072. SECUKINUMAB PROVIDES SUSTAINED IMPROVEMENTS IN THE SIGNS AND SYMPTOMS OF ACTIVE PSORIATIC ARTHRITIS: 104 WEEKS RESULTS FROM A PHASE 3 TRIAL
Bibliographic record
Abstract
Background: Secukinumab, a fully human anti-IL-17A monoclonal antibody, significantly improved signs and symptoms of psoriatic arthritis (PsA) over 52 weeks in FUTURE 2 (NCT01752634); we now present Week 104 efficacy and safety data. Methods: Patients with active PsA (n = 397) were randomized to receive subcutaneous (s.c.) secukinumab (300, 150, 75 mg) or placebo at baseline, weekly Weeks 1–4 and every 4 weeks (q4w) thereafter. Placebo patients were rerandomized to secukinumab 300 or 150 mg s.c. q4w depending upon Week 16 ACR20 response; patients classified as responders (≥20% improvement from baseline in tender and swollen joint counts) switched at Week 24, non-responders at Week 16. Exploratory endpoints assessed at Week 104 were from patients originally randomized to secukinumab (Table 1). Data were assessed by mixed-model repeated measures for continuous variables; multiple imputation was applied to missing binary variables. Analyses stratified by anti-TNF-α status [naive or inadequate response/intolerance (IR)] were pre-specified and reported as observed. Safety analysis included all patients who received ≥1 doses of secukinumab; data are presented as exposure adjusted incidence rates (EAIR) per 100 patient-years over treatment period.
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 | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".