Background: Drug-induced Acute Kidney Injury (AKI) develops in 10-15% of patients who receive nephrotoxic medications. Urinary biomarkers of renal tubular dysfunction may detect nephrotoxicity early and predict AKI.
Methods: We prospectively studied patients who received aminoglycosides, vancomycin, amphotericin, or calcineurin inhibitors, and collected their serial urine while on therapy. Patients who developed drug-induced AKI (fulfilling KDIGO criteria) were matched with non-AKI controls in a 1:2 ratio. Their urine samples were batch-analyzed at time-intervals leading up to AKI onset; the latter benchmarked against the final day of nephrotoxic therapy in non- AKI controls. Biomarkers examined include clusterin, beta-2-microglobulin, KIM1, MCP1, cystatin-C, trefoil-factor- 3, NGAL, interleukin-18, GST-Pi, calbindin, and osteopontin; biomarkers were normalized with corresponding urine creatinine.
Results: Nine of 84 (11%) patients developed drug-induced AKI. Biomarkers from 7 AKI cases with pre-AKI samples were compared with those from 14 non-AKI controls. Corresponding mean ages were 55(±17) and 52(±16) years; baseline eGFR were 99(±21) and 101(±24) mL/min/1.73m2 (all p=NS). Most biomarker levels peaked before the onset of AKI. Median levels of 5 biomarkers were significantly higher in AKI cases than controls at 1-3 days before AKI onset (all µg/mmol): clusterin [58(8-411) versus 7(3-17)], beta-2-microglobulin [1632(913-3823) versus 253(61-791)], KIM1 [0.16(0.13-0.76) versus 0.07(0.05-0.15)], MCP1 [0.40(0.16-1.90) versus 0.07(0.04-0.17)], and cystatin-C [33(27-2990) versus 11(7-19)], all p<0.05; their AUROC for AKI prediction were >0.80 (confidence intervals >0.50), with average accuracy highest for clusterin (86%), followed by beta-2-microglobulin, cystatin-C, MCP1, and KIM1 (57%) after cross-validation.
Conclusion: Serial surveillance of these biomarkers could improve the lead time for nephrotoxicity detection by days.
[http://dx.doi.org/10.1136/bmj.38028.520995.63] [PMID: 14996699]
[http://dx.doi.org/10.1128/AAC.02829-14] [PMID: 24957831]
[http://dx.doi.org/10.1016/j.transproceed.2004.01.021] [PMID: 15041343]
[http://dx.doi.org/10.1046/j.1523-1755.2002.00433.x] [PMID: 12081583]
[http://dx.doi.org/10.1093/ndt/18.3.543] [PMID: 12584277]
[http://dx.doi.org/10.1056/NEJM198005153022002] [PMID: 6988713]
[http://dx.doi.org/10.1007/s00441-009-0913-8] [PMID: 20063012]
[http://dx.doi.org/10.1172/JCI34487] [PMID: 18414680]
[http://dx.doi.org/10.1053/j.ajkd.2015.07.025] [PMID: 26362696]
[http://dx.doi.org/10.7326/0003-4819-150-9-200905050-00006] [PMID: 19414839]
[http://dx.doi.org/10.1055/s-0035-1563714] [PMID: 26344007]
[http://dx.doi.org/10.1371/journal.pone.0043809] [PMID: 22937100]
[http://dx.doi.org/10.1002/cpt.606] [PMID: 28002630]
[http://dx.doi.org/10.1016/j.vascn.2013.11.003] [PMID: 24333954]
[http://dx.doi.org/10.1080/1071576031000061002] [PMID: 12747731]
[http://dx.doi.org/10.1038/ki.2010.463] [PMID: 21150870]
[http://dx.doi.org/10.1186/cc12503] [PMID: 23388612]
[http://dx.doi.org/10.1016/j.taap.2016.04.012] [PMID: 27105553]
[http://dx.doi.org/10.1016/j.taap.2017.10.010] [PMID: 29051111]
[http://dx.doi.org/10.1177/0192623312444765] [PMID: 22581811]