Therapies for Active Rheumatoid Arthritis after Methotrexate Failure
Bibliographic record
Abstract
BACKGROUND: Few blinded trials have compared conventional therapy consisting of a combination of disease-modifying antirheumatic drugs with biologic agents in patients with rheumatoid arthritis who have active disease despite treatment with methotrexate--a common scenario in the management of rheumatoid arthritis. METHODS: We conducted a 48-week, double-blind, noninferiority trial in which we randomly assigned 353 participants with rheumatoid arthritis who had active disease despite methotrexate therapy to a triple regimen of disease-modifying antirheumatic drugs (methotrexate, sulfasalazine, and hydroxychloroquine) or etanercept plus methotrexate. Patients who did not have an improvement at 24 weeks according to a prespecified threshold were switched in a blinded fashion to the other therapy. The primary outcome was improvement in the Disease Activity Score for 28-joint counts (DAS28, with scores ranging from 2 to 10 and higher scores indicating more disease activity) at week 48. RESULTS: Both groups had significant improvement over the course of the first 24 weeks (P=0.001 for the comparison with baseline). A total of 27% of participants in each group required a switch in treatment at 24 weeks. Participants in both groups who switched therapies had improvement after switching (P<0.001), and the response after switching did not differ significantly between the two groups (P=0.08). The change between baseline and 48 weeks in the DAS28 was similar in the two groups (-2.1 with triple therapy and -2.3 with etanercept and methotrexate, P=0.26); triple therapy was noninferior to etanercept and methotrexate, since the 95% upper confidence limit of 0.41 for the difference in change in DAS28 was below the margin for noninferiority of 0.6 (P=0.002). There were no significant between-group differences in secondary outcomes, including radiographic progression, pain, and health-related quality of life, or in major adverse events associated with the medications. CONCLUSIONS: With respect to clinical benefit, triple therapy, with sulfasalazine and hydroxychloroquine added to methotrexate, was noninferior to etanercept plus methotrexate in patients with rheumatoid arthritis who had active disease despite methotrexate therapy. (Funded by the Cooperative Studies Program, Department of Veterans Affairs Office of Research and Development, and others; CSP 551 RACAT ClinicalTrials.gov number, NCT00405275.)
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 0.001 |
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".