Impact of clinical domains other than arthritis on composite outcomes in psoriatic arthritis: comparison of treatment effects in the SEAM-PsA trial
Bibliographic record
Abstract
OBJECTIVE: We used the Study of Etanercept And Methotrexate in Combination or as Monotherapy in Subjects with Psoriatic Arthritis (SEAM-PsA) data set to examine the impact of presence of enthesitis, dactylitis, nail disease and/or psoriasis on treatment response in patients with early psoriatic arthritis (PsA). METHODS: This post hoc analysis evaluated the effect of baseline Spondyloarthritis Research Consortium of Canada (SPARCC) Enthesitis Index (EI), Leeds Enthesitis Index (LEI), Leeds Dactylitis Index (LDI), modified Nail Psoriasis Severity Index (mNAPSI) scores and body surface area (BSA) on composite outcomes of minimal disease activity (MDA) responses, Psoriatic Arthritis Disease Activity Score (PASDAS) low disease activity (LDA), PASDAS changes and Good Responses and Disease Activity Index for Psoriatic Arthritis (DAPSA) scores at Week 24. RESULTS: Overall, 851 patients completed the SEAM-PsA trial and were included in the analysis. Baseline enthesitis (SPARCC EI>0 vs SPARCC EI=0 or LEI>0 vs LEI=0) was not associated with improved outcomes. Baseline dactylitis (LDI>0 vs LDI=0) was positively associated with improved MDA (OR: 1.4, p=0.0457), PASDAS LDA (OR: 1.8, p=0.0014) and Good Responses (OR: 1.6, p=0.0101) and greater reductions in PASDAS (estimate: -0.9, p<0.0001) and DAPSA scores (estimate: -3.8, p=0.0155) at Week 24. Similarly, baseline nail disease (mNAPSI >1 vs mNAPSI≤1) was positively associated with improved MDA (OR: 1.8, p=0.0233) and PASDAS LDA (OR: 1.8, p=0.0168) responses and greater reduction in PASDAS (estimate: -0.7, p=0.0005) at Week 24. CONCLUSIONS: Results from our analysis suggest that presence of dactylitis and nail disease, but not enthesitis, are associated with improved outcomes in patients with early PsA who were treated with methotrexate and/or etanercept.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".