Identifying unmet needs and challenges in the definition of a plaque in mycosis fungoides: An EORTC‐CLTG/ISCL survey
Bibliographic record
Abstract
BACKGROUND: Consensus about the definition and classification of 'plaque' in mycosis fungoides is lacking. OBJECTIVES: To delineate a comprehensive view on how the 'plaque' entity is defined and managed in clinical practice; to evaluate whether the current positioning of plaques in the TNMB classification is adequate. METHODS: A 12-item survey was circulated within a selected panel of 22 experts (pathologists, dermatologists, haematologists and oncologists), members of the EORTC and International Society for Cutaneous Lymphoma. The questionnaire discussed clinical and histopathological definitions of plaques and its relationship with staging and treatment. RESULTS: Total consensus and very high agreement rates were reached in 33.3% of questions, as all panellists regularly check for the presence of plaques, agree to evaluate the presence of plaques as a potential separate T class, and concur on the important distinction between plaque and patch for the management of early-stage MF. High agreement was reached in 41.7% of questions, since more than 50% of the responders use Olsen's definition of plaque, recommend the distinction between thin/thick plaques, and agree on performing a biopsy on the most infiltrated/indurated lesion. High divergence rates (25%) were reported regarding the possibility of a clinically based distinction between thin and thick plaques and the role of histopathology to plaque definition. CONCLUSIONS: The definition of 'plaque' is commonly perceived as a clinical entity and its integration with histopathological features is generally reserved to specific cases. To date, no consensus is achieved as for the exact definition of thin and thick plaques and current positioning of plaques within the TNMB system is considered clinically inadequate. Prospective studies evaluating the role of histopathological parameters and other biomarkers, as well as promising diagnostic tools, such as US/RM imaging and high-throughput blood sequencing, are much needed to fully integrate current clinical definitions with more objective parameters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".