Discriminative power of salivary gland ultrasound in relation to symptom-based endotypes in suspected and definite primary Sjögren's Syndrome
医学
内科学
痹症科
内型
胃肠病学
疾病
作者
Liselotte Deroo,Helena Achten,Kristel De Boeck,Eva Genbrugge,Wouter Bauters,Dimitri Roels,Frederick Dochy,David Creytens,Ann‐Sophie De Craemer,Filip Van den Bosch,Dirk Elewaut,Isabelle Peene
Salivary gland ultrasound (SGUS) is emerging as essential tool in primary Sjögren's Syndrome (pSS), but its link to symptom-based endotypes is unknown. Therefore, we explored SGUS outcomes in relation to endotypes in patients with definite and suspected pSS.Definite pSS patients (n = 171) fulfilling the 2016 ACR/EULAR classification criteria, and suspected pSS patients (n = 119), positive for at least one criterion, were included in the Belgian Sjögren's Syndrome Transition Trial (BeSSTT). Stratification into endotypes according to the Newcastle Sjögren's Stratification Tool resulted in low symptom burden (LSB), pain dominant with fatigue (PDF), dryness dominant with fatigue (DDF) and high symptom burden (HSB). SGUS was assessed with Hocevar score (0-48). The dataset was randomly divided into a discovery (n = 203) and replication (n = 87) cohort.SGUS had strong discriminative power for pSS classification (AUC=0.74), especially in DDF (AUC=0.89). In definite pSS, Hocevar scores in DDF were high compared to other endotypes (38 (20-44) versus 18 (9-33); p < 0.001). Patients with highest SGUS-scores showed more sicca and laboratory abnormalities. Moreover, a subset of young, anti-SSA/Ro positive patients not fulfilling classification criteria showed clear SGUS abnormalities. Replication showed similar results.SGUS-scores were significantly higher in definite pSS with DDF endotype, providing the first evidence of imaging abnormalities in salivary glands matching distinct biological profiles ascribed to pSS endotypes. Additionally, a subset of patients with potential early disease was detected based on presence of anti-SSA antibodies and high SGUS-scores. These results underscore the role of SGUS as powerful tool both in pSS classification and stratification.