Non-Invasive Treatment of Basal Cell Carcinoma: Photodynamic Therapy Following Curettage
Bibliographic record
Abstract
BACKGROUND: To investigate the effectiveness, safety, patient satisfaction, and cosmetic outcome of Methyl Aminolevulinate-Photodynamic Therapy (MAL-PDT) following curettage in order to make recommendations for its use in dermatology practices. METHODS: A retrospective chart review of patients who received MAL-PDT following curettage for the indication of basal cell carcinoma (BCC) between 2009 and 2016 at a single private clinic in Ontario, Canada. Two hundred and seventy-eight patients with 352 BCC lesions were included, consisting of 44.2% males (n=123) and 55.8% females (n=155) with a mean age of 57.24 years. The primary outcome measurement consisted of the cure rate. Secondary outcome measurements included side effects, patient satisfaction, and cosmetic outcome, as reported in the medical charts. RESULTS: The overall cure rate was 90.3% (n=318). After controlling for age, sex, and lesion type, nasal lesions were approximately 2.82 (95% CI: 1.24-6.40, P=0.01) times more likely to experience a recurrence. 18.3% of patients (n=51) reported side effects, the most common being burning (n=19). Of those who expressed satisfaction, 100% (n=25) reported being happy. Of lesions with cosmetic data, 90.3% displayed a good response (n=149). CONCLUSION: MAL-PDT following curettage is an effective and safe treatment option for BCC lesions with a good cosmetic outcome and suggested high patient satisfaction. J Drugs Dermatol. 2023;22(5): doi:10.36849/JDD.7133.
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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) | 0.000 | 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".