Treatment patterns in rheumatoid arthritis after discontinuation of methotrexate: data from the Ontario Best Practices Research Initiative (OBRI).
Bibliographic record
Abstract
OBJECTIVES: In active rheumatoid arthritis (RA) patients with inadequate response to methotrexate (MTX), guidelines support adding or switching to another conventional synthetic disease-modifying anti-rheumatic drug (csDMARD) and/or a biologic DMARD (bDMARD). The purpose of this analysis was to describe treatment practices in routine care and to evaluate determinants of regimen selection after MTX discontinuation. METHODS: Biologic-naïve patients in the Ontario Best Practice Research Initiatives registry discontinuing MTX due to primary/secondary failure, adverse events, or patient/physician decision were included. RESULTS: Of 313 patients discontinuing MTX, 102 (32.6%) were on MTX monotherapy, 156 (49.8%) on double, and 55 (17.6%) on multiple csDMARDs. Patients on MTX monotherapy were older than patients on double or multiple csDMARDs (p=0.013), less likely to have joint erosions (p=0.009) and had lower patient global assessment (p=0.046) at MTX discontinuation. Post-MTX discontinuation, 169 (54.0%) transitioned to, or added new DMARD(s) (new csDMARD(s): 139 [44.4%]; bDMARD: 30 [9.6%]), and 144 (46.0%) opted for no new DMARD treatment. Patients on MTX monotherapy transitioning monotherapy, whereas patients on combination csDMARDs switched more to new csDMARDs and bDMARD combination therapy. Early RA (adjOR [95%CI]: 3.07 [1.40-6.72]) and treatment with multiple csDMARDs vs. MTX monotherapy (4.15 [1.35-12.8]) at MTX discontinuation were significant predictors of transitioning to or adding new csDMARD(s)/bDMARD treatment versus opting for no new DMARD treatment. CONCLUSIONS: Differences in subsequent treatment patterns exist between patients discontinuing MTX when used as monotherapy versus in combination with other csDMARDs where the former are more likely to use a subsequent monotherapy treatment.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".