Safety and Efficacy of Rituximab in Severe Juvenile Dermatomyositis: Results from 9 Patients from the French Autoimmunity and Rituximab Registry
Bibliographic record
Abstract
OBJECTIVE: To evaluate the safety and efficacy of rituximab (RTX) in juvenile dermatomyositis (JDM) in off-trial patients. METHODS: We conducted a multicenter prospective study of patients with JDM included in the French Autoimmunity and Rituximab (AIR) registry. RESULTS: Nine patients with severe JDM were studied. The main indication for RTX treatment was severe and/or refractory muscle involvement (7 patients), severe calcinosis (1 patient), or severe chronic abdominal pain associated with abdominal lipomatosis (1 patient). RTX was associated with corticosteroids, immunosuppressive drugs, and plasma exchange therapy in 9/9, 5/9, and 2/9 patients, respectively. Mild infections of the calcinosis sites occurred in 2 patients and an infusion-related event in 1. Complete clinical response was achieved in 3/6 patients treated with RTX for muscle involvement. In these responders steroid therapy was stopped or tapered to < 15% of the baseline dosage, with no relapse, with a followup ranging from 1.3 to 3 years. Calcinosis did not improve in the 6 affected patients. CONCLUSION: This small series suggests that rituximab may be effective for treating muscle and skin involvement in a small subset of children with severe JDM, and that its safety profile was satisfactory. Further studies are needed to identify predictive factors of response to RTX in patients with severe JDM.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".