Earlier Time to Remission Predicts Sustained Clinical Remission in Early Rheumatoid Arthritis — Results from the Canadian Early Arthritis Cohort (CATCH)
Bibliographic record
Abstract
OBJECTIVE: To evaluate the prevalence and predictive factors of sustained remission in an early rheumatoid arthritis (ERA) population. Predictive factors of sustained remission in ERA are unknown. We hypothesized that a short time to remission is an important predictor of sustained clinical remission. METHODS: Patients in the Canadian Early Arthritis Cohort were included. Remission was defined by Boolean-based American College of Rheumatology/European League Against Rheumatism clinical trial and clinical practice definitions and Simplified Disease Activity Index (SDAI). Logistic regression analysis identified predictors of sustained remission and influence of time to remission. RESULTS: Of 1840 patients, 633 (34%) achieved clinical trial remission, 759 (41%) clinical practice remission, and 727 (39%) SDAI remission. Over half of those meeting remission criteria achieved sustained remission based on clinical trial (55%), clinical practice (60%), and/or SDAI (58%). Corticosteroid use and lack of initial disease-modifying antirheumatic drug (DMARD) were associated with decreased probability of sustained remission, while initial combination DMARD increased this probability. Female sex, greater pain, and longer time to first remission made sustained remission less likely. CONCLUSION: Female sex, greater pain, and lack of initial DMARD therapy reduced the probability of sustained remission. A shorter time to remission is related to sustainability and supports striving for early remission.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".