Cryosurgery + 5% 5-Fluorouracil for Treatment of Superficial Basal Cell Carcinoma and Bowen’s Disease
Bibliographic record
Abstract
BACKGROUND: Superficial basal cell carcinoma (sBCC) and squamous cell carcinoma in situ (SCCis) are 2 types of nonmelanoma skin cancers (NMSCs) that are amenable to treatment with topical 5-fluorouracil, cryosurgery, or topical imiquimod, among other destructive and surgical modalities. There are few studies examining the effectiveness of combination therapy with 5% 5-fluorouracil and cryosurgery for the treatment of sBCC and SCCis. OBJECTIVES: Our objective was to study the clinical cure rate achieved with the regimen of cryosurgery and a 3-week course of 5% 5-fluorouracil in the treatment of biopsy-proven sBCC and SCCis. METHODS: A retrospective chart review of patients treated with cryosurgery and a 3-week course of 5% 5-fluorouracil was performed. Immunocompetent patients with biopsy-proven sBCC or SCCis who completed the treatment and attended a follow-up appointment at 6 months were included in the study. RESULTS: On clinical examination, 30 sBCC lesions of the 34 that were assessed and 31 SCCis lesions of the 33 that were assessed demonstrated no evidence of recurrence. The clinical cure rates were found to be 73% (sBCC) and 82% (SCCis), with the inclusion of patients that were lost to follow-up. CONCLUSIONS: This approach may represent a suitable option for select patients for the treatment of SCCis. Further studies with a longer follow-up duration, documentation of histologic cure, and tolerability of this regimen for SCCis are needed. The effectiveness of cryosurgery and 5-fluorouracil for sBCC requires further study.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".