Background: Juvenile idiopathic arthritis (JIA) is a heterogeneous disease whose signs and symptoms can be summarised using composite disease activity measures, including the clinical Juvenile Arthritis Disease Activity Score (cJADAS). This study aimed to identify global clusters of children and young people (CYP) who experience similar patterns across different individual disease features following diagnosis.
Methods: CYP recruited before January 2015 to the Childhood Arthritis Prospective Study, a UK, multicentre inception cohort, were included. Latent class analyses and multivariate group-based trajectory models explored groups of CYP with similar disease patterns in active joint count, physician’s global and patient/parental global evaluations at initial presentation to paediatric rheumatology, and during the following three years, respectively. Optimal models were selected based on a combination of model fit, clinical plausibility and model parsimony.
Finding: Among 1184 CYP, five clusters were identified at baseline and six trajectory groups were identified using longitudinal follow-up data. Disease course was not well predicted from clusters at baseline; however, in both cross-sectional and longitudinal analyses, substantial proportions of CYP experienced high patient/parent global scores despite low or improving joint counts and physician global scores. These groups were characterised by older age, enthesitis-related JIA and lower socioeconomic status.
Interpretation: Almost one in four CYP with JIA reported persistent, high patient/parent global scores despite low or improving active joint count and physician’s global scores. Distinct patient subgroups defined by disease manifestation or trajectories of progression could help better personalise healthcare services and treatment plans.