The Effect of Early Attainment of Minimal Disease Activity on Radiographic Outcomes: A Real-World Longitudinal Cohort Study in Psoriatic Arthritis
Bibliographic record
Abstract
Objective To evaluate the effect of achieving minimal disease activity (MDA) within the first year on radiologic damage at 3-year follow-up in patients with newly diagnosed psoriatic arthritis (PsA). Methods Data were used from the Dutch southwest Early PsA cohort, a real-world cohort of newly diagnosed patients with PsA, focusing on those with oligoarthritis or polyarthritis. Patients were stratified into 3 groups: (1) sustained MDA, achieving MDA at least at both 9 and 12 months post diagnosis; (2) nonsustained MDA, achieving MDA in the first year but not sustaining it at 9 and 12 months; (3) no MDA, not achieving MDA in the first year. Radiographic assessment was used by the modified Total Sharp/van der Heijde score for PsA. Group comparisons at 3-year follow-up for radiographic changes were conducted using a linear mixed model. Results Two hundred eighty-four patients were categorized into 3 groups: 96 patients (34%) in the sustained MDA group, 83 (29%) in the nonsustained MDA group, and 105 (37%) in the no-MDA group. According to baseline characteristics, in the no-MDA group, a notably higher rate of female individuals (70%) and an elevated tender joint count (median 7, IQR 4-12) were observed. Patients who did not achieve MDA in the first year experienced remarkably higher radiographic changes during follow-up than the sustained MDA group (β 0.05, 95% CI 0.02-0.08,P< 0.01). Conclusion Radiographic changes during the 3-year follow-up were markedly higher in those unable to achieve MDA within the first year of follow-up, emphasizing the long-term structural benefits of reaching stringent disease activity targets early in the disease course.
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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 | 0.006 | 0.014 |
| 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 | 0.001 |
| 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".