Skip to main content

Kidney Damage and Stress Biomarkers for Early Identification of Drug-Induced Kidney Injury: A Systematic Review

Drug Safety volume 45, pages 839–852 (2022)Cite this article

Abstract

Introduction

Acute kidney injury (AKI) resulting from nephrotoxic medication use is prominent in hospitalized patients and is attributable to overall increases in mortality and costs of care. Serum creatinine (SCr), the current standard for identifying drug-induced AKI (DIAKI) is often delayed in its response to kidney insult by 26–36 h.

Objective

This systematic review seeks to evaluate the clinical utility of several novel kidney damage and stress biomarkers for the prediction/timely detection of DIAKI, in comparison with traditional methods.

Methods

A systematic review of the CINAHL, Cochrane Library, Embase, and PubMed databases was conducted per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, for articles analyzing the use of β2-microglobulin (B2M), interleukin (IL)-18, kidney injury molecule-1 (KIM-1), liver-type fatty acid-binding protein (L-FABP), neutrophil gelatinase-associated lipocalin (NGAL), and tissue inhibitor of metalloproteinase-2 * insulin-like growth factor-binding protein 7 [TIMP-1]*[IGFBP-7], for identifying DIAKI. Primary outcomes included time to DIAKI diagnosis using traditional methods and the time to significant difference in biomarker concentrations between DIAKI and non-AKI study subjects. Secondary outcomes included biomarker concentrations at the time of significant difference between the AKI status groups.

Results

Fifteen unique articles were identified from the literature search. Twelve studies consisted of strictly hospitalized patient populations and three studies included hospitalized patients and patients discharged to home treatment. No studies reported values for urine volume output. Seventy-three percent of studies reported earlier times to significant difference of novel biomarker concentrations between the AKI and non-AKI groups than diagnosis of DIAKI by SCr alone. Significant variation was observed for individual urine biomarker concentrations at time of significant difference between the AKI status groups.

Conclusions

All analyzed biomarkers showed potential for use as early clinical markers of DIAKI, however further consensus on threshold urine concentrations for DIAKI is needed for meaningful implementation of these biomarkers in clinical practice.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 49.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1

References

  1. Ghane Shahrbaf F, Assadi F. Drug-induced renal disorders. J Renal Injury Prev. 2015. https://doi.org/10.12861/jrip.2015.12.

    Article  Google Scholar 

  2. Kane-Gill SL, Smithburger PL, Kashani K, Kellum JA, Frazee E. Clinical relevance and predictive value of damage biomarkers of drug-induced kidney injury. Drug Saf. 2017. https://doi.org/10.1007/s40264-017-0565-7.

    Article  PubMed  Google Scholar 

  3. Mehta RL, Awdishu L, Davenport A, Murray PT, Macedo E, Cerda J, et al. Phenotype standardization for drug-induced kidney disease. Kidney Int. 2015. https://doi.org/10.1038/ki.2015.115.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Pazhayattil GS, Shirali AC. Drug-induced impairment of renal function. Int J Nephrol Renov Dis. 2014. https://doi.org/10.2147/IJNRD.S39747.

    Article  Google Scholar 

  5. Wang HE, Muntner P, Chertow GM, Warnock DG. Acute kidney injury and mortality in hospitalized patients. Am J Nephrol. 2012. https://doi.org/10.1159/000337487.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Silver SA, Chertow GM. The economic consequences of acute kidney injury. Nephron. 2017. https://doi.org/10.1159/000475607.

    Article  PubMed  Google Scholar 

  7. Dasta JF, Kane-Gill S. Review of the literature on the costs associated with acute kidney injury. J Pharm Pract. 2019. https://doi.org/10.1177/0897190019852556.

    Article  PubMed  Google Scholar 

  8. Abdelsalam M, Elmorsy E, Abdelwahab H, Algohary O, Naguib M, El Wahab AA, et al. Urinary biomarkers for early detection of platinum based drugs induced nephrotoxicity. BMC Nephrol. 2018. https://doi.org/10.1186/s12882-018-1022-2.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cox ZL, McCoy AB, Matheny ME, Bhave G, Peterson NB, Siew ED, et al. Adverse drug events during AKI and its recovery. Clin J Am Soc Nephrol. 2013. https://doi.org/10.2215/cjn.11921112.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Ostermann M, Joannidis M. Acute kidney injury 2016: diagnosis and diagnostic workup. Crit Care. 2016. https://doi.org/10.1186/s13054-016-1478-z.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Samra M, Abcar AC. False estimates of elevated creatinine. Permanente J. 2012. https://doi.org/10.7812/tpp/11-121.

    Article  Google Scholar 

  12. Ostermann M, Bellomo R, Burdmann EA, Doi K, Endre ZH, Goldstein SL, et al. Controversies in acute kidney injury: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Conference. Kidney Int. 2020. https://doi.org/10.1016/j.kint.2020.04.020.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Kashani K, Al-Khafaji A, Ardiles T, Artigas A, Bagshaw SM, Bell M, et al. Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit Care. 2013. https://doi.org/10.1186/cc12503.

