Why Dosing Matters: A Closer Look at the Dose–Response Relationship With <scp>OnabotulinumtoxinA</scp>
Bibliographic record
Abstract
BACKGROUND: OnabotulinumtoxinA is licensed in many countries for simultaneous treatment of three areas of the upper face: glabellar lines, 20 U; lateral canthal lines, 24 U; and forehead lines, 20 U. AIMS: To assess the onabotulinumtoxinA dosing science and dose-response relationship in the treatment of upper facial lines (UFL). METHODS: Key practical questions are addressed using available data. RESULTS: OnabotulinumtoxinA doses were selected for Phase 3 registrational trials based on rigorous dose-ranging studies. In clinical practice, it is important to consider the relationship between dose and efficacy outcomes, duration, and safety. Interstudy comparison of duration analyses is complicated by the lack of a single comprehensive definition, but trial data with standard onabotulinumtoxinA dosing in the glabella suggest a median effect duration of ~4 months. Treatment of UFL at below the approved dose is associated with a shorter duration, inferior response rates, and lower patient satisfaction; there is no evidence that underdosing reduces adverse event risk. It may therefore be advisable to avoid going below the licensed dose unless there is a clear clinical rationale. By contrast, there is growing evidence that treatment outcomes can be further improved using doses above those currently licensed, without adversely affecting safety-as demonstrated in the glabella. Further studies are needed to assess this in lateral canthal and forehead lines. Additional work is also required to examine potential ceiling doses and better understand the dose-response relationship in patient subgroups. CONCLUSIONS: Appropriate dosing of onabotulinumtoxinA is essential for maximizing benefit and ensuring patient satisfaction.
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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 | 0.095 | 0.189 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".