Consensus recommendations for the treatment of basal cell carcinomas in <scp>G</scp>orlin syndrome with topical methylaminolaevulinate‐photodynamic therapy
Bibliographic record
Abstract
BACKGROUND: Patients with Gorlin syndrome develop multiple basal cell carcinomas (BCC), for which treatment is often difficult. Methylaminolevulinate-photodynamic therapy (MAL-PDT) is approved for the treatment of superficial and nodular BCCs in Canada and several European countries. OBJECTIVES: To establish consensus recommendations for the use of MAL-PDT in patients with Gorlin syndrome. METHODS: The Gorlin consensus panel was comprised of 7 dermatologists who had treated a total of 83 patients with Gorlin syndrome using MAL-PDT. Consensus was developed based on the personal experience of the expert and results of literature review (on PUBMED using the keywords 'MAL' and 'PDT' and 'Gorlin' or 'naevoid basal cell carcinoma syndrome'). RESULTS: Consensus was reached among the experts and the literature review identified 9 relevant reports. The experts considered MAL-PDT a generally effective and safe therapy for treatment of BCC in Gorlin syndrome. For superficial BCC (sBCC), all sizes can be treated, and in nodular BCC (nBCC), better efficacy can be achieved in thinner lesions (<2 mm in thickness). MAL-PDT treatment schedule should be performed according to labelling although in individual cases, it may be adapted and performed on a monthly basis based on clinical assessment. Follow-up should be related to frequency of recurrence, and severity, number and location of lesions. Multiple lesions and large areas may be treated during the same session; however, adequate pain management should be considered. CONCLUSIONS: MAL-PDT is safe and effective in patients with Gorlin syndrome. Utilization of these recommendations may improve efficacy and clearance rates in this population.
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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 | 0.037 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".