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Record W4396706510 · doi:10.4081/dr.2024.10008

When mycosis fungoides seems not to be within the spectrum of clinical and histopathological differential diagnoses

2024· review· en· W4396706510 on OpenAlexaff
Monia Di Prete, Andrea Michelerio, Viviana Lora, Carlo Tomasini, Carlo Cota

Bibliographic record

VenueDermatology Reports · 2024
Typereview
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsMycosis fungoidesMedicineMedical diagnosisDermatologyDifferential diagnosisBroad spectrumPathologyLymphoma

Abstract

fetched live from OpenAlex

The most prevalent primary cutaneous T-cell lymphoma, mycosis fungoides (MF), is characterized by the development of plaques and nodules after an erythematous patchy phase that is non-specific. An infiltrate of atypical small- to medium-sized cerebriform lymphocytes in the superficial dermis, with variable epidermotropism, is the histopathological hallmark of the disease. In more advanced stages of the illness, large-cell transformation may be seen. Early diagnosis of MF can be very challenging based only on histopathologic or clinical findings, so it is critical to have a clinical-pathological correlation. Many atypical variants of MF that deviate from the classic Alibert-Bazin presentation of the disease have been described over the past 30 years, sometimes with different prognostic and therapeutic implications. Clinically or histopathologically, they can mimic a wide range of benign inflammatory skin disorders. To make a conclusive diagnosis in these cases, it is recommended to take multiple biopsies from various lesions and to carefully correlate the clinical and pathological findings. We have outlined the various facets of the illness in this review, positioning MF as a "great imitator", with an emphasis on the more recently identified variations, differential diagnosis, and its benign mimics.

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)0.003
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 score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.124
GPT teacher head0.443
Teacher spread0.319 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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