Effect of Treatment Changes on Health-Related Quality of Life in Canadian Children With Juvenile Idiopathic Arthritis: Results From ReACCh-Out and CAPRI
Bibliographic record
Abstract
Objective We assessed changes in health-related quality of life (HRQOL) in Canadian patients with juvenile idiopathic arthritis (JIA), comparing inception cohorts from 2017 to 2023 and 2005 to 2010. Methods We included newly diagnosed patients who completed the Juvenile Arthritis Quality of Life Questionnaire (JAQQ) at both enrollment and 1 year later. Mean changes in JAQQ domain scores from baseline to 1 year were compared between cohorts using Mann-Whitney U tests. Multivariable linear regression was used to adjust for baseline imbalances between the cohorts. We also compared changes in treatments, the Quality of My Life scale, arthritis pain, Childhood Health Assessment Questionnaire disability index, and physician and parent global assessments. Results We included 478 and 663 patients from the 2017-2023 and 2005-2010 cohorts, respectively. By 1 year, a greater proportion of patients in the 2017-2023 cohort had used conventional synthetic and biologic disease-modifying antirheumatic drugs compared to the 2005-2010 cohort (57.9% vs 46.2% and 27.2% vs 6.3%, respectively). Improvements in total JAQQ score from baseline to 1 year were similar between the 2017-2023 (0.97; 95% CI 0.85-1.09) and 2005-2010 (0.92; 95% CI 0.82-1.02) cohorts, with no significant difference observed across JAQQ domains. Pain scores, however, improved significantly (−2.07 vs −1.62, P = 0.03). After adjusting for baseline imbalances, greater improvements were observed in the 2017-2023 cohort for all JAQQ domains in patients with ≥ 5 active joints (β 0.28 for psychosocial to β 0.62 for gross motor). Conclusion First-year improvements in HRQOL measured by JAQQ were similar in the 2017-2023 and 2005-2010 cohorts, but adjustment for baseline imbalances suggests greater HRQOL improvements in those with more severe disease in the later cohort.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".