Emergence of cutaneous Rosai–Dorfman disease during immunosuppressive treatment of follicular B-cell lymphoma: A case report
Bibliographic record
Abstract
BACKGROUND: Sinus histiocytosis with massive lymphadenopathy, also known as Rosai-Dorfman disease, is a rare proliferation of non-Langerhans histiocytes. Cutaneous Rosai-Dorfman disease is a rare subtype of Rosai-Dorfman disease limited to the skin with variable clinical presentation. CASE SUMMARY: A 59-year-old female with a history of osteoarthritis, hypothyroidism, and follicular B-cell lymphoma presented with pruritic, erythematous, dome-shaped papules that developed while on chemotherapy treatment. During cutaneous disease progression, the patient was further diagnosed with myelodysplastic syndrome. Histology review revealed patchy staining for S100 in the CD68+ histiocytes within the dermis with no enlarged histiocytes or emperipolesis. Given the absence of other findings, this was interpreted as cutaneous Rosai-Dorfman disease. CONCLUSION: There is still little known about the aetiology and pathogenesis of cutaneous Rosai-Dorfman disease. Non-specific immunohistochemistry in the midst of lymphoma, immunosuppressive treatments, and myelodysplastic syndrome produced a blurred diagnostic picture and delayed appropriate treatment, highlighting the diagnostic challenges of cutaneous Rosai-Dorfman disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".