Comparative safety of biologic versus conventional synthetic DMARDs in rheumatoid arthritis with COPD: a real-world population study
Bibliographic record
Abstract
OBJECTIVES: Abatacept, a biologic DMARD, was associated with respiratory adverse events in a small subgroup of RA patients with chronic obstructive pulmonary disease (COPD) in a trial. Whether this potential risk is specific to abatacept or extends to all biologics and targeted synthetic DMARDs (tsDMARDs) is unclear. We assessed the risk of adverse respiratory events associated with biologic and tsDMARDs compared with conventional synthetic DMARDs (csDMARDs) among RA patients with concomitant COPD in a large, real-world cohort. METHODS: We used a prevalent new-user design to study RA patients with COPD in the US-based MarketScan databases. New users of biologic DMARDs and/or tsDMARDs were matched on time-conditional propensity scores to new users of csDMARDs. Adverse respiratory events were estimated using Cox models comparing current use of biologic/tsDMARDs with csDMARDs. RESULTS: The cohort included 7424 patients initiating biologic/tsDMARDs and 7424 matched patients initiating csDMARDs. The adjusted hazard ratio of hospitalized COPD exacerbation comparing biologic/tsDMARD vs csDMARD was 0.76 (95% CI: 0.55, 1.06), while it was 1.02 (95% CI: 0.82, 1.27) for bronchitis, 1.21 (95% CI: 0.92, 1.58) for hospitalized pneumonia or influenza and 0.99 (95% CI: 0.87, 1.12) for outpatient pneumonia or influenza. The hazard ratio of the combined end point of COPD exacerbation, bronchitis and hospitalized pneumonia or influenza was 1.04 (95% CI: 0.89, 1.21). CONCLUSION: In this large, real-world comparative safety study, biologic and tsDMARDs, including abatacept, were not associated with an increased risk of adverse respiratory events when compared with csDMARDs in patients with RA and COPD.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".