Treatment Outcomes of Adjunct and Stand-alone Photodynamic Therapy in Patients With Extramammary Paget Disease: A Literature Review
Bibliographic record
Abstract
BACKGROUND: Extramammary Paget disease (EMPD) is a rare malignant neoplasm arising from apocrine gland-bearing skin. The surgical management of EMPD is often coupled with noninvasive techniques including cryotherapy, ablative lasers, topical chemotherapies, and photodynamic therapy (PDT). The specificity and preservation of tissue that PDT with photosensitizers 5-aminolevulinic acid or 5-methyl aminolevulinate allows makes it a potential treatment of EMPD. METHODS: The authors present a review of 13 studies, from 2002 to 2019, examining the reported efficacy of PDT alone and adjunctive PDT in EMPD treatment. RESULTS: In the 52 patients with 56 lesions who received stand-alone PDT, 20 lesions (35.7%, n = 20/56) experienced complete resolution, 31 lesions (55.4%, n = 31/56) experienced partial resolution, 5 lesions (8.9%, n = 5/56) failed to demonstrate response to treatment, and 23 lesions (41.1%, n = 23/56) had recurrence. In the 56 patients with 66 lesions that received adjunctive PDT paired with surgery ( n = 55/66), imiquimod ( n = 4/66), holmium laser and surgery ( n = 1/66), Mohs surgery ( n = 2/66), and combined surgery, imiquimod, and 5-fluorouracil ( n = 1/66), 34 lesions (51.5%) experienced complete resolution, 27 lesions (40.9%) experienced partial resolution, 5 lesions (7.6%) failed to demonstrate any response to treatment, and 16 lesions (24.2%) had EMPD recurrence. CONCLUSION: Further studies with larger sample size are needed to consolidate these findings and inform clinical decisions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".