The Efficacy and Duration of Onabotulinum Toxin A in Improving Upper Facial Expression Lines With 64-Unit Dose Optimization: A Systematic Review and Meta-Analysis With Trial Sequential Analysis of the Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Onabotulinumtoxin A (Onabot A) was the first treatment to be approved for aesthetic indications, namely glabellar lines (GLs), crow's feet lines (CFLs), and forehead lines (FHLs), with a cumulative dose of 64 U. OBJECTIVES: The aim of this study was to conduct a meta-analysis to combine the available data for approved doses for GLs, CFLs, and FHLs to explore the effect and duration of simultaneous treatment with Onabot A. METHODS: PubMed/MEDLINE, Embase, and other national clinical trial registries were searched for randomized controlled trials from January 2010 to July 2022. The meta-analysis, trial sequential analysis, and investigator-assessed time to return to nonresponder status in GLs, CFLs, and FHLs following Onabot A were plotted to elicit a cumulative dose-adjusted response curve based on Kaplan-Meier analysis with a log-rank test. RESULTS: Fourteen randomized controlled trials were eligible for quantitative analysis. A total of 8369 subjects were recruited across the trials. The meta-analysis results show that Onabot A is very effective in reducing moderate to severe GLs, CFLs, and FHLs. The cumulative Z-curve for GLs, CFLs, and FHLs also exceeds the required information size (RIS). Kaplan-Meier analysis with a log-rank test demonstrated that simultaneous treatment of GLs, CFLs, and FHLs requires 182 days (95% CI = 179, 215 days) (P < 0.00002) to return to nonresponder status. CONCLUSIONS: Treatment of the upper facial expression lines with Onabot A is effective, and the approved cumulative dose of 64 U gives longer-lasting effects.
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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 | 0.018 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.027 | 0.008 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".