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Published on: June 18, 2020
Unsupervised Clustering Identifies High-Risk Phenotypic Subgroup in Crescentic Glomerulonephritis Patients
Yaoyao Tang1,2, Huiyu Liu1,2, Jianwen Yu1,2
1Department of Nephrology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Insights
This study developed a new risk stratification system for crescentic glomerulonephritis (cGN) patients, identifying high-risk groups for improved overall survival prediction and a renal risk score for end-stage renal disease (ESRD) prediction.
Area of Science:
- Nephrology
- Internal Medicine
- Clinical Epidemiology
Background:
- Current crescentic glomerulonephritis (cGN) classification focuses on renal outcomes, with controversial ability to predict overall patient survival.
- Need for improved risk stratification for both overall survival and end-stage renal disease (ESRD) in cGN patients.
Purpose of the Study:
- To develop a risk stratification system for overall survival in cGN.
- To validate a renal risk score for predicting ESRD in cGN patients.
Main Methods:
- Retrospective analysis of 224 cGN patients.
- Utilized K-means clustering, principal component analysis, and decision tree analysis.
- Primary outcome: all-cause mortality; Secondary outcome: ESRD.
Main Results:
- K-means clustering identified high-risk and low-risk groups with significantly different 10-year survival rates (63.1% vs. 89.6%, p=0.004).
- High-risk status independently predicted mortality (HR=3.28).
- A cGN kidney risk score (serum creatinine, normal glomeruli percentage, tubular atrophy/interstitial fibrosis) independently predicted ESRD (p<0.001).
Conclusions:
- Identified two distinct survival risk groups in cGN.
- Developed a novel renal risk score for ESRD prediction.
- The developed risk stratification system provides comprehensive information for clinical management of cGN.
Introduction:
The current classification of crescentic glomerulonephritis (cGN) primarily focuses on renal outcomes; its ability to predict overall patient survival remains controversial. This study aims to develop a risk stratification system for overall survival and validate a renal risk score for predicting end-stage renal disease (ESRD) in cGN.
Methods:
We retrospectively analyzed 224 cGN patients from the First Affiliated Hospital of Sun-Yat Sen University, with a median follow-up of 87.10 (interquartile range: 32.35, 153.97) months. The primary outcome was all-cause mortality, and the secondary outcome was ESRD. K-means clustering, principal component analysis, and decision tree analysis were used to identify patient groups.
Results:
Traditional classification showed that type III cGN patients had the poorest overall survival rates, whereas type I had the poorest renal survival. K-means clustering stratified patients into high-risk (n = 142) and low-risk (n = 82) groups with 10-year survival rates of 63.1% versus 89.6% (p = 0.004). High-risk status independently predicted mortality (HR = 3.28, 95% CI: 1.56-6.87, p = 0.002). The cGN kidney risk score consisting of serum creatinine levels, the percentage of normal glomeruli, and tubular atrophy/interstitial fibrosis independently predicted ESRD (p < 0.001, HR = 1.10, 95% CI: 1.06-1.13). A decision tree based on age, serum C3, serum creatinine, albumin, 24-h proteinuria, and fibrous crescents percentage accurately identified high-risk patients in the development and validation sets.
Conclusions:
We identified two survival risk groups and developed a renal risk score in cGN patients, providing an informative and comprehensive risk stratification to facilitate the clinical management.
