Identification of distinct subgroups of Sjögren's disease by cluster analysis based on clinical and biological manifestations... (2024) Nguyen et al.

Full title: Identification of distinct subgroups of Sjögren's disease by cluster analysis based on clinical and biological manifestations: data from the cross-sectional Paris-Saclay and the prospective ASSESS cohorts

Summary

Background

Sjögren's disease is a heterogenous autoimmune disease with a wide range of symptoms—including dryness, fatigue, and pain—in addition to systemic manifestations and an increased risk of lymphoma. We aimed to identify distinct subgroups of the disease, using cluster analysis based on subjective symptoms and clinical and biological manifestations, and to compare the prognoses of patients in these subgroups.

Methods

This study included patients with Sjögren's disease from two independent cohorts in France: the cross-sectional Paris-Saclay cohort and the prospective Assessment of Systemic Signs and Evolution of Sjögren's Syndrome (ASSESS) cohort. We first used an unsupervised multiple correspondence analysis to identify clusters within the Paris-Saclay cohort using 26 variables comprising patient-reported symptoms and clinical and biological manifestations. Next, we validated these clusters using patients from the ASSESS cohort. Changes in disease activity (measured by the European Alliance of Associations for Rheumatology [EULAR] Sjögren's Syndrome Disease Activity Index [ESSDAI]), patient-acceptable symptom state (measured by the EULAR Sjögren's Syndrome Patient Reported Index [ESSPRI]), and lymphoma incidence during follow-up were compared between clusters. Finally, we compared our clusters with the symptom-based subgroups previously described by Tarn and colleagues.

Findings

534 patients from the Paris-Saclay cohort (502 [94%] women, 32 [6%] men, median age 54 years [IQR 43–64]), recruited between 1999 and 2022, and 395 patients from the ASSESS cohort (370 [94%] women, 25 [6%] men, median age 53 years [43–63]), recruited between 2006 and 2009, were included in this study. In both cohorts, hierarchical cluster analysis revealed three distinct subgroups of patients: those with B-cell active disease and low symptom burden (BALS), those with high systemic disease activity (HSA), and those with low systemic disease activity and high symptom burden (LSAHS). During follow-up in the ASSESS cohort, disease activity and symptom states worsened for patients in the BALS cluster (67 [36%] of 186 patients with ESSPRI score <5 at month 60 vs 92 [49%] of 186 at inclusion; p<0·0001). Lymphomas occurred in patients in the BALS cluster (five [3%] of 186 patients; diagnosed a median of 70 months [IQR 42–104] after inclusion) and the HSA cluster (six [4%] of 158 patients; diagnosed 23 months [13–83] after inclusion). All patients from the Paris-Saclay cohort with a history of lymphoma were in the BALS and HSA clusters. This unsupervised clustering classification based on symptoms and clinical and biological manifestations did not correlate with a previous classification based on symptoms only.

Interpretation

On the basis of symptoms and clinical and biological manifestations, we identified three distinct subgroups of patients with Sjögren's disease with different prognoses. Our results suggest that these subgroups represent different heterogeneous pathophysiological disease mechanisms, stages of disease, or both. These findings could be of interest when stratifying patients in future therapeutic trials.

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INteresting. Is this approach to stratification/forming clusters something that might be relevant for ME/CFS? given they are talking about criteria within such groups (fatigue and dryness vs symptom clusters) that perhaps aren't biomarker-requiring but in this (and I haven't checked the significance of claims) apparently are linked to treatment effects of different medications/treatment plans?

Is a comparator with this, and the data available regarding progression/prognosis, symptoms, markers and things like lyphoma something that also offers a useful benchmark for what basics might be missing with regards ME/CFS clinics and management/monitoring?