Treatment sequences and lines of therapy in rheumatoid arthritis: a real-world evaluation of retention and effectiveness
Bibliographic record
Abstract
OBJECTIVES: Many patients with rheumatoid arthritis (RA) do not maintain disease control or tolerance their first advanced therapy (AT), making subsequent treatment choices critical. This study described real-world patterns of sequential AT use and evaluate drug survival and effectiveness across multiple lines of therapy in a large Canadian RA cohort. METHOSD: Adult RA patients from the Ontario Best Practice Research Initiative (OBRI) who initiated AT between 2008 and 2023 were included. Drug survival was defined as time from initiation to discontinuation. Effectiveness was assessed using changes in Clinical Disease Activity Index (CDAI), achievement of minimal clinically important difference (MCID), low disease activity (LDA), and remission at 6 months. Outcomes were compared before and after 2010, the year treat-to-target (T2T) guidelines were introduced. Analyses were adjusted using propensity scores and multiple imputation for missing data. RESULTS: Among 2,449 patients, TNFi agents were the most common first-line AT. Drug survival decreased with each subsequent line. Patients initiating AT after 2010 had shorter treatment durations (median 7.63 vs. 12.2 years), reflecting more frequent switching under T2T strategies. First-line therapies showed greater CDAI improvement and higher MCID, LDA, and remission rates. Effectiveness declined in later lines but remained clinically meaningful. CONCLUSIONS: This study offers insights into real-world sequential AT use in Canadian RA care. First-line AT is associated with superior survival and effectiveness; however, subsequent therapies continue to provide important clinical benefits. These findings support the value of personalised sequential treatment strategies and highlight the need for further research to inform future RA management guidelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".