Clinical efficacy, radiographic and safety findings through 5 years of subcutaneous golimumab treatment in patients with active psoriatic arthritis: results from a long-term extension of a randomised, placebo-controlled trial (the GO-REVEAL study)
Bibliographic record
Abstract
OBJECTIVES: Assess golimumab's long-term efficacy/safety in psoriatic arthritis (PsA). METHODS: Adults with active PsA (≥3 swollen and tender joints, active psoriasis) were randomly assigned to subcutaneous placebo, golimumab 50 mg, or golimumab 100 mg every 4 weeks (q4wks) through wk20. All patients received golimumab 50 mg or 100 mg q4wks from wk24 forward. Methotrexate was allowed and taken by approximately half the patients. Findings through 5 years are reported herein. Efficacy assessments included ≥20% improvement in American College of Rheumatology (ACR20) response, C-reactive-protein-based, 28-joint-count Disease Activity Score (DAS28-CRP) response, ≥75% improvement in Psoriasis Area and Severity Index (PASI75) scores, and PsA-modified Sharp/van der Heijde scores (SHSs). RESULTS: 126/405 (31%) randomised patients discontinued treatment through wk252. Golimumab was effective in maintaining clinical improvement through year-5 (ACR20: 62.8-69.9%, DAS28-CRP: 75.2-84.9% for randomised patients; PASI75: 60.8-72.2% among randomised patients with ≥3% body surface area involvement) and inhibiting radiographic progression (mean changes in PsA-modified SHS: 0.1-0.3) among patients with radiographic data. While concomitant methotrexate did not affect ACR20/PASI75, it appeared to reduce radiographic progression. No new safety signals were identified. Antibodies-to-golimumab occurred in 1.8%/10.0% of patients with/without methotrexate). CONCLUSIONS: Long-term golimumab safety/efficacy in PsA was demonstrated through 5 years. TRIAL REGISTRATION NUMBER: NCT00265096.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.003 | 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".