Outcomes with Biological Disease-Modifying Anti-Rheumatic Drugs (bDMARDs) in Older Patients Treated for Rheumatoid Arthritis
Bibliographic record
Abstract
Background Biological disease-modifying antirheumatic drugs (bDMARDs) are recommended for rheumatoid arthritis (RA), but older patients reportedly experience more adverse events (AEs) and show variable treatment response. The objective of this study was to evaluate AEs and effectiveness of bDMARDs in a cohort of older patients. Methods AE and treatment effectiveness (based on DAS28 scores) data from a prospective provincial pharmacovigilance program for the years 2006–2009 in patients 55–64, 65–74, and 75+ years of age were compared. An intention to treat analysis with chisquare and unpaired t-testing for significance was performed. Results There were a total of 333 patients (156 were aged 55–64, 125 were 65–74, 52 were 75+). Those 75+ had higher disease activity and worse functional status at baseline. Among those 75+, AEs with bDMARDs were more common and likely to lead to discontinuation of therapy, be graded as severe, and classified as infectious (p < .05). Remission rate among those 75+ was significantly higher than patients 65–74. Etanercept was the most commonly used drug in all age groups. Conclusion Patients 75+ treated with bDMARDs are at a significantly greater risk of AEs, including infectious ones. The higher remission found in the oldest age group warrants further study.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".