Impact of dactylitis and enthesitis resolution on disease control in guselkumab-treated psoriatic arthritis patients with TNFi-IR: COSMOS <i>post hoc</i> analysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate guselkumab efficacy on dactylitis resolution (DR) and enthesitis resolution (ER), and their impact on subsequent disease control, in patients with active psoriatic arthritis (PsA) and prior inadequate response to tumour necrosis factor inhibitors (TNFi-IR). METHODS: In the Phase IIIb COSMOS trial, 285 adults with TNFi-IR PsA were randomized (2:1) to receive guselkumab 100 mg or placebo at Week (W)0, W4, then every 8 weeks until W44. The Dactylitis Severity Score (DSS) and Leeds Enthesitis Index (LEI) assessed dactylitis and enthesitis, respectively. This post hoc analysis evaluated associations between W24 DR or ER and W48 achievement of stringent disease control measures using logistic regression. RESULTS: At baseline, 103/285 (36.1%) patients had dactylitis (DSS ≥ 1) and 190/285 (66.7%) had enthesitis (LEI ≥ 1). Patients with dactylitis were more likely to have enthesitis, more joint (SJC/DAPSA) and skin involvement, higher PGA score and lower BMI vs those without dactylitis. Patients with enthesitis were more likely to be female, and have dactylitis, more joints affected (SJC/TJC/DAPSA) and worse physical functioning (HAQ-DI/SF-36 PCS) vs those without enthesitis. Greater proportions of guselkumab- vs placebo-treated patients achieved DR/ER (W24: 44.8%/39.7% vs 25.0%/18.8%); rates increased through W48 among guselkumab-randomized patients (67.2%/55.6%). W24 resolution was associated with W48 achievement of stringent measures, including ACR50/70, DAPSA LDA/remission, PASI100, PASDAS LDA/VLDA and MDA/VLDA (odds ratios: DR, 3.28-13.38; ER, 2.88-6.09). CONCLUSION: Guselkumab treatment resulted in high DR/ER rates through W48 in TNFi-IR PsA patients. W24 DR/ER was associated with W48 disease control, providing valuable insights for clinical decision-making based on W24 treatment responses.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| 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 | 0.001 | 0.001 |
| 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".