Leflunomide for the treatment of rheumatoid arthritis: a systematic review and metaanalysis.
Bibliographic record
Abstract
OBJECTIVE: To systematically review the evidence from clinical trials on the efficacy and toxicity of leflunomide for the treatment of active rheumatoid arthritis (RA). METHODS: We searched Medline, Embase, Current Contents, and the Cochrane Controlled Trial Register for human randomized controlled trials (RCT) and controlled clinical trials up to December 2001. We also hand-searched reference lists and conference proceedings and consulted content experts. Relative benefit (RB), and weighted mean differences or standardized mean differences with their 95% confidence interval (95% CI) were calculated. RESULTS: Six RCT totaling 2044 patients with RA were included in this review. Using specific criteria, all trials were considered of high methodological quality. Leflunomide improved the ACR20 response rate roughly 2 times over placebo both at 6 months (RB = 1.93, 95% CI 1.51, 2.47) and at 12 months (RB = 1.99, 95% CI 1.42, 2.77). Other clinical outcomes of disease activity and function and radiological scores were also significantly better for leflunomide patients than those taking placebo. No significant differences for most of the outcomes were observed between leflunomide and sulfasalazine (SSZ) or methotrexate (MTX). Adverse events were more common in the leflunomide group, but withdrawal rates were fewer than for placebo. Overall, withdrawal rates and adverse events in the leflunomide group were not different from SSZ or MTX. CONCLUSION: Leflunomide improves all clinical outcomes and delays radiographic progression at 6 and 12 months of RA treatment compared to placebo. Its efficacy and adverse events at 2 years of treatment are comparable to SSZ and MTX. Longterm efficacy and toxicity remain to be established.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 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) | 0.000 | 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".