Patients with Moderate Rheumatoid Arthritis (RA) Achieve Better Disease Activity States with Etanercept Treatment Than Patients with Severe RA
Bibliographic record
Abstract
OBJECTIVE: This analysis examined clinical and radiographic responses to methotrexate (MTX), etanercept (ETN), and combination ETN and MTX in patients with moderate versus severe rheumatoid arthritis (RA) in both early and late disease. METHODS: Data from the Trial of Etanercept and Methotrexate With Radiographic Patient Outcomes (TEMPO) and the Early Rheumatoid Arthritis trials were used. Patients were classified with moderate or severe RA based on Disease Activity Score including 28-joint count (DAS28). Outcomes included DAS28 remission, DAS28 low disease activity, Health Assessment Questionnaire (HAQ), American College of Rheumatology (ACR) scores, Total Sharp Score (TSS) progression, no radiographic progression (annualized change in TSS > or = 0), change from baseline in TSS, and the change in TSS for patients who had radiographic progression (TSS > 0). RESULTS: Patients with moderate disease generally achieved better clinical outcomes than patients with severe disease, including significant differences in DAS28 remission, low disease activity, and HAQ < or =0.5 at Month 12. Patients with baseline severe disease had higher ACR and DAS responses than patients with moderate disease. CONCLUSION: Patients with severe RA disease activity achieved substantial clinical improvement with high-dose MTX and/or ETN treatment, but patients with moderate disease were more likely to reach a lower disease activity state. These findings were independent of disease duration. The results support the opportunity for excellent clinical outcomes, particularly with combination therapy, in patients with moderate RA.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".