ACPA and RF as predictors of sustained clinical remission in patients with rheumatoid arthritis: data from the Ontario Best practices Research Initiative (OBRI)
Bibliographic record
Abstract
Objective(s) This study evaluated the interaction of anticitrullinated protein antibody (ACPA) and rheumatoid factor (RF) in predicting sustained clinical response in an observational registry of patients with rheumatoid arthritis (RA) followed in routine practice. Methods Patients with RA enrolled in the Ontario Best Practices Research Initiative registry, with ≥1 swollen joint, autoantibody information and ≥1 follow-up assessment were included. Sustained clinical remission was defined as Clinical Disease Activity Index (CDAI) ≤2.8 in at least two sequential visits separated by 3–12 months. Time to sustained remission was assessed using cumulative incidence curves and multivariate cox regression. Results Among 3251 patients in the registry, 970 were included, of whom 262 (27%) were ACPAneg/RFneg, 60 (6.2%) ACPApos /RFneg, 117 (12.1%) ACPAneg/RFpos and 531 (54.7%) ACPApos /RFpos at baseline. Significant between group differences were observed in age (p=0.02), CDAI (p=0.03), tender joint count (p=0.02) and Health Assessment Questionnaire (p=0.002), with ACPApos patients being youngest with lowest disease activity and disability. No difference in biologic use was found between groups (20.2% of patients). Over a mean follow-up of 3 years, sustained remission was achieved by 43.5% of ACPApos/RFpos patients, 43.3% of ACPApos /RFneg patients, 31.6 % of ACPAneg/RFpos patients and 32.4% of ACPAneg/RFneg patients (p=0.01). Significant differences were observed in CDAI improvement based on ACPA and RF status where ACPApos/RFpos had a shorter time to achieving sustained remission (HR 1.30; 95% CI 1.01 to 1.67) and experienced significantly higher improvements compared with ACPAneg/RFneg patients. Conclusion(s) Combined ACPA and RF positivity were associated with improved and faster response to antirheumatic medications in patients with RA.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".