Advances and Challenges in the Classification of Childhood Arthritis

Abstract

The most appropriate classification of childhood arthritis remains controversial. Several efforts have been made over the years to devise classification systems that identify homogeneous subgroups within the disease spectrum. Although widely used, the International League of Associations for Rheumatology (ILAR) classification has shown major limitations as it was found to have failed its primary goal of identifying homogeneous disease categories. Furthermore, its use of the count of affected joints and of the presence of psoriatic features to define individual disease subsets has been criticized. A novel classification system has been proposed by the Pediatric Rheumatology International Trials Organization (PRINTO) through expert consensus. The preliminary scheme is currently being scrutinized by means a large-scale data collection aimed to formulate an evidence-based classification, whose results will likely be available in 2024. The development of a clinicobiologic classification has been tried in a proof-of-concept study by integrating meaningful biologic and clinical characteristics, including levels of proinflammatory cytokines and measures of disease activity, that defined indicators or composite variables capable of identifying homogeneous patient subgroups by cluster analysis. The current advance in biotechnology, especially genomics, proteomics and transcriptomics, may pave the way to the future identification of well-defined clusters of patients that will inform a biology-based and data-driven classification system. However, any attempt to defining biologic subtypes should be combined with precise clinical and prognostic data in order to devise a rational classification that facilitates the progress towards personalized management of children with JIA. Furthermore, the observed variability in the prevalence of disease subtypes across geographic areas and ethnic groups must be taken into account to develop a classification that is applicable on a global scale.