Anti-TNF Alpha and Risk of Lymphoma in Rheumatoid Arthritis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background and Objectives: Anti-tumor necrosis factor-alpha (TNF-α) agents are effective in treating rheumatoid arthritis (RA) but may entail a risk of lymphoma due to TNF-α’s role in immune surveillance. This systematic review and meta-analysis assesses the risk of lymphoma in patients with RA treated with anti-TNF agents versus patients treated with methotrexate and/or a placebo. Materials and Methods: The Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Embase, PubMed, and Google Scholar were systematically searched for relevant literature. Data were extracted and analyzed to determine risk ratios (RRs) and 95% confidence intervals (CIs), with heterogeneity assessed using I2 statistics. Methodological quality and risk of bias were assessed using the Cochrane Risk of Bias tool for randomized controlled trials (RCTs) and the Newcastle–Ottawa Scale for observational studies. Results: The search yielded 932 articles, 13 of which were retained for qualitative review and 12 for quantitative synthesis. Overall, the studies reviewed included 181,735 participants: 3772 from six RCTs and 177,963 from seven observational studies. The meta-analysis of RCTs revealed no significant difference in the risk of lymphoma between patients receiving anti-TNF-α therapy and patients on conventional treatments, with an overall RR of 1.43 (95% CI: 0.32–5.16) and I2 of 0%. Conversely, observational studies showed some variability, with an overall RR of 1.43 (95% CI: 0.59–3.47) and significant heterogeneity (I2 = 95%), whereas others indicated a potentially elevated risk of lymphoma in specific subgroups but had inconsistent results. Conclusions: The systematic and meta-analysis revealed no significant difference in the risk of lymphoma for patients with RA treated with anti-TNF-α agents versus conventional therapies. However, given the limitations of the studies included, additional research is needed to validate the results and explore potential risk factors contributing to the development of lymphoma in patients with RA.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.017 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| 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".