Cutaneous T-cell lymphoma in a JAK inhibitor patient: A case report
Bibliographic record
Abstract
Janus kinase (JAK) inhibitors are novel molecules increasingly prescribed for various dermatologic conditions. However, the Food and Drug Administration recently reported increased risks of malignancy in patients taking this class of medication. To shed more light on this potential adverse effect, we present a patient with cutaneous T-cell lymphoma possibly associated with his treatment with a JAK inhibitor for atopic dermatitis. To our knowledge, there are no reported cases of cutaneous T-cell lymphoma in association with JAK inhibitors in the literature. We highlight the importance of remaining cautious when prescribing this new class of medication, especially in patients with risk factors for malignancy. Moreover, when faced with atypical presentations of atopic dermatitis, we stress the need for a biopsy to make the correct diagnosis prior to treatment. Lastly, we encourage further studies to better characterize the malignancy risk associated with JAK inhibitors.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".