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Morbidity and mortality in antiphospholipid syndrome based on cluster analysis: a 10-year longitudinal cohort study
Yusuke Ogata1, Yuichiro Fujieda1, Masanari Sugawara1
1Department of Rheumatology, Endocrinology and Nephrology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
Insights
Patients with antiphospholipid syndrome (APS) were classified into subgroups using cluster analysis. Cluster B, characterized by cardiovascular risks and arterial thrombosis, exhibited the poorest prognosis and highest mortality.
Area of Science:
- Rheumatology
- Immunology
- Clinical Medicine
Background:
- Antiphospholipid syndrome (APS) is an autoimmune disorder associated with aPL antibodies.
- Identifying patient subgroups with poor prognosis is crucial for effective management.
Purpose of the Study:
- To identify subgroups of APS patients with the poorest prognosis.
- To characterize these high-risk subgroups.
Main Methods:
- Longitudinal retrospective cohort study of 168 APS patients.
- Cluster analysis based on clinical data and aPL profiles.
- Events included thrombosis, severe bleeding, and mortality.
Main Results:
- Three patient subgroups were identified: Cluster A (secondary APS), Cluster B (cardiovascular risks and arterial thrombosis), and Cluster C (triple aPL positivity and venous thrombosis).
- Cluster B demonstrated a significantly higher frequency of adverse events and mortality compared to Clusters A and C.
Conclusions:
- Cluster analysis successfully identified APS patient subgroups with distinct prognoses.
- Patients in Cluster B, with accumulated cardiovascular risks and arterial thrombosis, face the poorest prognosis.
- Cardiovascular risk factors may exacerbate adverse events in APS patients.
Objective:
Using cluster analysis, to identify the subgroup of patients with APS with the poorest prognosis and clarify the characteristics of that subgroup.
Methods:
This is a longitudinal retrospective cohort study of APS patients. Using clinical data and the profile of aPL, cluster analysis was performed to classify the patients into subgroups. Events were defined as thrombosis, severe bleeding, and mortality.
Results:
A total of 168 patients with APS were included. Cluster analysis classified the patients into three subgroups; Cluster A (n = 61): secondary APS, Cluster B (n = 56): accumulation of cardiovascular risks and arterial thrombosis, Cluster C (n = 61): triple positivity of aPL and venous thrombosis. Cluster B showed significantly higher frequency of the events and higher mortality compared with the other clusters (P = 0.0112 for B vs A and P = 0.0471 for B vs C).
Conclusion:
Using cluster analysis, we clarified the characteristics of the APS patients with the poorest prognosis. Risk factors for cardiovascular disease may further increase events in patients with APS.
