One-year Efficacy and Safety Results of Secukinumab in Patients With Rheumatoid Arthritis: Phase II, Dose-finding, Double-blind, Randomized, Placebo-controlled Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the longer-term safety and efficacy of secukinumab, a fully human monoclonal antiinterleukin-17A antibody, in patients with rheumatoid arthritis. METHODS: In this 52-week, double-blind, placebo-controlled (up to Week 20) study (NCT00928512), patients responding inadequately to disease-modifying antirheumatic drugs (DMARD) or biologics were randomized to receive monthly subcutaneous injections of secukinumab (25, 75, 150, or 300 mg), or placebo. The efficacy and safety results up to Week 20 have been reported previously. Here, efficacy results from Week 20 to 52 and safety results from Week 20 to 60 are presented. RESULTS: Of 237 patients randomized, 174 (73.4%) completed the study. Patients with improved American College of Rheumatology (ACR) and 28-joint Disease Activity Score (DAS28) C-reactive protein (CRP) responses at Week 16 sustained their responses through Week 52. In patients taking 150 mg of secukinumab, responses were improved through Week 52 (ACR50: Week 16 = 45%, Week 52 = 55%; DAS28-CRP ≤ 2.6: Week 16 = 25%, Week 52 = 40%). The rate of adverse events (AE) from weeks 20 to 60 was 64.8%, with most AE being mild to moderate in severity. The overall rate of infections was 31.9%, most being mild. The most predominant infection was nasopharyngitis, and was not associated with dose or concurrent neutropenia. Serious AE were reported in 21 patients (8.9%). There were 3 reports of malignancies (ovarian, lung, basal cell), and no deaths between weeks 20 and 60. CONCLUSION: Patients with active RA who failed to respond to DMARD and other biologics showed an improvement after longterm treatment with 150 mg of secukinumab. The frequency of AE remained stable over time and secukinumab had a consistent safety profile over 60 weeks.
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 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 | 0.001 |
| 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) | 0.004 | 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".