Vis enkel innførsel

dc.contributor.authorGlerup, Mia
dc.contributor.authorKessel, Christoph
dc.contributor.authorFoell, Dirk
dc.contributor.authorBerntson, Lillemor
dc.contributor.authorFasth, Anders
dc.contributor.authorMyrup, Charlotte
dc.contributor.authorNordal, Ellen Berit
dc.contributor.authorRypdal, Veronika Gjertsen
dc.contributor.authorRygg, Marite
dc.contributor.authorArnstad, Ellen Dalen
dc.contributor.authorPeltoniemi, Suvi
dc.contributor.authorAalto, Kristiina
dc.contributor.authorSchleifenbaum, Susanne
dc.contributor.authorHøllsberg, Malene Noer
dc.contributor.authorBilgrau, Anders Ellern
dc.contributor.authorHerlin, Troels
dc.date.accessioned2024-11-08T14:32:17Z
dc.date.available2024-11-08T14:32:17Z
dc.date.issued2024-09-05
dc.description.abstractObjectives - 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.<p> <p>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.<p> <p>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.<p> <p>Conclusion - Biomarkers indicating inflammation at baseline have the potential to improve evaluation of disease activity and prediction of long-term outcomes.en_US
dc.identifier.citationGlerup, Kessel, Foell, Berntson, Fasth, Myrup, Nordal, Rypdal, Rygg, Arnstad, Peltoniemi, Aalto, Schleifenbaum, Høllsberg, Bilgrau, Herlin. Inflammatory biomarkers predicting long-term remission and active disease in juvenile idiopathic arthritis: a population-based study of the Nordic JIA cohort. RMD Open. 2024;10(3)
dc.identifier.cristinIDFRIDAID 2299035
dc.identifier.doi10.1136/rmdopen-2024-004317
dc.identifier.issn2056-5933
dc.identifier.urihttps://hdl.handle.net/10037/35591
dc.language.isoengen_US
dc.publisherBMJ Publishing Groupen_US
dc.relation.journalRMD Open
dc.rights.holderCopyright 2024 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0en_US
dc.rightsAttribution-NonCommercial 4.0 International (CC BY-NC 4.0)en_US
dc.titleInflammatory biomarkers predicting long-term remission and active disease in juvenile idiopathic arthritis: a population-based study of the Nordic JIA cohorten_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)