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Record W7120256434 · doi:10.1097/dss.0000000000005005

Digital Papillary Carcinoma: A Literature Review of Epidemiology, Management Strategies, and Patient Outcomes

2025· article· en· W7120256434 on OpenAlexaff
William Liu, Rahul Nanda, David Zloty

Bibliographic record

VenueDermatologic Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer and Skin Lesions
Canadian institutionsMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsAmputationMEDLINEResectionPatient dataLarge sample

Abstract

fetched live from OpenAlex

BACKGROUND: Digital papillary carcinoma (DPC) is a rare tumor arising from the sweat glands, often occurring in the digits of the hands or feet with metastatic potential. OBJECTIVE: To present a literature review of the epidemiology, management modalities, disease progression, and outcome data on DPC. METHODS: Using the OVID platform, MEDLINE and Embase were searched for studies providing original data on DPC. RESULTS: A total of 155 cases of DPC from 81 articles were included. No case of recurrence was reported after Mohs micrographic surgery (MMS) ( n = 3), 28% of cases had recurrence after excision ( n = 46), 29% of cases had recurrence after amputation ( n = 24), and 67% with biopsy alone ( n = 3). Majority of DPCs were located on the right side of the body (68%) within the upper extremities (75%). The third finger of the hand was most affected (37%) compared to the other digits. CONCLUSION: No clear consensus on the optimal management of DPC has emerged. Excision and amputation have shown comparable recurrence rates. MMS may be a viable treatment but was based on a small sample size. Majority of DPC cases are nonrecurring and nonmetastatic, with low reported rates of death. Ultimately, more comprehensive data are needed to establish optimal treatment guidelines for DPC.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.665
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.300
Teacher spread0.276 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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