Effect of Time to Start of Biologic Therapy on Treatment Response in Childhood Arthritis: Results From the <scp>UCAN CAN</scp> ‐ <scp>DU</scp> Cohort
Bibliographic record
Abstract
OBJECTIVE: To estimate the effect of time from symptom onset to start of biologic treatment on achieving inactive arthritis within six months in a cohort of patients with juvenile idiopathic arthritis (JIA). METHODS: The international UCAN CAN-DU study prospectively enrolled patients with JIA across Canada and the Netherlands. A nested cohort study was performed and biologic-naive patients with nonsystemic JIA were included at the start of biologic therapy. The primary outcome was inactive arthritis at six months. Demographics, disease-related parameters, and treatment response were compared using (non)parametric tests among early (time symptom onset to biologic start: 0-6 months), intermediate (7-12 months), and late (13-24 months) treatment groups. A logistic regression model analyzed the effect of time to biologic start on the response at six months, adjusting for active joint count and physician global assessment. A graphical representation of the model was created. RESULTS: One hundred and thirty children with JIA were included (early: n = 35; intermediate: n = 46; late: n = 49), 66% were female, and the median age at symptom onset was 11.0 years. The proportion of patients that reach inactive arthritis in the early starters (83%) was significantly higher than in late starters (57%). For each month of delay to the start of biologic treatment, the adjusted odds of having active arthritis after six months of therapy was 1.09 (interquartile range: 1.02-1.17, P = 0.009). CONCLUSION: Early start of biologic therapies in patients with JIA was associated with a higher proportion of patients reaching inactive arthritis within six months, suggesting a window of opportunity to control disease activity.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".