Healthcare Provider Experience in Diagnosing and Treating Cutaneous T-Cell Lymphoma
Bibliographic record
Abstract
INTRODUCTION: Cutaneous T-cell lymphoma (CTCL) is a rare, heterogeneous group of non-Hodgkin lymphomas characterized by various clinical, molecular, and histopathologic features of the skin. Variants of CTCL share many clinical features with common inflammatory skin diseases such as atopic dermatitis and psoriasis, making accurate and early diagnosis challenging in clinical settings. Inappropriate treatment or a delay in diagnosis can lead to increased morbidity and mortality. Here, we report findings from an online survey that investigated dermatology community practice, knowledge, and education surrounding CTCL. METHODS: An electronic survey of ten questions was developed and approved by physician experts in CTCL to assess experiences in diagnosing and treating CTCL among healthcare providers (HCPs). The survey was deployed to 10,600 US dermatology HCPs, including medical doctors (MDs), doctors of osteopathic medicine (DOs), nurse practitioners (NPs), and physician assistants (PAs) and excluding HCPs associated with CTCL centers of excellence. RESULTS: Among 44 HCPs who responded and were eligible for inclusion, 82% had diagnosed between one and ten CTCL cases in the last 5 years. Most respondents (91%) reported that they include CTCL in their differential diagnoses after patients do not respond to treatment of more common conditions. Patients with CTCL were frequently diagnosed with other inflammatory dermatoses-most commonly dermatitis and psoriasis-before a CTCL diagnosis, and many were treated with ineffective therapies for years. The most common length of time before a CTCL diagnosis was made was between 1 and 3 years, though 16% of HCPs reported that patients were treated for other diseases or skin conditions for ≥ 5 years. Two-thirds of HCPs agreed that further education surrounding CTCL is needed. CONCLUSIONS: Given the infrequency of CTCL and its similar presentation to other common dermatologic conditions, increased education of CTCL is needed in the dermatology community to improve patient outcomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".