Clinical Relevance and Predictive Value of Damage Biomarkers of Drug-Induced Kidney Injury

Sandra L. Kane-Gill (), Pamela L. Smithburger, Kianoush Kashani, John A. Kellum and Erin Frazee
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Sandra L. Kane-Gill: University of Pittsburgh
Pamela L. Smithburger: University of Pittsburgh
Kianoush Kashani: Mayo Clinic
John A. Kellum: University of Pittsburgh School of Medicine
Erin Frazee: Mayo Clinic

Drug Safety, 2017, vol. 40, issue 11, No 2, 1049-1074

Abstract: Abstract Nephrotoxin exposure accounts for up to one-fourth of acute kidney injury episodes in hospitalized patients, and the associated consequences are as severe as acute kidney injury due to other etiologies. As the use of nephrotoxic agents represents one of the few modifiable risk factors for acute kidney injury, clinicians must be able to identify patients at high risk for drug-induced kidney injury rapidly. Recently, significant advancements have been made in the field of biomarker utilization for the prediction and detection of acute kidney injury. Such biomarkers may have a role both for detection of drug-induced kidney disease and implementation of preventative and therapeutic strategies designed to mitigate injury. In this article, basic principles of renal biomarker use in practice are summarized, and the existing evidence for six markers specifically used to detect drug-induced kidney injury are outlined, including liver-type fatty acid binding protein, neutrophil gelatinase-associated lipocalin, tissue inhibitor of metalloproteinase-2 times insulin-like growth factor-binding protein 7 ([TIMP-2]·[IGFBP7]), kidney injury molecule-1 and N-acetyl-β-d-glucosaminidase. The results of the literature search for these six kidney damage biomarkers identified 29 unique articles with none detected for liver-type fatty acid binding protein and [TIMP-2]·[IGFBP7]. For three biomarkers, kidney injury molecule-1, neutrophil gelatinase-associated lipocalin and N-acetyl-β-d-glucosaminidase, the majority of the studies suggest utility in clinical practice. While many questions need to be answered to clearly articulate the use of biomarkers to predict drug-induced kidney disease, current data are promising.

Date: 2017
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DOI: 10.1007/s40264-017-0565-7

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