Sirukumab for rheumatoid arthritis: the phase III SIRROUND-D study
Bibliographic record
Abstract
OBJECTIVES: Interleukin-6 (IL-6) is implicated in rheumatoid arthritis (RA) pathophysiology. Unlike IL-6 receptor inhibitors, sirukumab is a human monoclonal antibody that selectively binds to the IL-6 cytokine. The phase III, multicentre, randomised, double-blind, placebo-controlled, parallel-group SIRROUND-D study (ClinicalTrials.gov identifier NCT01604343) evaluated the efficacy and safety of sirukumab in patients with active RA refractory to disease-modifying antirheumatic drugs. METHODS: Patients were randomised 1:1:1 to treatment with sirukumab 100 mg every 2 weeks, 50 mg every 4 weeks or placebo every 2 weeks subcutaneously. Results through week 52 are reported. RESULTS: Of 1670 randomised patients, significantly more patients achieved American College of Rheumatology 20% (ACR20) response at week 16 (coprimary endpoint) with sirukumab 100 mg every 2 weeks (53.5%) or 50 mg every 4 weeks (54.8%) versus placebo (26.4%; both p<0.001). Mean (SD) change from baseline in modified Sharp/van der Heijde score at week 52 (coprimary endpoint) was significantly lower with sirukumab (100 mg every 2 weeks: 0.46 (3.26); 50 mg every 4 weeks: 0.50 (2.96)) versus placebo (3.69 (9.25); both p<0.001). All major secondary endpoints (week 24 Health Assessment Questionnaire-Disability Index change from baseline, ACR50 response, 28-joint Disease Activity Score based on C reactive protein and major clinical response (ACR70 for six continuous months by week 52)) were met. The most common adverse events with sirukumab were elevated liver enzymes, upper respiratory tract infection, injection site erythema and nasopharyngitis. CONCLUSIONS: Sirukumab 100 mg every 2 weeks and 50 mg every 4 weeks led to significant reductions in RA symptoms, inhibition of structural damage progression and physical function and quality of life improvements, with an expected safety profile. TRIAL REGISTRATION NUMBER: NCT01604343; Results.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".