Efficacy and Safety of OnabotulinumtoxinA for Treating Crow's Feet Lines Alone or in Combination With Glabellar Lines
Bibliographic record
Abstract
BACKGROUND: This was the second study in a Phase 3 program treating crow's feet lines (CFL) with onabotulinumtoxinA. OBJECTIVE: To evaluate the efficacy and safety of onabotulinumtoxinA treatment of CFL alone or with glabellar lines (GL). METHODS: This multicenter, double-blind, placebo-controlled, repeat treatment, 7-month study randomized subjects with moderate-to-severe CFL and GL (maximum contraction) to onabotulinumtoxinA 44 U (CFL: 24 U, GL: 20 U; n = 305), onabotulinumtoxinA 24 U (CFL: 24 U, GL: placebo; n = 306), or placebo (n = 306). Coprimary end points were investigator-assessed and subject-assessed proportion of subjects achieving a CFL Facial Wrinkle Scale Grade of 0 or 1 (maximum smile; Day 30, Cycle 1). Additional efficacy end points and safety/adverse events (AEs) were evaluated. RESULTS: All primary and secondary end points were achieved; statistically significant differences favored onabotulinumtoxinA (p < .001, all comparisons vs placebo). Investigator and subject responder rates were: CFL, 54.9% and 45.8%; CFL + GL, 59.0% and 48.5%; and placebo, 3.3% (both), respectively. Responder rates on other end points also significantly favored onabotulinumtoxinA treatments. Most AEs were mild or moderate. Two subjects discontinued: 1 serious AE unrelated to treatment (myocardial infarction) and 1 treatment-related AE (injection site pain). CONCLUSION: OnabotulinumtoxinA was effective and well tolerated for treating moderate-to-severe CFL alone or in combination with GL.
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 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 | 0.002 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".