Effects of Sarilumab on Rheumatoid Arthritis as Reported by Patients Using the Rheumatoid Arthritis Impact of Disease Scale
Bibliographic record
Abstract
OBJECTIVE: We evaluated the effect of sarilumab on patient-perceived impact of rheumatoid arthritis (RA) using the 7-domain RA Impact of Disease (RAID) scale. METHODS: Two phase III, randomized, controlled trials of sarilumab in patients with active, longstanding RA were analyzed: (1) sarilumab 150 mg and 200 mg every 2 weeks plus conventional synthetic disease-modifying antirheumatic drugs (+csDMARD) versus placebo + csDMARD [TARGET (NCT01709578)]; and (2) sarilumab 200 mg versus adalimumab (ADA) 40 mg monotherapy [MONARCH (NCT02332590)]. Least-squares mean (LSM) differences in RAID total score (range 0-10) and 7 key RA symptoms, including pain and fatigue (baseline to Weeks 12 and 24), were compared. "Responders" by RAID total score were defined by improvements from baseline ≥ minimal clinically important difference (MCID), and ≥ patient-acceptable symptom-state (PASS) at endpoint. RESULTS: Sarilumab 150 mg and 200 mg + csDMARD were nominally superior (p < 0.05) versus placebo + csDMARD and 200 mg sarilumab versus ADA 40 mg in LSM differences for RAID total score at weeks 12 (-0.93 and -1.13; -0.49, respectively) and 24 (-0.75 and -1.01; -0.78), and all effects of RA (except functional impairment in MONARCH Week 12). Effects were greater in physical domains (e.g., pain) than mental domains (e.g., emotional well-being). More patients receiving sarilumab versus placebo or ADA reported improvements ≥ MCID and PASS in total RAID scores at both assessments. CONCLUSION: Based on the RAID, sarilumab + csDMARD or as monotherapy reduced the effect of RA on patients' lives to a greater extent than placebo + csDMARD or ADA monotherapy. (ClinicalTrials.gov: NCT01709578 and NCT02332590).
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".