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Background The KDIGO guidelines advocate the cause-GFR-albuminuria (CGA) classification for predicting outcomes. However, there is a dearth of data supporting the use of the cause of chronic kidney disease (CKD). This study aimed to address how to incorporate a prior biopsy-proven diagnosis in outcome prediction. Methods We examined the association of biopsy-proven kidney disease diagnoses with kidney failure with replacement therapy (KFRT) and all-cause death before KFRT in patients with various biopsy-proven diagnoses (n = 778, Analysis A) and patients with diabetes mellitus labeled with biopsy-proven diabetic nephropathy (DN), other biopsy-proven diseases, and no biopsy (n = 1117, Analysis B). Results In analysis A, adding biopsy-proven diagnoses to GFR-albuminuria (GA) classification improved prediction of 8-year incidence of KFRT and all-cause death significantly regarding integrated discrimination improvement and net reclassification index. Fine-Gray (FG) models with KFRT as a competing event showed significantly higher subdistribution hazard ratios (sHRs) for all-cause death in nephrosclerosis (4.12 [1.11–15.2]), focal segmental glomerulosclerosis (3.77 [1.09–13.1]), and membranous nephropathy (MN) (2.91 [1.02–8.30]) than in IgA nephropathy, while Cox model failed to show significant associations. Crescentic glomerulonephritis had the highest risk of all-cause death (sHR 5.90 [2.05–17.0]). MN had a significantly lower risk of KFRT than IgA nephropathy (sHR 0.45, [0.24–0.84]). In analysis B, other biopsy-proven diseases had a lower risk of KFRT than biopsy-proven DN in the FG model, with death as a competing event (sHR 0.62 [0.39–0.97]). Conclusions The CGA classification is of greater value in predicting outcomes than the GA classification.

Biopsy-proven CKD etiology and outcomes: the Chronic Kidney Disease Japan Cohort (CKD-JAC) study