Treatment of Keratoacanthoma: Is Intralesional Methotrexate An Option?
Bibliographic record
Abstract
BACKGROUND: Keratoacanthomas (KAs) are a variant of squamous cell carcinomas. Some KAs have shown aggressive behaviour, leading to metastasis and death. Surgical excision is the treatment of choice for most KA patients. Intralesional methotrexate (MTX) may also be a potential treatment option for KAs. OBJECTIVE: To evaluate intralesional MTX as a treatment modality for KA. METHODS: A retrospective chart review of nine patients with KAs treated with intralesional MTX was performed. Each patient had biopsy-proven KA. The lesion was initially debulked, and MTX was injected at the base. Patients were seen weekly in the office, and reinjected with intralesional MTX depending on the response of the lesion. Each patient was evaluated for their response to the intralesional MTX injections, the number of injections required and complications. RESULTS: Patients required approximately two to four intralesional injections (12.5 mg to 25 mg per injection) before KA resolution. Eight of nine (88.9%) patients experienced complete resolution of their tumours. One patient experienced treatment failure, and underwent surgical excision of the KA. The average follow-up period was 2.8 years, and there were no recurrences. CONCLUSION: The results from the present retrospective study show that intralesional MTX injection is an effective treatment option for KAs. The authors propose that intralesional MTX injection with initial debulking of the KA should be used as a first line of treatment when KAs present on the extremities, in cosmetically sensitive areas and in elderly patients with multiple comorbities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".