Inflammatory biomarkers predicting long-term remission and active disease in juvenile idiopathic arthritis: a population-based study of the Nordic juvenile idiopathic arthritis (JIA) cohort
Authors' conclusion
Biomarkers indicating inflammation at baseline have the potential to improve evaluation of disease activity and prediction of long-term outcomes.
Study context
- Population
- Patients with JIA in the population-based Nordic JIA cohort, baseline and 18-year follow-up (FU)of 349 eligible
- Participants
- 236 patients
- Comparison
- Conventional prediction model vs extended model with 16 baseline biomarkers
- Outcome
- Prediction of disease activity and remission status by baseline serum biomarkers
- Follow-up
- 18-year FU
Methodological detailspopulation-based, longitudinal, multiplexed bead array assay, univariate and multivariate logistic regression
- Population-based
- Longitudinal
- Multiplexed bead array assay
- Univariate and multivariate logistic regression
Performance
As reported in the abstract
Prediction of active/inactive disease at 18-year FU: conventional model (gender, age, joint counts, ESR, CRP) vs extended model adding 16 baseline biomarkers
- Biomarker addition significantly improved prediction of activity/inactivity: AUC increased from 0.59 to 0.80
- p=0.02
Further findings
Baseline serum biomarkers in active vs inactive disease at 18-year FU
- Significantly higher baseline IL-1β, IL-6, IL-12p70, IL-13, MMP-3, S100A9 and S100A12 in patients with active disease
Strongest predictor of inactive disease (multiple regression) · 18 years after onset
- S100A9 was the strongest predictor of inactive disease
Original publication
Inflammatory biomarkers predicting long-term remission and active disease in juvenile idiopathic arthritis: a population-based study of the Nordic JIA cohort. RMD Open. Published 5 September 2024. doi:10.
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