Effectiveness of sequential biologic and targeted disease modifying anti-rheumatic drugs for rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVES: Whether patients with RA benefit from repeated trials of biologic or targeted synthetic DMARDs (b/tsDMARDs) after three or more attempts is unknown. We aimed to describe treatment outcomes in each line of b/tsDMARD therapy. METHODS: Using data from the British Society for Rheumatology Biologics Register for RA from 2001 to 2020, change to a new b/tsDMARD (except biosimilar switches) was defined as a new line of therapy. Treatment outcomes were compared across lines of therapy, including DAS28 remission (≤2.6), low disease activity (LDA, ≤3.2) at 6 months and median time to drug discontinuation. Multiple imputation was used for missing data. RESULTS: A total of 22 934 individuals starting a first b/tsDMARD were included (mean age 56 years, 76% female), among whom 10 823 commenced a second-line drug, 5056 third, 2128 fourth, 767 fifth and 292 sixth. Most (71%) had sufficient data for DAS28-derived outcome analyses. TNF inhibitors were the most common first-line drug, but choice of subsequent-line drugs changed over time. Seventeen percent achieved DAS28 remission following first-line, 13% second and 8-13% with third through sixth. LDA was achieved in 29% of first-line, 23% second, 17-22% through to the sixth. Patients stayed on first-line therapy for a median of 2.6 years, ranging from 1.0-1.4 years for lines two to six. CONCLUSION: Many patients will eventually benefit after repeated trials of b/tsDMARD. Further research to improve treatment selection are needed to prevent prolonged trial and error approaches in some patients.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".