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Updated: Aug 16, 2026
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Identification of novel clinical subtypes in patients with microscopic polyangiitis using cluster analysis:
Ayana Okazaki1, Shogo Matsuda1, Takuya Kotani1
1Department of Internal Medicine IV, Division of Rheumatology, Osaka Medical and Pharmaceutical University, Takatsuki, Japan.
Introduction:
This study aimed to identify new clinical phenotypes of microscopic polyangiitis (MPA) using a principal components analysis (PCA)-based cluster analysis.
Methods:
A total of 189 patients with MPA between May 2005 and December 2021 were enrolled from a multicenter cohort in Japan (REVEAL cohort). Categorical PCA and cluster analysis were performed based on clinical, laboratory, and radiological findings. Clinical characteristics and outcomes, including all-cause mortality, respiratory-related mortality, end-stage renal disease (ESRD), and relapse were compared between each cluster.
Results:
Eleven clinical variables were transformed into four components using categorical PCA and synthetic variables were created. Additionally, a cluster analysis was performed using these variables to classify patients with MPA into subgroups. Four distinct clinical subgroups were identified: Cluster 1 included the renal involvements and diffuse alveolar hemorrhage (DAH)-dominant group (N=33). Cluster 2 comprised the elderly onset systemic inflammation group (N=75). Cluster 3 included patients in the younger-onset limited-organ disease group (N=45). Cluster 4 was comprised of an ILD-predominant group without kidney involvement (N=36). 61 patients died during follow-up, with 32 dying of respiratory-related causes. Additionally, 19 patients developed ESRD and 70 relapsed. Cluster 1 showed the worst ESRD-free survival and relapse rates, whereas Cluster 2 showed the worst overall survival and respiratory-related death-free survival rates among the four groups.
Conclusions:
Our study identified four unique subgroups with different MPA outcomes. Individualized treatments for each subgroup may be required to improve the prognosis of MPA.
