Malignancy outcomes in patients with rheumatoid arthritis treated with abatacept and other disease-modifying antirheumatic drugs: Results from a 10-year international post-marketing study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the risk of malignancy (overall, breast, lung, and lymphoma) in patients with rheumatoid arthritis treated with abatacept, conventional synthetic (cs) disease-modifying antirheumatic drugs (DMARDs), and other biologic/targeted synthetic (b/ts)DMARDs in clinical practice. METHODS: Four international observational data sources were included: ARTIS (Sweden), RABBIT (Germany), FORWARD (USA), and BC (Canada). Crude incidence rates (IRs) per 1000 patient-years of exposure with 95% confidence intervals (CIs) for a malignancy event were calculated; rate ratios (RRs) were estimated and adjusted for demographics, comorbidities, and other potential confounders. RRs were then pooled in a random-effects model. RESULTS: Across data sources, mean follow-up for patients treated with abatacept (n = 5182), csDMARDs (n = 73,755), and other b/tsDMARDs (n = 37,195) was 3.0-3.7, 2.9-6.2, and 3.1-4.7 years, respectively. IRs per 1000 patient-years for overall malignancy ranged from 7.6-11.4 (abatacept), 8.6-13.2 (csDMARDs), and 5.0-11.8 (other b/tsDMARDs). IRs ranged from: 0-4.4, 0-3.3, and 0-2.5 (breast cancer); 0.1-2.8, 0-3.7, and 0.2-2.9 (lung cancer); and 0-1.1, 0-0.9, and 0-0.6 (lymphoma), respectively, for the three treatment groups. The numbers of individual cancers (breast, lung, and lymphoma) in some registries were low; RRs were not available. There were a few cases of lymphoma in some of the registries; ARTIS observed an RR of 2.8 (95% CI 1.1-6.8) with abatacept versus csDMARDs. The pooled RRs (95% CIs) for overall malignancy with abatacept were 1.1 (0.8-1.5) versus csDMARDs and 1.0 (0.8-1.3) versus b/tsDMARDs. CONCLUSIONS: This international, post-marketing observational safety study did not find any statistically significant increase in the risk of overall malignancies in pooled data in patients treated with abatacept compared with csDMARDs or with other b/tsDMARDs. Assessment of larger populations is needed to further evaluate the risks for individual cancers, especially lymphoma.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".