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Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Unsupervised Clustering of Membranoproliferative Glomerulonephritis and C3 Glomerulopathy Patients Discovers Distinct
Marja Kovala1, Minna Seppälä2, Mikolaj Wojnicki3
1Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Introduction:
Membranoproliferative glomerulonephritis is currently divided into immunoglobulin-mediated glomerulonephritis (IC-MPGN) and C3 glomerulopathy (C3G); however, the patients often overlap with histology, complement, clinical and prognostic factors. Our aim was to investigate if an unsupervised clustering method finds different patient groups in 44 IC-MPGN/C3G patients using only histological and clinical data available in everyday clinical work.
Methods:
Primary IC-MPGN/C3G adult patients were included whose diagnostic (baseline) native biopsy was obtained in 2006-2017. The biopsies were reassessed and the clinical data at baseline and during follow-up were obtained from the medical records. There were 39 baseline histological and clinical variables included in the unsupervised clustering. Follow-up information was combined with the clustering results.
Results:
The clustering resulted in two clusters (n = 24 and n = 20 patients for clusters 1-2, respectively), where cluster 1 had a significantly higher baseline plasma creatinine (mean 213 vs. 104, respectively, p value <0.001) and a lower baseline eGFR than cluster 2 (mean 37 vs. 70, respectively, p value <0.001). Regarding histology, chronic changes such as lobulated glomeruli, mesangial matrix expansion, and glomeruli double contours were more prevalent in cluster 1 (p value <0.001). Biopsy morphology was more often crescentic and membranoproliferative in cluster 1 (p value <0.001). Although the differences were insignificant, cluster 1 patients were in dialysis in the last follow-up or had a progressive disease more often than cluster 2 patients (21% vs. 5%, 38% vs. 10%).
Conclusions:
Our results indicate that these patients share greater similarity than the current classification IC-MPGN versus C3G indicates.

