Effect of Adherence to Protocolized Targeted Intensifications of Disease-modifying Antirheumatic Drugs on Treatment Outcomes in Rheumatoid Arthritis: Results from an Australian Early Arthritis Cohort
Bibliographic record
Abstract
OBJECTIVE: To investigate the association between adherence to treat-to-target (T2T) protocol and disease activity, functional outcomes, and radiographic outcomes in early rheumatoid arthritis (RA). METHODS: Data from a longitudinal cohort of patients with early RA were used. Adherence was determined at each followup visit over 3 years according to predefined criteria. The primary endpoint was remission according to Disease Activity Score in 28 joints (DAS28) and Simplified Disease Activity Index (SDAI) criteria. Functional and radiographic outcomes measured by modified Health Assessment Questionnaire and modified total Sharp score, respectively, were secondary endpoints. RESULTS: A total of 198 patients with 3078 clinic visits over 3 years were included in this analysis. After adjusting for relevant variables, although there was no significant association between adherence to T2T and remission rate after 1 year, the associations reached significance after 3 years for both DAS28 (OR 1.71, 95% CI 1.16-2.50; p = 0.006) and SDAI criteria (OR 1.94, 95% CI 1.06-3.56; p = 0.033). After 3 years, adherence was also associated with improvement in physical function (β=0.12, 95% CI 0.06-0.18; p < 0.0001). None of the radiographic outcomes were associated with adherence after either 1 or 3 years, although there was a trend for higher adherence to be associated with less radiographic progression at the end of the study (p = 0.061). CONCLUSION: Increased adherence to T2T was associated with better longterm disease activity and functional outcomes, which suggests that the benefit of a T2T protocol may be enhanced by ensuring adequate adherence.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".