Revealing the Patient Perspective: Evolution of Patient‐Reported Outcome Measures in Botulinum Toxin Studies in Aesthetic Medicine
Bibliographic record
Abstract
BACKGROUND: OnabotulinumtoxinA has been licensed for the treatment of upper facial lines for over 20 years. Patient benefits extend well beyond correction of the lines themselves-including positive effects on confidence, self-esteem, feelings of attractiveness, and age appearance. Regulatory bodies recommend that patient-reported outcomes (PROs) are routinely included in registrational studies to ensure the patient perspective is considered. Essential guidance is available from regulators and other expert groups to aid the development, validation, and use of appropriate PROs. AIMS: To reflect on the evolution of patient experience data collection in onabotulinumtoxinA aesthetic medicine development programs within the context of PRO usage across approved botulinum toxins. METHODS: Literature searches were performed to identify relevant publications. RESULTS: Several PRO instruments have been rigorously developed and validated following regulatory guidance and implemented in onabotulinumtoxinA clinical programs. These include the Facial Line Outcomes Questionnaire (FLO-11) and Facial Line Satisfaction Questionnaire (FLSQ). The data generated have supported the licensing process and enabled a deeper understanding of patient perspectives. Although these instruments were developed for clinical studies, the concepts obtained directly from patient interviews align with patient goals in clinical practice. Similarly, PROs such as FACE-Q are now employed more widely across approved botulinum toxins. CONCLUSIONS: A patient-centric approach, in lockstep with regulatory requirements, has been central to onabotulinumtoxinA development. Awareness of the comprehensive benefits of aesthetic treatments should continue to improve based on increasingly robust PROs.
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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 | 0.399 | 0.425 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 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".