Deep Penetrating Nevus and Borderline-Deep Penetrating Nevus: A Literature Review
Bibliographic record
Abstract
Deep penetrating nevi (DPN) are rare melanocytic nevi, which can exhibit atypical histological features hampering the differentiation from malignant melanoma. DPN are considered benign melanocytic lesions, but rare spread to lymph nodes and unfavorable clinical outcomes associated with borderline/atypical DPN (B-DPN) has been reported. Since no guidelines are available for DPN and B-DPN, we aimed to review the literature on DPN and B-DPN to assess the management and prognosis. We screened 3,513 references from EMBASE, Scopus and Medline databases, and included 15 studies with a total of 355 DPN patients and 48 B-DPN patients. Therapeutic interventions ranged from simple excision to wide excisions and sentinel lymph node biopsy (SLNB), with block lymph node dissection in some positive SLNB cases. Follow-up periods ranged from 3 months to 23 years during which a total of five recurrences, two in DPN and three in B-DPN group, and three metastases, in B-DPN group, were reported. While some of the included studies comprised clinical and histopathological correlation, few included genetic assessment. The present review highlights the need for prospective cohort studies applying composite measures to identify effective regimens of diagnostic workup and treatment in DPN and B-DPN.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".