Urine biomarkers of tubular injury do not improve on the clinical model predicting chronic kidney disease progression
- PMID: 28029431
- PMCID: PMC5362331
- DOI: 10.1016/j.kint.2016.09.003
Urine biomarkers of tubular injury do not improve on the clinical model predicting chronic kidney disease progression
Abstract
Few investigations have evaluated the incremental usefulness of tubular injury biomarkers for improved prediction of chronic kidney disease (CKD) progression. As such, we measured urinary kidney injury molecule-1, neutrophil gelatinase-associated lipocalin, N-acetyl-ß-D-glucosaminidase and liver fatty acid binding protein under highly standardized conditions among 2466 enrollees of the prospective Chronic Renal Insufficiency Cohort Study. During 9433 person-years of follow-up, there were 581 cases of CKD progression defined as incident end-stage renal disease or halving of the estimated glomerular filtration rate. Levels of the urine injury biomarkers, normalized for urine creatinine, were strongly associated with CKD progression in unadjusted Cox proportional hazard models with hazard ratios in the range of 7 to 15 comparing the highest with the lowest quintiles. However, after controlling for the serum creatinine-based estimated glomerular filtration rate and urinary albumin/creatinine ratio, none of the normalized biomarkers was independently associated with CKD progression. None of the biomarkers improved on the high (0.89) C-statistic for the base clinical model. Thus, among patients with CKD, risk prediction with a clinical model that includes the serum creatinine-based estimated glomerular filtration rate and the urinary albumin/creatinine ratio is not improved on with the addition of renal tubular injury biomarkers.
Keywords: chronic kidney disease; microalbuminuria; proteinuria.
Copyright © 2016 International Society of Nephrology. All rights reserved.
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Comment in
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Urinary biomarkers of tubular injury in chronic kidney disease.Kidney Int. 2017 Jan;91(1):21-23. doi: 10.1016/j.kint.2016.10.003. Kidney Int. 2017. PMID: 28003082
References
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- Fassett RG, Venuthurupalli SK, Gobe GC, et al. Biomarkers in chronic kidney disease: a review. Kidney Int. 2011;80:806–821. - PubMed
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