Forehead Line Treatment With OnabotulinumtoxinA in Subjects With Forehead and Glabellar Facial Rhytids: A Phase 3 Study
Bibliographic record
Abstract
BACKGROUND: Effacement of horizontal forehead lines (FHL) with onabotulinumtoxinA has not been investigated in prospective Phase 3 studies. OBJECTIVE: To evaluate safety and efficacy of onabotulinumtoxinA treatment of FHL together with glabellar lines (GL). MATERIALS AND METHODS: A 12-month, Phase 3 study randomized subjects with moderate-to-severe FHL and GL to onabotulinumtoxinA 40 U or placebo, distributed between the frontalis (20 U) and glabellar complex (20 U). After Day 180, subjects could receive up to 2 additional open-label onabotulinumtoxinA treatments. Efficacy was assessed using the Facial Wrinkle Scale (FWS) and Facial Line Outcomes questionnaire. RESULTS: The intent-to-treat (ITT) population included 391 subjects, and the modified ITT (mITT) population (subjects with psychological impact) included 254 subjects. After 30 days, onabotulinumtoxinA significantly improved the investigator- and subject-assessed appearance of FHL severity by at least 2 FWS grades in 61.4% of ITT subjects versus 0% of placebo subjects (p < .0001). In the mITT population, 94.8% of onabotulinumtoxinA subjects and 1.7% of placebo subjects achieved investigator- and subject-assessed FWS ratings of none/mild (p = .0003). Patient-reported outcomes were consistent with FWS ratings. OnabotulinumtoxinA was well tolerated. CONCLUSION: OnabotulinumtoxinA 40 U distributed between the frontalis and glabellar complex was safe and effective for treatment of moderate-to-severe FHL.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".