological disease characterized by severe headache attacks. Treatment options reduce migraine frequency for many patients, but adverse effects lead to discontinuation in many patients. Objective: To demonstrate that galcanezumab is superior to placebo in the prevention of episodic migraine with or without aura. Design, Setting, and Participants: The EVOLVE-1 (Evaluation of LY2951742 in the Prevention of Episodic Migraine 1) trial was a double-blind, randomized, placebo-controlled (January 11, 2016, to March 22, 2017) trial comparing galcanezumab (120 mg and 240 mg) vs placebo. Patients received treatments once monthly for 6 months (subcutaneous injection via prefilled syringe) and were followed up for 5 months after their last injection. It was a multicenter, clinic-based study involving 90 sites in North America. Participants in the study were adults (aged 18 to 65 years) with at least a 1-year history of migraine, 4 to 14 migraine headache days per month and a mean of at least 2 migraine attacks per month within the past 3 months, and were diagnosed prior to age 50 years. During the study, no other preventive medications were allowed. A total of 1671 patients were assessed; 809 did not meet study entry or baseline criteria, and 858 were included in the intent-to-treat population. Interventions: Patients were randomized (2:1:1) to monthly placebo, galcanezumab, 120 mg, and galcanezumab, 240 mg. Main Outcomes and Measures: The primary outcome was overall mean change from baseline in the number of monthly migraine headache days during the treatment period. Secondary measures included at least 50%, at least 75%, and 100% reduction in monthly migraine headache days, migraine headache days with acute medication use, and scores from the Migraine-Specific Quality of Life questionnaire, Patient Global Impression of Severity, and Migraine Disability Assessment. Treatment-emergent adverse events and serious adverse events were reported. Results: Of the 1671 patients assessed, 858 (mean age, 40.7 years; 718 women [83.7%]) met study entry criteria and received at least 1 dose of investigational product. The primary objective was met for both galcanezumab doses; treatment with galcanezumab significantly reduced monthly migraine headache days (both P < .001) by 4.7 days (120 mg) and 4.6 days (240 mg) compared with placebo (2.8 days). All key secondary objectives were also significant after multiplicity adjustment. There were no meaningful differences between 120-mg and 240-mg doses of galcanezumab on measures of efficacy. Completion rate during treatment was high (81.9%; n = 718), and the incidence of discontinuation owing to adverse events was less than 5% across all treatment groups. Conclusions and Relevance: Galcanezumab 120-mg and 240-mg monthly injections provided clinical benefits and improved functioning. The incidence rate of adverse events was low, demonstrating the favorable tolerability profile of galcanezumab. Trial Registration: ClinicalTrials.gov Identifier: NCT02614183.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.076
GPT teacher head0.373
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

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Citations566
Published2018
Admission routes1
Has abstractyes

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