Evaluating a Child Presenting with Symptoms Concerning for Sjögren Disease: A Clinical Tool for Practice.

Background/purpose: Childhood Sjögren disease (cSjD) is a rare disease. There are no widely accepted diagnostic or classification criteria for cSjD. To fill this gap, members from CARRA Sjogren Workgroup and the International cSjD Workgroup created a clinical diagnostic algorithm. This study evaluates the accuracy of this algorithm using an international cohort of participants with clinician diagnosed cSjD.

Methods: 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 evaluated each participant's disease status in the diagnostic algorithm via an international cohort of 300 cSjD cases.

Results: The diagnostic algorithm has three distinct clinical pathways, which represents 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 1 pathway of the algorithm (n = 100 filtered out of 300). Parotitis (70%) and sicca pathways (82%) had the highest sensitivity and extraglandular pathways (52%) had the lowest.

Conclusion: 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.