Long-term tolerance and efficacy of siltuximab (anti-IL-6) in a young adult with idiopathic multicentric Castleman disease during COVID-19
Bibliographic record
Abstract
Background: Castleman disease (CD) is a rare lymphoproliferative disorder with various subtypes, including the HHV-8-negative/idiopathic multicentric CD (iMCD). The diagnosis of iMCD remains challenging due to its non-specific presentation, in the form of generalised lymphadenopathies and inflammation. Two clinical presentations have been recently defined: a severe form iMCD-TAFRO and a milder form of iMCD not otherwise specified (iMCD-NOS). identification of interleukin-6 (IL-6) as a major culprit of inflammatory symptoms led to the development of anti-IL-6 therapies, with siltuximab being the approved first-line treatment. Case description: A 16-year-old male presented with recurrent fever, night sweats and several other non-specific symptoms. After extensive evaluations, an excisional lymph node biopsy confirmed the iMCD-NOS diagnosis. The patient received high-dose steroid therapy followed by siltuximab for four years. This treatment was well tolerated with only mild neutropenia not leading to dose adjustment. On siltuximab, the patient developed two mild COVID-19 episodes. His response to siltuximab remained effective throughout four years. Discussion: The absence of biomarker or causal agent identification poses a diagnostic challenge requiring lymph node histopathology for a definitive diagnosis of iMCD. Anti-IL 6 (siltuximab) is the recommended frontline therapy, suppressing inflammation and halting disease progression. Intravenous administration every 3 to 6 weeks can impact patient quality of life, prompting further research for alternative treatments. High-dose steroids, rituximab, cyclosporine, tacrolimus, lenalidomide or combined chemotherapy such as rituximab-bortezomib-dexamethasone are among the considered options according to disease severity. Conclusion: Overall, long-term siltuximab effectively controlled iMCD symptoms and was well tolerated by this young adult, who endured two mild COVID-19 episodes. LEARNING POINTS: Lymph node biopsy rather than bone marrow biopsy is needed for the diagnosis of iMCD.We were able to control the patient's condition in the absence of cumulative toxicity during four years of siltuximab anti-IL6 therapy.Immunosuppressive anti-IL6 therapy did not worsen two episodes of COVID-19.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".