Work

Modified histopathological classification with age-related glomerulosclerosis for predicting kidney survival in ANCA-associated glomerulonephritis

Year: 2022

Type: article

Abstract: Background The histopathological classification of ANCA-GN divides patients into four groups based on signs of glomerular injury. However, this classification did not consider age-related glomerulosclerosis. In this study, we aimed to compare the prediction of renal survival between Berden's ANCA-GN histopathological classification and ANCA-GN histopathological classification modified with age-related glomerulosclerosis. Methods Between January 2004 and December 2019, 65 patients diagnosed with ANCA-GN were enrolled. Demographic, laboratory, and histopathologic findings were retrospectively analyzed. Renal survival analyzes were compared according to classical and modified ANCA-GN histopathological classifications. The multivariate Cox regression analysis for the factors affecting renal survival was performed. Results In Berden's ANCA-GN histopathological classification, 15 patients were in the focal group, 21 in the crescentic, 21 in the sclerotic, and 8 in the mixed group. The ANCA-GN histopathological classification model generated statistically significant predictions for renal survival (p = 0.022). When the histopathological classification was modified with age-related glomerulosclerosis, 8 of the 9 patients previously classified in the sclerotic group were classified in the mixed and 1 in the crescentic groups. Modification of histopathological classification with age-related glomerulosclerosis increases the statistical significance in renal survival analysis (p = 0.009). The multivariate Cox regression analysis showed that the disease-related global sclerotic glomeruli percentage and serum creatinine level were the significant independent factors. Conclusion Modification of Berden's ANCA-GN histopathological classification model with age-related glomerulosclerosis may increase the statistical significance of the histopathological classification model.

Source: International Urology and Nephrology

DOI: 10.1007/s11255-022-03371-6