Derivation of an angiographically based classification system in Takayasu's arteritis: an observational study from...

Area of Science:

• Vascular Medicine
• Rheumatology
• Medical Imaging

Background:

• Takayasu arteritis is a rare, chronic inflammatory disease affecting large arteries, primarily the aorta and its branches.
• Current classification systems for Takayasu arteritis may not fully capture the heterogeneity of disease presentation and progression.
• A data-driven approach is needed to refine classification based on objective measures of arterial involvement.

Purpose of the Study:

• To develop and validate a novel classification system for Takayasu arteritis using data-driven methods.
• To identify distinct patient subgroups based on the distribution and pattern of arterial lesions.
• To replicate the identified subgroups across independent international cohorts.

Main Methods:

• Whole-body angiography was performed on 806 patients across Indian and North American cohorts.
• Arterial damage (stenosis, occlusion, aneurysm) was categorized in 13 territories.
• K-means cluster analysis was employed to identify patient subgroups based on angiographic patterns.

Main Results:

• Three distinct clusters of Takayasu arteritis patients were identified and replicated.
• Cluster one showed predominant involvement of the abdominal aorta, renal, and mesenteric arteries.
• Cluster two exhibited bilateral disease in carotid and subclavian arteries, while cluster three had asymmetric disease with fewer involved territories.
• Demographics, clinical symptoms, and outcomes varied significantly across the three clusters.

Conclusions:

• This study successfully identified and replicated three novel patient subsets in Takayasu arteritis based on angiographic patterns of arterial damage.
• The proposed classification system provides a data-driven framework for understanding disease heterogeneity.
• Further validation is required to explore the aetiological and prognostic implications of these identified subsets.