Extramammary Paget’s Disease: Diagnosis, Pathogenesis, and Treatment with Focus on Recent Developments
Bibliographic record
Abstract
Extramammary Paget's disease (EMPD) is a rare neoplasm that usually develops in apocrine gland-bearing areas, such as the vulva, scrotum, and penis. EMPD may present with a focal, multifocal, or an ectopic lesion. Clinically, EMPD lesions often exhibit infiltrative erythema, which is sometimes similar to other skin disorders such as eczema. While primary EMPD arises as intraepithelial neoplasm of the epidermis, EMPD-like lesions may occur from epidermotropic spread of malignant cells or direct extension from an underlying internal neoplasm, known as secondary EMPD. Because treatment strategies differ for primary EMPD and secondary EMPD, accurate diagnosis based on detailed histopathological evaluation is required. In the early stages, EMPD usually shows indolent growth, and most cases are diagnosed as carcinoma in situ. However, invasive lesions may result in metastases, and deep invasion is associated with high incidence of metastases. Conventional chemotherapies have been used for EMPD treatment in patients with distant metastases, but the efficacy is not satisfactory, and the prognosis for such patients remains poor. Recent studies have provided various insights into the molecular pathogenesis of the development and advancement of EMPD, which may lead to novel treatment approaches for metastatic EMPD. This review addresses the diagnosis, pathogenesis, and treatment of EMPD with focus on recent progress in understanding this disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".