Diagnosing a child presenting with symptoms suggesting Sjögren's disease: a tool for clinical practice.

Abstract

Childhood SjD (cSjD) is a rare disease. There are no widely accepted diagnostic or classification criteria for cSjD. To fill this gap, members from the CARRA Sjögren Disease Workgroup and the International Childhood Sjögren Disease Workgroup created a clinical diagnostic algorithm. This study evaluated the accuracy of this algorithm using an international cohort of participants with clinician-diagnosed cSjD. First, experts developed a cSjD diagnostic algorithm through a series of virtual workgroup meetings. Using the adult classification criteria as a framework, experts modified the algorithm through opinion and literature review. The group discussed and finalized each algorithm step by achieving majority rule. Then, R statistical software was used to evaluate each participant's disease status in the diagnostic algorithm via an international cohort of 300 cSjD cases. The diagnostic algorithm has three distinct clinical pathways representing the key clinical presentation in cSjD: parotitis, extraglandular manifestations, and sicca symptoms. The algorithm showed an overall sensitivity of 75% in the population that had enough data to complete at least one pathway of the algorithm (n = 100 filtered out of 300). The parotitis (70%) and sicca pathways (82%) had the highest sensitivity, and the extraglandular pathway (52%) had the lowest. As cSjD lacks a diagnostic strategy, this algorithm provides a clinical tool for evaluating children with cSjD-like symptoms. It performed well in an international cohort of cSjD, supporting the integration of this algorithm into clinical practice; however, its utility may be limited by low utilization of diagnostic testing in this population.