Safety and Effectiveness of 6 Months’ Etanercept Monotherapy and Combination Therapy in Japanese Patients with Rheumatoid Arthritis: Effect of Concomitant Disease-modifying Antirheumatic Drugs
Bibliographic record
Abstract
OBJECTIVE: To assess real-world safety, tolerability, and effectiveness of etanercept monotherapy, etanercept plus methotrexate (MTX), or etanercept plus other disease-modifying antirheumatic drugs (DMARD) in Japanese patients with active rheumatoid arthritis (RA) despite previous treatment with DMARD. METHODS: In this 24-week, all-cases postmarketing surveillance study, adverse events (AE) were coded using the Medical Dictionary for Regulatory Activities. Effectiveness was assessed every 4 weeks using the 28-joint Disease Activity Score and the European League Against Rheumatism response criteria. RESULTS: Of 13,861 patients (81% women) in the analysis, 3616, 2506, and 7739, respectively, were classified into etanercept monotherapy (ETN-mono), etanercept plus DMARD other than MTX (ETN + DMARD), and etanercept plus MTX (ETN + MTX) groups. Rates of AE and serious AE (SAE) in the ETN + MTX group were lower than in other groups. Risk of SAE or serious infections was not significantly increased with higher versus lower MTX doses at baseline or with concomitant use of salazosulfapyridine or bucillamine in ETN + DMARD versus ETN-mono groups. A greater likelihood of achieving clinical remission was seen with ETN + MTX versus ETN-mono (OR 1.36; 95% CI, 1.16-1.60; p < 0.001). Higher MTX dose at baseline was associated with a higher remission rate (> 8 mg vs 0 to ≤ 4 mg, OR 1.47, 95% CI 1.07-2.00, p = 0.016; 6 to ≤ 8 mg vs 0 to ≤ 4 mg, OR 1.27, 95% CI 1.01-1.60, p = 0.038). CONCLUSION: Combination therapies with etanercept plus MTX or other DMARD were reasonably well tolerated, and ETN + MTX at higher doses was more effective than ETN-mono in Japanese patients with 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 | 0.002 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".