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Record W2768522205 · doi:10.1159/000484203

Folliculotropism Does Not Affect Overall Survival in Mycosis Fungoides: Results from a Single-Center Cohort and Meta-Analysis

2017· review· en· W2768522205 on OpenAlexaff
Mariah Giberson, Ahmed Mourad, Robert Gniadecki

Bibliographic record

VenueDermatology · 2017
Typereview
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMycosis fungoidesSingle CenterMeta-analysisMedicineAffect (linguistics)CohortDermatologyCohort studyOncologyInternal medicineLymphomaPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Folliculotropic mycosis fungoides (FMF) is a distinct subtype of mycosis fungoides (MF) with unique clinicopathological features. The medical literature suggests that FMF has a more aggressive course and worse survival than classic MF. Previous studies do not use standardized treatment, and no studies have reported an association between treatment response and overall survival (OS). OBJECTIVE: To compare OS for MF, FMF, and Sézary syndrome (SS) patients. METHODS: Data were collected retrospectively from 218 patients (171 MF, 15 SS, 32 FMF) treated in a single academic center between 1970 and 2016. RESULTS: Negative predictors of OS were age (OR = 1.07), male sex (OR = 1.63), and stage IIB, III, and IV (OR = 4.10, 5.42, and 7.54, respectively, vs. stage IA). Lack of initial PUVA response was strongly associated with negative OS (OR = 3.08). Kaplan-Meier analysis of age-, sex-, and stage-matched MF and FMF patients found similar OS between the 2 groups. The 5-year OS was 91% for FMF and 74% for MF. Meta-analysis of current data and 2 published studies where survival of FMF patients was compared to MF did not reveal statistically significant differences between these 2 diseases. CONCLUSIONS: When patients were matched for age, sex, and disease stage, folliculotropism did not affect OS in MF.

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: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.541
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0110.003
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.204
GPT teacher head0.415
Teacher spread0.211 · 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 designMeta-analysis
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

Citations10
Published2017
Admission routes1
Has abstractyes

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