Observational Studies of Infections in Rheumatoid Arthritis: A Metaanalysis of Tumor Necrosis Factor Antagonists
Bibliographic record
Abstract
OBJECTIVE: Published metaanalyses of tumor necrosis factor (TNF) antagonists and infection have focused on randomized controlled trials, which tend to have short duration, relatively small size, and stringent inclusion/exclusion criteria that may limit enrollment to patients at low risk of infection. We performed a systematic review and synthesis of observational studies of TNF antagonists and infection risk. METHODS: We conducted a systematic literature search of studies estimating overall risk of serious infection after anti-TNF exposure in rheumatoid arthritis (RA). We estimated a pooled relative risk (RR) for the relevant observational studies, using a random-effects model. RESULTS: Five cohort studies and 2 nested case-control studies were included in the metaanalysis. Anti-TNF therapy appeared to significantly increase risk of serious infection (pooled adjusted RR 1.37, 95% CI 1.18, 1.60). CONCLUSION: Our metaanalysis of observational data demonstrated an increased risk of serious infection in subjects with RA receiving anti-TNF therapy, versus those not receiving these agents.
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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 | 0.021 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".