A Tale of Many Canadas: Associations of Ancestry With Juvenile Idiopathic Arthritis Categories and Disease Severity at Presentation to Care
Bibliographic record
Abstract
Objective To assess associations of ancestry with juvenile idiopathic arthritis (JIA) categories and clinical Juvenile Arthritis Disease Activity Scores (cJADAS10) at presentation to pediatric rheumatology care in a multicultural country with universal health care. Methods Parents reported their child's ancestry in the Research in Arthritis in Canadian Children Emphasizing Outcomes (ReACCh‐Out) cohort. For each ancestry reported for ≥30 children, we compared JIA category distribution and median cJADAS10 scores among three groups: only that ancestry, with that and other ancestries, and without that ancestry. Chi‐square, Fisher's exact, and Kruskal‐Wallis tests compared the three groups and multivariable linear regression assessed factors associated with cJADAS10 scores. Results Among 1,407 participants, 629 (44.7%) reported more than one ancestry. British ancestry was associated with higher median cJADAS10 scores (7.5) and higher frequency of enthesitis‐related arthritis (18.7%) and psoriatic arthritis (10.0%), French ancestry was associated with lower cJADAS10 scores (5.8) and higher oligoarthritis (51.2%), Indigenous ancestry was associated with higher cJADAS10 scores (11.0) and higher rheumatoid factor–positive polyarthritis (21.9%), Black ancestry was associated with higher rheumatoid factor–positive polyarthritis (16.0%), and Eastern European ancestry was associated with lower cJADAS10 scores (3.6). Associations of ancestry with cJADAS10 scores were largely explained by differences in JIA categories (total R2 = 0.28, with R2 = 0.25 for JIA category alone). Black ancestry was associated with longer time from symptom onset to diagnosis (27 vs 18.9 weeks). Conclusions British and French ancestries had distinct associations with JIA categories and cJADAS10 scores, and many children had multiple ancestries, questioning the use of a single “European” reference group. Higher cJADAS10 scores were largely explained by differences in JIA categories across ancestries. image
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 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".