Efficacy and safety of rituximab in anti-synthetase antibody positive and negative subjects with idiopathic inflammatory myopathy: a registry-based study
Bibliographic record
Abstract
OBJECTIVE: Post-hoc analyses of the Rituximab in Myositis trial indicate that specific autoantibodies profiles may influence treatment response. We compared the efficacy and safety of rituximab in anti-synthetase antibody (ARS-ab) positive and negative patients. METHODS: Adult idiopathic inflammatory myopathy (IIM) subjects in the Swedish Rheumatology Quality Register who received ⩾ 1 cycle of rituximab were enrolled. Efficacy assessment was based on the International Myositis Assessment and Clinical Studies (IMACS) core set measures and the 2016 ACR/EULAR definition of improvement for PM and DM. Safety assessment included drug-related adverse event and death during study period. Comparisons were done within and between the ARS-ab defined groups before and after first and last cycles. Associations between selected clinical features and improvement after one rituximab cycle were assessed using logistic regression. RESULTS: Sixty-five subjects were included and 43 had a follow-up visit within 5-10 months. Seventy-eight percent of ARS-ab positive subjects had moderate/major ACR/EULAR improvement after one cycle compared with 50% in the ARS-ab negative group. After several cycles, 79% of the ARS-ab positive and 67% of the ARS-ab negative patients achieved moderate/major improvement. A significant glucocorticoid-sparing effect was only observed in the ARS-ab positive group (P = 0.001). The most frequent adverse events were infections. One ARS-ab positive and two ARS-ab negative patients died during follow-up period. CONCLUSION: Irrespectively of their autoantibody status, a majority of subjects treated with several rituximab cycles had moderate/major improvement. In addition, ARS-ab positive subjects experienced a significant glucocorticoid-sparing effect.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".