Data-Driven Clustering Approach to Identify Different Phenotypes of Primary Central Nervous System Vasculitis.

Background: To determine whether hierarchical unsupervised cluster analysis identifies a phenotypic distinction in adult patients with primary CNS vasculitis (PCNSV).

Methods: An agglomerative hierarchical cluster analysis based on the Ward method was conducted, including 153 patients with complete baseline phenotypic characterization in the COVAC' registry.

Results: The hierarchical analysis identified two main clusters. In Cluster 1 (n = 109 patients, 71%), patients more frequently had a motor deficit (p = 0.039), ≥ 1 acute brain infarct (p < 0.001), and ≥ 1 intracranial stenosis on CT or MR angiogram (p < 0.001) than patients in Cluster 2 (n = 44 patients, 29%). Conversely, patients in Cluster 2 more frequently had seizures (p < 0.001), cognitive impairment (p = 0.002), gadolinium-enhanced parenchymal lesions (p < 0.001), leptomeningeal enhancement (p < 0.001), ≥ 1 cerebral microbleed (p < 0.001), and intracranial hemorrhage(s) (p < 0.001). In multivariable logistic regression, gadolinium-enhanced parenchymal lesions were significantly associated with Cluster 2 lesions (OR = 35.53 [95% CI: 3.91-322.81], p = 0.002). Conversely, ≥ 1 acute brain infarct was significantly associated with Cluster 1 (OR = 0.003 [95% CI: 0.01-0.03], p < 0.001). A CNS biopsy was positive in 11/40 (28%) patients from Cluster 1 and 35/37 (95%) patients from Cluster 2 (p < 0.001). At 12 months, functional independence (modified Rankin scale score ≤ 2) did not differ between the two groups (p = 0.17). Relapse and mortality rates did not differ between the clusters (p = 0.17 and p = 0.23, respectively).

Conclusion: This unsupervised analysis of a large PCNSV cohort identified two different clinical and radiological phenotypes with different diagnostic work-ups, which confirms the relevance of distinguishing PCNSV phenotypes according to the sizes of affected vessels.