Stern Sara M, Basiaga Matthew L, Cha Seunghee, Thatayatikom Akaluck, Treemacki Erin B, Randell Rachel L, Dizon Brian L P, Appenzeller Simone, Edens Cuoghi, Orrock Janet E, Tiger Sharon, Diianni Jamie, Amoafo Linda, Lieberman Scott M
Department of Pediatrics, University of Utah, Salt Lake City, UT, USA.
Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, USA.
Rheumatology (Oxford). 2025 May 1;64(5):3039-3047. doi: 10.1093/rheumatology/keae640.
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.
儿童干燥综合征（cSjD）是一种罕见疾病。目前尚无被广泛接受的cSjD诊断或分类标准。为填补这一空白，儿童关节炎与风湿病研究联盟（CARRA）干燥综合征工作组和国际儿童干燥综合征工作组的成员创建了一种临床诊断算法。本研究使用一个国际队列中经临床医生诊断为cSjD的参与者来评估该算法的准确性。
首先，专家们通过一系列虚拟工作组会议制定了cSjD诊断算法。以成人分类标准为框架，专家们通过意见和文献综述对算法进行了修改。该小组通过多数决讨论并最终确定了算法的每一步。然后，使用R统计软件通过一个包含300例cSjD病例的国际队列来评估诊断算法中每个参与者的疾病状态。
该诊断算法有三条不同的临床路径，代表了cSjD的关键临床表现：腮腺炎、腺外表现和干燥症状。在有足够数据完成算法至少一条路径的人群中（300例中筛选出100例），该算法的总体敏感性为75%。腮腺炎路径（70%）和干燥症状路径（82%）的敏感性最高，腺外表现路径（52%）的敏感性最低。
由于cSjD缺乏诊断策略，该算法为评估有cSjD样症状的儿童提供了一种临床工具。它在一个国际cSjD队列中表现良好，支持将该算法整合到临床实践中；然而，其效用可能受到该人群诊断检测利用率低的限制。
