Identification of clinical phenotypes in Behçet's syndrome using latent class analysis: a step toward precision medicine

Abstract

This study is the first to apply LCA for BS clinical phenotyping, providing a probabilistic classification that uncovers complex patient subgroups. Five latent classes were identified, with distinct clinical profiles, significant sex disparities, and varying therapeutic needs. These findings are crucial for advancing precision medicine in BS and ultimately improving patient outcomes.