Effectiveness and Safety of Etanercept in Patients with Psoriatic Arthritis in a Canadian Clinical Practice Setting: The REPArE Trial
Bibliographic record
Abstract
OBJECTIVE: To describe the longterm effectiveness and safety of etanercept in Canadian patients with psoriatic arthritis (PsA), treated over 24 months in clinical practice. METHODS: Patients with active PsA (≥ 3 tender and ≥ 3 swollen joints) were recruited from 22 centers. Etanercept was administered at 50 mg/week subcutaneously. In addition to clinical assessment of skin and joint disease, conducted at baseline and at Months 6, 12, 18, and 24, regular patient interviews were conducted by telephone. Patient responses related to health status, disability, and work productivity were scored using the patient global assessment tool, the Health Assessment Questionnaire (HAQ), the Health and Labour Questionnaire (HLQ), and the Fatigue Severity Scale. RESULTS: Out of 110 patients, 71 (65%) maintained etanercept treatment through the end of our study. All clinical measures of disease severity, including joint tenderness/pain, joint swelling, and Psoriasis Area and Severity Index score, improved significantly between baseline and Month 6 of etanercept treatment and remained constant thereafter. By the end of our study, 79% of patients achieved a Psoriatic Arthritis Response Criteria response, and 56% of patients achieved a 0.5-point improvement on HAQ, indicating clinically significant improvement in disability; 14% of patients finished our study free of disability (HAQ = 0). Patients' work productivity and fatigue improved significantly in parallel with these clinical and functional improvements. CONCLUSION: Continuous treatment with etanercept over 2 years in a clinical setting improved clinical symptoms of PsA while reducing fatigue, improving work productivity, and ameliorating or eliminating disability.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".