A network meta-analysis of randomized controlled trials of biologics for rheumatoid arthritis: a Cochrane overview
Bibliographic record
Abstract
BACKGROUND: We sought to compare the benefits and safety of 6 biologics (abatacept, adalimumab, anakinra, etanercept, infliximab and rituximab) in patients with rheumatoid arthritis. METHODS: In this network meta-analysis, we included all completed and updated Cochrane reviews on biologics for rheumatoid arthritis. We included data from all placebo-controlled trials that used standard dosing regimens. The major outcomes were benefit (defined as a 50% improvement in patient- and physician-reported criteria of the American College of Rheumatology [ACR50]) and safety (determined by the number of withdrawals related to adverse events). We used mixed-effects logistic regression to carry out an indirect comparison of the treatment effects between biologics. RESULTS: Compared with placebo, biologics were associated with a clinically important higher ACR50 rate (odds ratio [OR] 3.35, 95% confidence interval [CI] 2.62-4.29) and a number needed to treat for benefit of 4 (95% CI 4-6). However, biologics were associated with more withdrawals related to adverse events (OR 1.39, 95% CI 1.13-1.71), with a number needed to treat for harm of 52 (95% CI 29-152). Anakinra was less effective than all of the other biologics, although this difference was statistically significant only for the comparison with adalimumab (OR 0.45, 95% CI 0.21-0.99) and etanercept (OR 0.34, 95% CI 0.14-0.81). Adalimumab, anakinra and infliximab were more likely than etanercept to lead to withdrawals related to adverse events (adalimumab OR 1.89, 95% CI 1.18-3.04; anakinra OR 2.05, 95% CI 1.27-3.29; and infliximab OR 2.70, 95% CI 1.43-5.26). INTERPRETATION: Given the limitations of indirect comparisons, anakinra was less effective than adalimumab and etanercept, and etanercept was safer than adalimumab, anakinra and infliximab. This summary of the evidence will help physicians and patients to make evidence-based choices about biologics for the treatment of rheumatoid arthritis.
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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 | 0.046 | 0.079 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.006 | 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; both teacher heads agree on what is shown here.
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".