Clinical Improvement in Early-Onset Interstitial Lung Disease Using Rituximab in Children With Antimelanoma Differentiation-Associated Gene 5–Positive Juvenile Dermatomyositis
Bibliographic record
Abstract
OBJECTIVE: Children with juvenile dermatomyositis (JDM) and antibodies to antimelanoma differentiation-associated gene 5 (anti-MDA5) are at increased risk of severe disease complications, including interstitial lung disease (ILD). Data regarding treatment of disease complications in this patient population are limited. In this study, we examined the disease course of children with JDM and anti-MDA5 antibodies before and after treatment with rituximab (RTX). METHODS: Patients aged 2-21 years and seen at the Children's Hospital at Montefiore between July 2012 and August 2021, with a diagnosis of JDM, positive anti-MDA5 antibodies, and evidence of ILD, and who were treated with RTX were eligible for inclusion. Retrospective clinical and laboratory data were reviewed. RESULTS: Five of 8 patients with positive anti-MDA5 antibodies had evidence of ILD (62.5%). Four patients had data available for review. All patients received at least 5 courses of RTX infusions, with discontinuation of steroids by an average of 12 months after starting RTX and a decrease to fewer than 2 concurrent medications by the fifth course of RTX. Indicators of ILD on high-resolution computed tomography and pulmonary function tests either improved or fully resolved over the course of RTX treatment for all patients. Patients also demonstrated resolution of active cutaneous manifestations and musculoskeletal disease activity. CONCLUSION: To our knowledge, this is the first study to examine the use of RTX in children with JDM and anti-MDA5 antibodies, with notable improvements in ILD, cutaneous, and musculoskeletal manifestations. Further studies are needed to better understand the efficacy of RTX for JDM disease-related complications.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".