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Record W3028558697 · doi:10.3389/fonc.2020.00837

Deep Penetrating Nevus and Borderline-Deep Penetrating Nevus: A Literature Review

2020· review· en· W3028558697 on OpenAlexaff
Ioana Cosgarea, Klaus Griewank, Loredana Ungureanu, Arturo Tamayo, Timo Siepmann

Bibliographic record

VenueFrontiers in Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsUniversity of ManitobaBrandon Regional Health Authority
FundersSächsische Landesbibliothek – Staats- und Universitätsbibliothek DresdenTechnische Universität Dresden
KeywordsMedicineMelanomaDermatologyBiopsySentinel lymph nodeNevusLymph nodeDissection (medical)SurgeryRadiologyPathologyInternal medicineCancerBreast cancer

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.326
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations21
Published2020
Admission routes1
Has abstractyes

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