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Predictive Value of Urine Tubular Biomarkers on Kidney Outcomes: Observations from EMPA-KIDNEY
Greco B Malijan1, William G Herrington1,2, Parminder K Judge1,2
1Renal Studies Group, Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Background:
Urine tubular biomarkers have previously been associated with chronic kidney disease (CKD) progression independently of estimated glomerular filtration rate (eGFR) and albuminuria. We evaluated whether nine urine tubular biomarkers could improve prediction of kidney failure beyond serum creatinine and urine albumin-to-creatinine ratio among adults with CKD.
Methods:
Among 5100 participants in EMPA-KIDNEY, a randomized trial which assessed the effects of empagliflozin 10 mg versus matching placebo among patients with CKD at risk of progression, nine urine creatinine-indexed tubular biomarkers were measured including alpha-1 microglobulin, dickkopf-3, epidermal growth factor [EGF], interleukin-18, kidney injury molecule-1 [KIM-1], monocyte chemoattractant protein-1 [MCP-1], neutrophil gelatinase-associated lipocalin, uromodulin, and human cartilage glycoprotein-40. Outcomes were kidney disease progression ('treated kidney failure', renal death, or sustained ≥40% eGFR decline) and treated kidney failure (maintenance dialysis or kidney transplant). Relative to models based on the linear predictor of the kidney failure risk equation (KFRE), improvements in discrimination were estimated with further addition of the nine tubular biomarkers using absolute difference in Uno's C-index.
Results:
Over median 3.5 years of follow-up, 1191 participants experienced kidney disease progression and 461 experienced treated kidney failure. KFRE demonstrated excellent discrimination for treated kidney failure [C-index 0.858 (0.840,0.874)] and moderate discrimination for kidney disease progression [0.724 (0.705,0.743)]. Addition of three biomarkers (MCP-1, KIM-1, and EGF) most strongly associated with CKD outcomes yielded some further improvement in predicting kidney failure [absolute difference 0.014 (0.009,0.024)] and kidney disease progression [0.038 (0.026,0.053)]. Prediction of kidney outcomes were only slightly improved when further expanding from three to all ning tubular biomarkers.
Conclusion:
In a wide range of causes of CKD, adding three urine tubular biomarkers (MCP-1, KIM-1, EGF) to KFRE improves estimates of risk of CKD progression.
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