The effects of tumour necrosis factor inhibitors, methotrexate, non-steroidal anti-inflammatory drugs and corticosteroids on cardiovascular events in rheumatoid arthritis, psoriasis and psoriatic arthritis: a systematic review and meta-analysis
Bibliographic record
Abstract
The objective of this systematic literature review was to determine the association between cardiovascular events (CVEs) and antirheumatic drugs in rheumatoid arthritis (RA) and psoriatic arthritis (PsA)/psoriasis (Pso). Systematic searches were performed of MEDLINE, EMBASE and Cochrane databases (1960 to December 2012) and proceedings from major relevant congresses (2010-2012) for controlled studies and randomised trials reporting confirmed CVEs in patients with RA or PsA/Pso treated with antirheumatic drugs. Random-effects meta-analyses were performed on extracted data. Out of 2630 references screened, 34 studies were included: 28 in RA and 6 in PsA/Pso. In RA, a reduced risk of all CVEs was reported with tumour necrosis factor inhibitors (relative risk (RR), 0.70; 95% CI 0.54 to 0.90; p=0.005) and methotrexate (RR, 0.72; 95% CI 0.57 to 0.91; p=0.007). Non-steroidal anti-inflammatory drugs (NSAIDs) increased the risk of all CVEs (RR, 1.18; 95% CI 1.01 to 1.38; p=0.04), which may have been specifically related to the effects of rofecoxib. Corticosteroids increased the risk of all CVEs (RR, 1.47; 95% CI 1.34 to 1.60; p<0.001). In PsA/Pso, systemic therapy decreased the risk of all CVEs (RR, 0.75; 95% CI 0.63 to 0.91; p=0.003). In RA, tumour necrosis factor inhibitors and methotrexate are associated with a decreased risk of all CVEs while corticosteroids and NSAIDs are associated with an increased risk. Targeting inflammation with tumour necrosis factor inhibitors or methotrexate may have positive cardiovascular effects in RA. In PsA/Pso, limited evidence suggests that systemic therapies are associated with a decrease in all CVE risk.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".