Long-term safety and efficacy of sirukumab for patients with rheumatoid arthritis who previously received sirukumab in randomised controlled trials (SIRROUND-LTE)
Bibliographic record
Abstract
OBJECTIVE: Interleukin (IL)-6 is a pleiotropic cytokine involved in the pathophysiology of rheumatoid arthritis (RA). Sirukumab is a human monoclonal antibody that binds to IL-6 with high affinity and specificity. METHODS: This long-term extension (LTE) study of the SIRROUND-D and SIRROUND-T studies assessed long-term safety and efficacy of sirukumab in adults with moderate-to-severe RA refractory to conventional disease-modifying antirheumatic drug therapy or antitumor necrosis factor agents. Patients received sirukumab 100 mg subcutaneously (SC) every 2 weeks (q2w) or sirukumab 50 mg SC every 4 weeks (q4w). RESULTS: 1820 patients enrolled in the LTE; median exposure was 2.34 and 2.07 years in sirukumab 50 mg q4w and 100 mg q2w groups, respectively. Adverse events (AEs) occurred in similar proportions between groups, with the exception of major adverse cardiovascular events (MACE), which were more common in the 50 mg q4w versus 100 mg q2w group (2.2% vs 1.0%), and injection-site reactions, more common in the 100 mg q2w group versus 50 mg q4w group (7.5% vs 3.7%). The most common serious AEs were infections (10% of the patients); 32 (1.8%) patients died during the study (primarily from serious infection and MACE). Malignancies were reported in 24 (1.3%) patients. Gastrointestinal perforations, hepatobiliary abnormalities and changes in laboratory parameters were rare. Reductions in RA signs and symptoms and improvements in physical function were maintained throughout the LTE. CONCLUSIONS: The safety profile of sirukumab in the LTE remained consistent with that reported in SIRROUND-D and SIRROUND-T and efficacy was maintained. TRIAL REGISTRATION NUMBER: NCT01856309.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".