Evidence-Based Clinical Practice Guidelines for Extramammary Paget Disease
Bibliographic record
Abstract
IMPORTANCE: Extramammary Paget disease (EMPD) is a frequently recurring malignant neoplasm with metastatic potential that presents in older adults on the genital, perianal, and axillary skin. Extramammary Paget disease can precede or occur along with internal malignant neoplasms. OBJECTIVE: To develop recommendations for the care of adults with EMPD. EVIDENCE REVIEW: A systematic review of the literature on EMPD from January 1990 to September 18, 2019, was conducted using MEDLINE, Embase, Web of Science Core Collection, and Cochrane Libraries. Analysis included 483 studies. A multidisciplinary expert panel evaluation of the findings led to the development of clinical care recommendations for EMPD. FINDINGS: The key findings were as follows: (1) Multiple skin biopsies, including those of any nodular areas, are critical for diagnosis. (2) Malignant neoplasm screening appropriate for age and anatomical site should be performed at baseline to distinguish between primary and secondary EMPD. (3) Routine use of sentinel lymph node biopsy or lymph node dissection is not recommended. (4) For intraepidermal EMPD, surgical and nonsurgical treatments may be used depending on patient and tumor characteristics, although cure rates may be superior with surgical approaches. For invasive EMPD, surgical resection with curative intent is preferred. (5) Patients with unresectable intraepidermal EMPD or patients who are medically unable to undergo surgery may receive nonsurgical treatments, including radiotherapy, imiquimod, photodynamic therapy, carbon dioxide laser therapy, or other modalities. (6) Distant metastatic disease may be treated with chemotherapy or individualized targeted approaches. (7) Close follow-up to monitor for recurrence is recommended for at least the first 5 years. CONCLUSIONS AND RELEVANCE: Clinical practice guidelines for EMPD provide guidance regarding recommended diagnostic approaches, differentiation between invasive and noninvasive disease, and use of surgical vs nonsurgical treatments. Prospective registries may further improve our understanding of the natural history of the disease in primary vs secondary EMPD, clarify features of high-risk tumors, and identify superior management approaches.
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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 | 0.031 | 0.168 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.018 | 0.014 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.011 | 0.005 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.024 | 0.010 |
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".