The efficacy of inhibiting tumour necrosis factor and interleukin 1 in patients with rheumatoid arthritis: a meta-analysis and adjusted indirect comparisons
Bibliographic record
Abstract
OBJECTIVE: New treatments that inhibit the cytokines tumour necrosis factor alpha (TNFalpha) and interleukin 1 (IL-1) in the treatment of rheumatoid arthritis have proven clinical effect against placebo and methotrexate (MTX) in several clinical trials in early and late-stage disease and different severity groups. Since there are no head-to-head randomized controlled trials directly comparing the currently available treatments, etanercept, adalimumab, infliximab or anakinra, we perform a meta-analysis that adjusts for differences between study characteristics, and allows indirect comparisons between treatments. METHODS: Thirteen trials of cytokine antagonists were included from a systematic review of the literature. They reported the primary outcome of American College of Rheumatology (ACR) response criteria at 6 months or beyond. Meta-analytical methods are used to quantify relative treatment effects, using the log odds ratio of an ACR20 or ACR50 response at 6 months, whilst adjusting for study-level variables. RESULTS: In each of the trials, cytokine treatment was efficacious in comparison with placebo or MTX. For each treatment, the inclusion of MTX in combination improved the response. After adjustment for study-level variables, we found TNFalpha antagonists to be more efficacious compared with anakinra (P < 0.05). Indirect comparisons between the three TNFalpha antagonists indicated no difference in efficacy. Sensitivity analysis using a different statistical model structure confirmed these results. CONCLUSION: When the outcome of interest is the probability of an ACR20 or ACR50 response at 6 months we found: (i) treatment with the IL-1 antagonist anakinra is better than placebo; (ii) for each treatment, the use of combination MTX improves the probability of response; (iii) treatment with any of the TNFalpha antagonists is better than with the IL-1 antagonist anakinra; and (iv) all drugs in the TNFalpha antagonist class are no different from each other.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| 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 | 0.001 |
| 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".