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Model estimates likelihood of severe disease in patients with JIA
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Researchers have developed a prediction model to estimate the likelihood of severe disease in patients diagnosed with juvenile idiopathic arthritis, according to a recently published study.
Jaime Guzman, MD, MSc, of the British Columbia Children’s Hospital and the University of British Columbia, and colleagues assessed 609 children with juvenile idiopathic arthritis (JIA) and identified disease courses based on changes of five variables in 5 years and used this to estimate the probability of severe disease at diagnosis. The five variables were quality of life, pain, medication requirements, patient-reported side effects and active joint counts. Researchers scheduled an assessment of each variable at 0, 6, 12, 18, 24, 36, 48 and 60 months. For the study, they included patients who attended at least six of the assessments. To identify distinct disease courses, researchers used multivariable cluster analysis, coefficient of determination (r2) and silhouette statistics. They developed 100 candidate prediction models in random samples of 75% of the cohort and then tested the model’s reliability and accuracy in the other 25%.
Researchers found four distinct disease courses: mild (in 43.8% of patients), moderate (35.6%), severe controlled (9%) and severe persisting (11.5%). For the model, JIA category, active joint count and pattern of joint involvement at enrollment best predicted severe disease course for both controlled and persisting (C index = 0.87). In the model, 91% of children in the highest decile of risk experienced severe disease vs. 5% in the lowest decile. – by Will Offit
Disclosure: The researchers report no relevant financial disclosures.
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