Improved Disease Course Associated With Early Initiation of Biologics in Polyarticular Juvenile Idiopathic Arthritis: Trajectory Analysis of a Childhood Arthritis and Rheumatology Research Alliance Consensus Treatment Plans Study
Bibliographic record
Abstract
OBJECTIVE: To investigate the effects of early introduction of biologic disease-modifying antirheumatic drugs (bDMARDs) on the disease course in untreated polyarticular juvenile idiopathic arthritis (JIA). METHODS: We analyzed data on patients with polyarticular JIA participating in the Start Time Optimization of Biologics in Polyarticular JIA (STOP-JIA) study (n = 400) and a comparator cohort (n = 248) from the Childhood Arthritis and Rheumatology Research Alliance Registry. Latent class trajectory modeling (LCTM) was applied to identify subgroups of patients with distinct disease courses based on disease activity (clinical Juvenile Arthritis Disease Activity Score in 10 joints) over 12 months from baseline. RESULTS: In the STOP-JIA study, 198 subjects (49.5%) received bDMARDs within 3 months of baseline assessment. LCTM analyses generated 3 latent classes representing 3 distinct disease trajectories, characterized by slow, moderate, or rapid disease activity improvement over time. Subjects in the rapid improvement trajectory attained inactive disease within 6 months from baseline. Odds of being in the rapid improvement trajectory versus the slow improvement trajectory were 3.6 times as high (95% confidence interval 1.32-10.0; P = 0.013) for those treated with bDMARDs ≤3 months from baseline compared with subjects who started bDMARDs >3 months after baseline, after adjusting for demographic characteristics, clinical attributes, and baseline disease activity. Shorter disease duration at first rheumatology visit approached statistical significance as a predictor of favorable trajectory without bDMARD treatment. CONCLUSION: Starting bDMARDs within 3 months of baseline assessment is associated with more rapid achievement of inactive disease in subjects with untreated polyarticular JIA. These results demonstrate the utility of trajectory analysis of disease course as a method for determining treatment efficacy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".