This study applied cluster analysis to urinary biomarker profiles in IC/BPS patients, aiming to provide a new perspective on disease classification and its clinical relevance.

We retrospectively analyzed urine samples from 127 IC/BPS patients and 30 controls. Urinary levels of 10 inflammatory cytokines and 3 oxidative stress markers (8-OHdG, 8-isoprostane, and TAC) were quantified. K-means clustering was performed to identify biomarker-based patient subgroups, and associations with clinical characteristics and treatment outcomes within each cluster were examined.

IC/BPS patients exhibited significantly elevated urinary levels of Eotaxin, MCP-1, NGF, 8-OHdG, 8-isoprostane, and TAC compared to controls (all p < 0.05). K-means clustering identified four distinct subgroups. Cluster 4 characterized by the highest levels of inflammatory and oxidative stress biomarkers, comprised 85% ESSIC type 2 IC/BPS patients and exhibited the lowest VAS pain scores (2.8±2.3) and MBC (581.0±183.70 mL). Correlation analysis revealed distinct cluster-specific associations between biomarker levels and clinical parameters, including VAS pain score, MBC, the grade of glomerulation, and treatment outcomes (GRA). Notably, in Cluster 4, MIP-1β negatively correlated with GRA (r=-0.597, p=0.015), suggesting its potential role in predicting treatment response.

Applying K-means clustering to urine inflammatory and oxidative stress biomarkers provides a new perspective on disease classification, identifying IC/BPS subtypes with distinct clinical and biochemical characteristics. This approach may refine disease phenotyping and guide personalized treatment strategies in the future.