Efficacy and Safety of Subcutaneous and Intravenous Loading Dose Regimens of Secukinumab in Patients with Active Rheumatoid Arthritis: Results from a Randomized Phase II Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy and safety of secukinumab, a fully human antiinterleukin-17A monoclonal antibody, administered with an intravenous (IV) or subcutaneous (SC) loading regimen versus placebo, in patients with active rheumatoid arthritis (RA). METHODS: In this phase II, double-blind, double-dummy, 52-week study (ClinicalTrials.gov NCT01359943), 221 patients with inadequate response to methotrexate were randomized (2:2:1) to secukinumab, IV loading 10 mg/kg at baseline, Weeks 2 and 4, then SC 150 mg every 4 weeks (n = 88); secukinumab SC loading 150 mg once weekly for 5 weeks, then every 4 weeks (n = 89); or a matching placebo (followed by secukinumab 150 mg every 4 weeks starting Week 16; n = 44). The primary endpoint was superior efficacy of pooled secukinumab versus placebo using American College of Rheumatology 20% response (ACR20) at Week 12. RESULTS: The primary efficacy endpoint was not met: ACR20 response at Week 12 was 49.2% for pooled secukinumab versus 40.9% for placebo (p = 0.3559). These variables improved significantly with pooled secukinumab versus placebo at Week 12 (all p < 0.05): the 28-joint Disease Activity Score (DAS28), patient's and physician's global assessment of disease activity, patient's assessment of RA pain, and high-sensitivity C-reactive protein levels. Results of continuous efficacy outcomes were similar between the IV and SC loading regimens. The most frequent adverse events were infections, with similar rates across secukinumab and placebo. CONCLUSION: Although the primary endpoint (ACR20) was not met, secukinumab demonstrated improved efficacy in reducing disease activity over placebo as measured by DAS28 and other secondary endpoints.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".