BACKGROUND: Granulomatosis with polyangiitis (Wegener's) (GPA) and microscopic polyangiitis (MPA) are subgroups of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) defined historically by clinical and histological features. GPA and MPA are heterogeneous entities with overlapping phenotypes. To identify novel subgroupings, cluster analysis was used to explore the phenotypic spectrum of AAV. METHODS: This study used a dataset of patients newly diagnosed as having GPA and MPA enrolled in five clinical trials. One cluster model included nine clinical baseline variables as input variables, and a second cluster model additionally included ANCA specificities. The clustering process involved multiple correspondence analyses followed by hierarchical ascendant cluster analysis. The clinical relevance of the generated clusters was analysed by their summary characteristics and outcomes. RESULTS: The analyses involved data for 673 subjects: 396 (59%) with GPA and 277 (41%) with MPA. Both cluster models resulted in five partially redundant clusters of subjects, and the model including ANCA resulted in more pertinent separations. These clusters were named 'renal AAV with proteinase 3 (PR3)-ANCA' (40% of subjects), 'renal AAV without PR3-ANCA' (32%) and 'non-renal AAV' (12%), 'cardiovascular AAV' (9%) and 'gastrointestinal AAV' (7%). The five clusters had distinct death and relapse rates. On the basis of 4 variables, 651 subjects (97%) could be accurately allocated to 1 of the 5 classes. CONCLUSIONS: This analysis suggests that AAV encompasses five classes associated with different outcomes. As compared with the traditional GPA-MPA separation, this classification system may better reflect the phenotypic spectrum of AAV.
BACKGROUND:Granulomatosis with polyangiitis (Wegener's) (GPA) and microscopic polyangiitis (MPA) are subgroups of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) defined historically by clinical and histological features. GPA and MPA are heterogeneous entities with overlapping phenotypes. To identify novel subgroupings, cluster analysis was used to explore the phenotypic spectrum of AAV. METHODS: This study used a dataset of patients newly diagnosed as having GPA and MPA enrolled in five clinical trials. One cluster model included nine clinical baseline variables as input variables, and a second cluster model additionally included ANCA specificities. The clustering process involved multiple correspondence analyses followed by hierarchical ascendant cluster analysis. The clinical relevance of the generated clusters was analysed by their summary characteristics and outcomes. RESULTS: The analyses involved data for 673 subjects: 396 (59%) with GPA and 277 (41%) with MPA. Both cluster models resulted in five partially redundant clusters of subjects, and the model including ANCA resulted in more pertinent separations. These clusters were named 'renal AAV with proteinase 3 (PR3)-ANCA' (40% of subjects), 'renal AAV without PR3-ANCA' (32%) and 'non-renal AAV' (12%), 'cardiovascular AAV' (9%) and 'gastrointestinal AAV' (7%). The five clusters had distinct death and relapse rates. On the basis of 4 variables, 651 subjects (97%) could be accurately allocated to 1 of the 5 classes. CONCLUSIONS: This analysis suggests that AAV encompasses five classes associated with different outcomes. As compared with the traditional GPA-MPA separation, this classification system may better reflect the phenotypic spectrum of AAV.