Biopsy-proven CKD etiology and outcomes : the Chronic Kidney Disease Japan Cohort (CKD-JAC) study
© The Author(s) 2022. Published by Oxford University Press on behalf of the ERA..
BACKGROUND: The Kidney Disease: Improving Global Outcomes guidelines advocate the cause-glomerular filtration rate (GFR)-albuminuria (CGA) classification for predicting outcomes. However, there is a dearth of data supporting the use of the cause of chronic kidney disease. 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 the GFR-albuminuria (GA) classification improved the 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 [95% confidence interval (CI) 1.11-15.2)], focal segmental glomerulosclerosis [3.77 (95% CI 1.09-13.1)]} and membranous nephropathy (MN) [2.91 (95% CI 1.02-8.30)] than in immunoglobulin A nephropathy (IgAN), while the Cox model failed to show significant associations. Crescentic glomerulonephritis had the highest risk of all-cause death [SHR 5.90 (95% CI 2.05-17.0)]. MN had a significantly lower risk of KFRT than IgAN [SHR 0.45 (95% CI 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 (95% CI 0.39-0.97)].
CONCLUSIONS: The CGA classification is of greater value in predicting outcomes than the GA classification.
| Errataetall: |
ErratumIn: Nephrol Dial Transplant. 2022 Oct 19;37(11):2296. - PMID 36007962 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:38 |
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| Enthalten in: |
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association - 38(2023), 2 vom: 13. Feb., Seite 384-395 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Hamano, Takayuki [VerfasserIn] |
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| Links: |
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| Themen: |
CKD |
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| Anmerkungen: |
Date Completed 14.02.2023 Date Revised 19.02.2023 published: Print ErratumIn: Nephrol Dial Transplant. 2022 Oct 19;37(11):2296. - PMID 36007962 Citation Status MEDLINE |
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| doi: |
10.1093/ndt/gfac134 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 100 | 1 | |a Hamano, Takayuki |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Biopsy-proven CKD etiology and outcomes |b the Chronic Kidney Disease Japan Cohort (CKD-JAC) study |
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| 500 | |a Date Revised 19.02.2023 | ||
| 500 | |a published: Print | ||
| 500 | |a ErratumIn: Nephrol Dial Transplant. 2022 Oct 19;37(11):2296. - PMID 36007962 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © The Author(s) 2022. Published by Oxford University Press on behalf of the ERA. | ||
| 520 | |a BACKGROUND: The Kidney Disease: Improving Global Outcomes guidelines advocate the cause-glomerular filtration rate (GFR)-albuminuria (CGA) classification for predicting outcomes. However, there is a dearth of data supporting the use of the cause of chronic kidney disease. This study aimed to address how to incorporate a prior biopsy-proven diagnosis in outcome prediction | ||
| 520 | |a 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) | ||
| 520 | |a RESULTS: In analysis A, adding biopsy-proven diagnoses to the GFR-albuminuria (GA) classification improved the 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 [95% confidence interval (CI) 1.11-15.2)], focal segmental glomerulosclerosis [3.77 (95% CI 1.09-13.1)]} and membranous nephropathy (MN) [2.91 (95% CI 1.02-8.30)] than in immunoglobulin A nephropathy (IgAN), while the Cox model failed to show significant associations. Crescentic glomerulonephritis had the highest risk of all-cause death [SHR 5.90 (95% CI 2.05-17.0)]. MN had a significantly lower risk of KFRT than IgAN [SHR 0.45 (95% CI 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 (95% CI 0.39-0.97)] | ||
| 520 | |a CONCLUSIONS: The CGA classification is of greater value in predicting outcomes than the GA classification | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a CKD | |
| 650 | 4 | |a diabetic kidney disease | |
| 650 | 4 | |a epidemiology | |
| 650 | 4 | |a kidney biopsy | |
| 650 | 4 | |a prognosis | |
| 700 | 1 | |a Imaizumi, Takahiro |e verfasserin |4 aut | |
| 700 | 1 | |a Hasegawa, Takeshi |e verfasserin |4 aut | |
| 700 | 1 | |a Fujii, Naohiko |e verfasserin |4 aut | |
| 700 | 1 | |a Komaba, Hirotaka |e verfasserin |4 aut | |
| 700 | 1 | |a Ando, Masahiko |e verfasserin |4 aut | |
| 700 | 1 | |a Nangaku, Masaomi |e verfasserin |4 aut | |
| 700 | 1 | |a Nitta, Kosaku |e verfasserin |4 aut | |
| 700 | 1 | |a Hirakata, Hideki |e verfasserin |4 aut | |
| 700 | 1 | |a Isaka, Yoshitaka |e verfasserin |4 aut | |
| 700 | 1 | |a Wada, Takashi |e verfasserin |4 aut | |
| 700 | 1 | |a Maruyama, Shoichi |e verfasserin |4 aut | |
| 700 | 1 | |a Fukagawa, Masafumi |e verfasserin |4 aut | |
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