Determining Best Practices in Early Rheumatoid Arthritis by Comparing Differences in Treatment at Sites in the Canadian Early Arthritis Cohort
Bibliographic record
Abstract
OBJECTIVE: To determine site variation by comparing outcomes across sites in an early rheumatoid arthritis cohort. METHODS: Sites from the Canadian Early Arthritis Cohort database with at least 40 patients were studied. Comparisons were made among sites in change in 28-joint Disease Activity Score (DAS28), proportion of patients in DAS28 remission, and treatment strategies. RESULTS: The study included 1138 baseline patients at 8 sites, with baseline (SD) age 52 years (16.9); 72% women; 23% erosions; 54% ever smokers; 51% rheumatoid factor-positive; 37% anticitrullinated protein antibody-positive; disease duration 187 (203) days; DAS28 4.5 (1.4). Site had an effect on outcomes when adjusting for confounders. At 6 and 12 months, sites B and H, the 2 largest sites, had the best changes in DAS28 (-1.82 and -2.09, respectively, at 6 mos, and -2.27 for both at 12 mos; p < 0.001). Site H had the most patients in DAS28 remission at 6 months [64.5% compared to other sites that had from 34.1% to 51.7% (p < 0.001)], and at the last followup, sites B and H had the most in remission. Subcutaneous methotrexate was used more overall and earlier at sites B and H. Those sites used less steroid therapy, and site B had the second-highest use of triple disease-modifying antirheumatic drugs at any visit. Medications were increased more in 2 of the 3 smallest sites. Biologics were used by 9 months most in the smallest (50.0%) and then largest (19.6%) sites. CONCLUSION: Sites in an early inflammatory arthritis cohort yielded different outcomes. Better outcomes up to 12 months may result from initial treatment with early combination therapy and/or subcutaneous methotrexate.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".