Intralesional Botulinum Toxin A for Keloid Treatment: A Review of Efficacy, Safety, and Clinical Applications
Bibliographic record
Abstract
Background: Keloids are fibroproliferative disorders characterized by excessive scarring, functional impairment, and aesthetic concerns. Despite the availability of various treatments, recurrence rates remain high, highlighting the need for alternative therapies with favorable safety profiles. Botulinum toxin A (BTX-A) has emerged as a potential option for keloid treatment; however, its therapeutic role is still not fully elucidated. The aim of this study was to evaluate the efficacy and safety of BTX-A in the treatment of keloids through a structured review of available literature. Methods: This literature review was conducted from three scientific databases: PubMed, Scopus, and Cochrane. The following keywords used were "botulinum toxin", "BTX-A", "botulinum toxin A", and "keloids". Original studies published in English between 2014 and 2024 that involved human subjects and investigated the use of BTX-A in the treatment of keloids were included. Results: A total of eleven randomized controlled trials were included in this review. Of these, eight studies reported statistically significant improvements in keloid characteristics such as height, pliability, and vascularity following intralesional BTX-A treatment, as measured by validated scales like the Vancouver Scar Scale (VSS). Two studies demonstrated comparable efficacy between BTX-A and intralesional triamcinolone acetonide (TAC). Adverse events were rare and generally limited to mild local reactions. In addition, BTX-A has been shown to be safe for use as a keloid therapy even in the pediatric population. Conclusion: BTX-A showed satisfactory efficacy and safety. In addition, BTX-A showed significant improvement in subjective symptoms in keloid lesions, making BTX-A a promising alternative option for keloid therapy.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".