Patient-reported wellbeing and clinical disease measures over time captured by multivariate trajectories of disease activity in individuals with juvenile idiopathic arthritis in the UK: a multicentre prospective longitudinal study

Abstract

Background: Juvenile idiopathic arthritis (JIA) is a heterogeneous disease, the signs and symptoms of which can be summarised with use of composite disease activity measures, including the clinical Juvenile Arthritis Disease Activity Score (cJADAS). However, clusters of children and young people might experience different global patterns in their signs and symptoms of disease, which might run in parallel or diverge over time. We aimed to identify such clusters in the 3 years after a diagnosis of JIA. The identification of these clusters would allow for a greater understanding of disease progression in JIA, including how physician-reported and patient-reported outcomes relate to each other over the JIA disease course.

Methods: In this multicentre prospective longitudinal study, we included children and young people recruited before Jan 1, 2015, to the Childhood Arthritis Prospective Study (CAPS), a UK multicentre inception cohort. Participants without a cJADAS score were excluded. To assess groups of children and young people with similar disease patterns in active joint count, physician's global assessment, and patient or parental global evaluation, we used latent profile analysis at initial presentation to paediatric rheumatology and multivariate group-based trajectory models for the following 3 years. Optimal models were selected on the basis of a combination of model fit, clinical plausibility, and model parsimony.

Finding: Between Jan 1, 2001, and Dec 31, 2014, 1423 children and young people with JIA were recruited to CAPS, 239 of whom were excluded, resulting in a final study population of 1184 children and young people. We identified five clusters at baseline and six trajectory groups 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 children and young people had high patient or parent global scores despite low or improving joint counts and physician global scores. Participants in these groups were older, and a higher proportion of them had enthesitis-related JIA and lower socioeconomic status, compared with those in other groups.

Interpretation: Almost one in four children and young people with JIA in our study reported persistent, high patient or parent global scores despite having low or improving active joint counts and physician's global scores. Distinct patient subgroups defined by disease manifestation or trajectories of progression could help to better personalise health-care services and treatment plans for individuals with JIA.

Funding: Medical Research Council, Versus Arthritis, Great Ormond Street Hospital Children's Charity, Olivia's Vision, and National Institute for Health Research.

Figure 1

Median cJADAS 10 components for each latent class at baseline AJC=active joint count. cJADAS 10=clinical Juvenile Arthritis Disease Activity Score with an active joint count up to ten. PGA=physician's global assessment. PGE=patient or parent global evaluation.

Figure 2

Mean active joint count, PGA, and PGE trajectories within six multivariate disease clusters of children and young people with JIA over 3 years after an initial presentation to paediatric rheumatology Error bands surrounding mean trajectories were constructed with use of the predict method for linear smoothed ggplots within R, version 3.6.1, stat_smooth function. JIA=juvenile idiopathic arthritis. PGA=physician's global assessment. PGE=patient or parent global evaluation.

Figure 3

Distribution of ILAR categories across the six cJADAS 10 multivariate trajectory groups ILAR=International League of Associations for Rheumatology. cJADAS 10= clinical Juvenile Arthritis Disease Activity Score with an active joint count up to ten. JIA=juvenile idiopathic arthritis. RF=rheumatoid factor.

Figure 4

Mapping from data-driven cross-sectional clusters at baseline (lower) to longitudinal clusters over the 3-year follow-up (upper) PGA=physician's global assessment. PGE=patient or parent global evaluation.