P129 A prospective comparative audit of outcomes in patients with basal cell carcinoma receiving 10 600-nm carbon dioxide laser-assisted photodynamic therapy with either methyl aminolaevulinate or 5-aminolaevulinic acid as a photosensitizer
Bibliographic record
Abstract
Abstract Photodynamic therapy (PDT) is a well-established nonsurgical management option for low-risk basal cell carcinomas (BCCs). This study compares the efficacy of two photosensitizing agents: methyl aminolaevulinate (MAL) and 5-aminolaevulinic acid (ALA), when used for patients undergoing 10 600-nm carbon dioxide laser-assisted photodynamic therapy. We included all patients with BCC receiving fully ablative laser-assisted PDT at a tertiary centre between November 2021 and November 2024. Lesions were first ablated with a 10 600-nm carbon dioxide laser (SmartXide Touch, DEKA Laser, Calenzano, Italy) under local anaesthetic. The photosensitizer was applied topically according to availability, and incubated for 3 h. The photosensitizer was either MAL 160 mg g−1 cream (Metvix; Galderma, Lausanne, Switzerland) or 5-ALA 78 mg g−1 gel (Ameluz; Biofrontera, Leverkusen, Germany). Photoactivation was by pulsed-dye laser (Cynergy; Cynosure, Westford, MA, USA) or intense pulsed light (Excelight, Lynton, UK). In total 132 lesions were included from 33 patients. Overall, 54.5% were treated with the photosensitizer MAL and 45.5% were treated with ALA. The rolling recurrence rate for all lesions treated with MAL was 2.8%, and with ALA 1.7%. The 2-year recurrence rate for MAL was 5.7% and for ALA 0.0%. Complication rates were low and were 1.4% for MAL and 1.7% for ALA. Cosmetic outcomes were good in both groups, with mean Vancouver Scar Scores of 3.1% and 3.9% for MAL and ALA, respectively. This study concludes that ALA-PDT has a lower overall and 2-year recurrence rate than MAL-PDT. The rate of complications was lower for MAL-PDT than for ALA-PDT, and the cosmetic outcomes for MAL-PDT were slightly better than for ALA-PDT when assessed using mean Vancouver Scar Scores.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".