Rheumatology (Oxford, England) · 2020
Derivation of an angiographically based classification system in Takayasu's arteritis: an observational study from India and North America.
СтатьяМногоцентровое исследованиеНаблюдательное исследованиеПоддержка NIH: внешняя программаResearch Support, N.I.H., IntramuralНазвание и аннотация: Перевод в очереди
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Goel Ruchika, Gribbons K Bates, Carette Simon, Cuthbertson David, Hoffman Gary S, Joseph George, Khalidi Nader A, Koening Curry L, Kumar Sathish, Langford Carol, Maksimowicz-McKinnon Kathleen, McAlear Carol A, Monach Paul A, Moreland Larry W, Nair Aswin, Pagnoux Christian, Quinn Kaitlin A, Ravindran Raheesh, Seo Philip, Sreih Antoine G, Warrington Kenneth J, Ytterberg Steven R, Merkel Peter A, Danda Debashish, Grayson Peter C
Аннотация
OBJECTIVES: To develop and replicate, using data-driven methods, a novel classification system in Takayasu's arteritis based on distribution of arterial lesions.
METHODS: Patients were included from four international cohorts at major academic centres: India (Christian Medical College Vellore); North America (National Institutes of Health, Vasculitis Clinical Research Consortium and Cleveland Clinic Foundation). All patients underwent whole-body angiography of the aorta and branch vessels, with categorization of arterial damage (stenosis, occlusion or aneurysm) in 13 territories. K-means cluster analysis was performed to identify subgroups of patients based on pattern of angiographic involvement. Cluster groups were identified in the Indian cohort and independently replicated in the North American cohorts.
RESULTS: A total of 806 patients with Takayasu's arteritis from India (n = 581) and North America (n = 225) were included. Three distinct clusters defined by arterial damage were identified in the Indian cohort and replicated in each of the North American cohorts. Patients in cluster one had significantly more disease in the abdominal aorta, renal and mesenteric arteries (P < 0.01). Patients in cluster two had significantly more bilateral disease in the carotid and subclavian arteries (P < 0.01). Compared with clusters one and two, patients in cluster three had asymmetric disease with fewer involved territories (P < 0.01). Demographics, clinical symptoms and clinical outcomes differed by cluster.
CONCLUSION: This large study in Takayasu's arteritis identified and replicated three novel subsets of patients based on patterns of arterial damage. Angiographic-based disease classification requires validation by demonstrating potential aetiological or prognostic implications.
METHODS: Patients were included from four international cohorts at major academic centres: India (Christian Medical College Vellore); North America (National Institutes of Health, Vasculitis Clinical Research Consortium and Cleveland Clinic Foundation). All patients underwent whole-body angiography of the aorta and branch vessels, with categorization of arterial damage (stenosis, occlusion or aneurysm) in 13 territories. K-means cluster analysis was performed to identify subgroups of patients based on pattern of angiographic involvement. Cluster groups were identified in the Indian cohort and independently replicated in the North American cohorts.
RESULTS: A total of 806 patients with Takayasu's arteritis from India (n = 581) and North America (n = 225) were included. Three distinct clusters defined by arterial damage were identified in the Indian cohort and replicated in each of the North American cohorts. Patients in cluster one had significantly more disease in the abdominal aorta, renal and mesenteric arteries (P < 0.01). Patients in cluster two had significantly more bilateral disease in the carotid and subclavian arteries (P < 0.01). Compared with clusters one and two, patients in cluster three had asymmetric disease with fewer involved territories (P < 0.01). Demographics, clinical symptoms and clinical outcomes differed by cluster.
CONCLUSION: This large study in Takayasu's arteritis identified and replicated three novel subsets of patients based on patterns of arterial damage. Angiographic-based disease classification requires validation by demonstrating potential aetiological or prognostic implications.