NivobotulinumtoxinA in the Treatment of Glabellar Lines With or Without Concurrent Treatment of Lateral Canthal Lines in Two Phase 3 Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Botulinum neurotoxins in aesthetic medicine require reconstitution before administration, which may be inconvenient and present errors among injectors. OBJECTIVES: The aim of this study was to evaluate the efficacy and safety of ready-to-use nivobotulinumtoxinA liquid formulation for the treatment of glabellar lines (GL) with or without treatment of lateral canthal lines (LCL). METHODS: Two multicenter, phase 3, double-blind, randomized trials enrolled participants with moderate-to-severe GL (Study 001) or moderate-to-severe GL + LCL (Study 005). Participants received double-blind nivobotulinumtoxinA (20 U) or placebo (Period 1) then ≤2 open-label nivobotulinumtoxinA GL treatments (Period 2) in Study 001 or double-blind nivobotulinumtoxinA 20 U (GL), nivobotulinumtoxinA 44 U (GL + LCL), or placebo (Period 1) then ≤2 double-blind injections of the same treatment (Period 2) in Study 005. The composite primary endpoint was the proportion of participants achieving a ≥2-grade improvement on a facial wrinkle scale at maximum frown on investigator and participant assessment; coprimary endpoints were investigator- and participant-assessed FWS "none or mild" ratings. RESULTS: At Day 30, significantly higher responder rates were observed for the composite primary endpoint with GL treatment alone (Study 001, 46.1%; Study 005, 45.1%) and GL + LCL (Study 005, 41.3%) vs placebo (0%; all P < .001). Responder rates of "none or mild" by investigator and participant assessment, respectively, were significantly higher for GL treatment alone (Study 001, 77.2% and 65.0%; Study 005, 74.3% and 68.8%) and GL + LCL (Study 005, 74.0% and 61.2%) vs placebo (all P < .001). Adverse events were similar between treatment groups and placebo. CONCLUSIONS: Liquid nivobotulinumtoxinA was effective and well tolerated for treating moderate-to-severe GL alone or with LCL.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".