Inflammatory biomarkers predicting long-term remission and active disease in juvenile idiopathic arthritis: a population-based study of the Nordic JIA cohort.

Abstract

Objectives: To assess the ability of baseline serum biomarkers to predict disease activity and remission status in juvenile idiopathic arthritis (JIA) at 18-year follow-up (FU) in a population-based setting.

Methods: Clinical data and serum levels of inflammatory biomarkers were assessed in the longitudinal population-based Nordic JIA cohort study at baseline and at 18-year FU. A panel of 16 inflammatory biomarkers was determined by multiplexed bead array assay. We estimated both univariate and multivariate logistic regression models on binary outcomes of disease activity and remission with baseline variables as explanatory variables.

Results: Out of 349 patients eligible for the Nordic JIA cohort study, 236 (68%) had available serum samples at baseline. We measured significantly higher serum levels of interleukin 1β (IL-1β), IL-6, IL-12p70, IL-13, MMP-3, S100A9 and S100A12 at baseline in patients with active disease at 18-year FU than in patients with inactive disease. Computing receiver operating characteristics illustrating the area under the curve (AUC), we compared a conventional prediction model (gender, age, joint counts, erythrocyte sedimentation rate, C reactive protein) with an extended model that also incorporated the 16 baseline biomarkers. Biomarker addition significantly improved the ability of the model to predict activity/inactivity at the 18-year FU, as evidenced by an increase in the AUC from 0.59 to 0.80 (p=0.02). Multiple regression analysis revealed that S100A9 was the strongest predictor of inactive disease 18 years after disease onset.

Conclusion: Biomarkers indicating inflammation at baseline have the potential to improve evaluation of disease activity and prediction of long-term outcomes.