Treatment of Psoriatic Arthritis with Tumor Necrosis Factor Inhibitors: Longer-term Outcomes Including Enthesitis and Dactylitis with Golimumab Treatment in the Longterm Extension of a Randomized, Placebo-controlled Study (GO-REVEAL)
Bibliographic record
Abstract
OBJECTIVE: To assess longer-term outcomes, including enthesitis and dactylitis, in patients with active psoriatic arthritis (PsA), in a study of golimumab treatment. METHODS: Adult patients with active PsA were randomized to receive subcutaneous injections of placebo (n = 113), golimumab 50 mg (n = 146), or golimumab 100 mg (n = 146) every 4 weeks through Week 20. All patients received golimumab 50 mg or 100 mg from Week 24 onward. Entheses tenderness was scored in 15 body sites using the PsA-modified Maastricht Ankylosing Spondylitis Enthesitis Score (MASES). Dactylitis was assessed in 20 digits of the hands and feet. RESULTS: Among the 405 randomized patients, 77% presented with enthesitis and 34% dactylitis at baseline. At Week 24 of the placebo-controlled study phase, significant differences were observed between golimumab 50 mg and/or 100 mg and placebo for mean percent improvement in the PsA-modified MASES [46% (p < 0.001) and 52% (p < 0.001) vs 13%, respectively] and the dactylitis score [66% (p = 0.09) and 82% (p < 0.001) vs 28%, respectively]. By Week 52, improvements were maintained among patients randomized to receive golimumab (mean improvements of 54% for PsA-modified MASES and 77% for the dactylitis score). Those given placebo who had enthesitis or dactylitis at baseline and who crossed over to golimumab at Week 16 or 24 had somewhat less improvement at Week 52 (i.e., 39% for the PsA-modified MASES, 57% for dactylitis score). CONCLUSION: Treatment of PsA patients with the TNF inhibitor golimumab was effective across all components of disease, including enthesitis and dactylitis, and efficacy was maintained over longer-term followup.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".