    Article  PubMed  PubMed Central  Google Scholar 

  14. George B, Joy MS, Aleksunes LM. Urinary protein biomarkers of kidney injury in patients receiving cisplatin chemotherapy. Exp Biol Med. 2018. https://doi.org/10.1177/1535370217745302.

    Article  Google Scholar 

  15. Chui H, Caldwell J, Yordanova M, Cockovski V, Fredric D, Harel-Sterling M, et al. Tubular injury and cell-cycle arrest biomarkers to predict acute kidney injury in noncritically ill children receiving aminoglycosides. Biomark Med. 2020. https://doi.org/10.2217/bmm-2019-0419.

    Article  PubMed  PubMed Central  Google Scholar 

  16. De Chiara L, Lugli G, Villa G, Raglianti V, Husain-Syed F, Ravaglia F, et al. Molecular mechanisms and biomarkers associated with chemotherapy-induced AKI. Int J Mol Sci. 2022. https://doi.org/10.3390/ijms23052638.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Javan AO, Salamzadeh J, Shokouhi S, Sahraei Z. Evaluation of renal toxicity of colistin therapy with neutrophil gelatinase-associated lipocalin: a biomarker of renal tubular damage. Iran J Kidney Dis. 2017;11:447–53.

    Google Scholar 

  18. Gameiro J, Fonseca JA, Outerelo C, Lopes JA. Acute kidney injury: from diagnosis to prevention and treatment strategies. J Clin Med. 2020. https://doi.org/10.3390/jcm9061704.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Moorthie S. What is clinical utility? 2021. https://www.phgfoundation.org/explainer/clinical-utility. Accessed 12 May 2022.

  20. KDIGO. Acute kidney injury. 2012. https://kdigo.org/guidelines/acute-kidney-injury/. Accessed 11 May 2022.

  21. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, The PRISMA, et al. statement: an updated guideline for reporting systematic reviews. BMJ. 2020. https://doi.org/10.1136/bmj.n71.

    Article  PubMed  Google Scholar 

  22. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009. https://doi.org/10.1371/journal.pmed.1000100.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Moher D, Liberati A, Tetzlaff J, Altman DG, The PG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. PLoS Med. 2009. https://doi.org/10.1371/journal.pmed.1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016. https://doi.org/10.1186/s13643-016-0384-4.

    Article  PubMed  PubMed Central  Google Scholar 

  25. National Heart L, and Blood Institute Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. 2014. https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools. Accessed 1 May 2021.

  26. National Heart L, and Blood Institute. Quality Assesment of Controlled Intervention Studies 2014. https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools. Accessed 1 May 2021.

  27. Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P, the Aw. Acute renal failure – definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care. 2004. https://doi.org/10.1186/cc2872.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Mehta RL, Kellum JA, Shah SV, Molitoris BA, Ronco C, Warnock DG, et al. Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury. Crit Care. 2007. https://doi.org/10.1186/cc5713.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Ahn JY, Lee MJ, Seo JS, Choi D, Park JB. Plasma neutrophil gelatinase-associated lipocalin as a predictive biomarker for the detection of acute kidney injury in adult poisoning. Clin Toxicol. 2016. https://doi.org/10.3109/15563650.2015.1118487.

    Article  Google Scholar 

  30. Da Y, Akalya K, Murali T, Vathsala A, Tan CS, Low S, et al. Serial quantification of urinary protein biomarkers to predict drug-induced acute kidney injury. Curr Drug Metab. 2019. https://doi.org/10.2174/1389200220666190711114504.

    Article  PubMed  Google Scholar 

  31. Carvalho Pedrosa D, Macedo de Oliveira Neves F, Cavalcante Meneses G, Pinheiro Gomes Wirtzbiki G, da Costa Moraes CA, Costa Martins AM, et al. Urinary KIM-1 in children undergoing nephrotoxic antineoplastic treatment: a prospective cohort study. Pediatric Nephrol. 2015. https://doi.org/10.1007/s00467-015-3178-3.

    Article  Google Scholar 

  32. Abdelkhalek M, El Wahab AA, Sabry A, Awad E, Elbastawessy A, Elgohary O, et al. Early detection of acute kidney injury in cancer patients receiving platinum based chemotherapy. Nephrol Dial Transplant. 2017;32:iii174.

    Article  Google Scholar 

  33. Pang HM, Qin XL, Liu TT, Wei WX, Cheng DH, Lu H, et al. Urinary kidney injury molecule-1 and neutrophil gelatinase-associated lipocalin as early biomarkers for predicting vancomycin-associated acute kidney injury: a prospective study. Eur Rev Med Pharmacol Sci. 2017;21:4203–13.

    PubMed  Google Scholar 

  34. Babic JT, Manchandani P, Ledesma KR, Tam VH. Evaluation of urinary KIM-1 for prediction of polymyxin B-induced nephrotoxicity. Antimicrob Agents Chemother. 2017. https://doi.org/10.1128/AAC.01735-17.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Thammathiwat T, Tiranathanagul K, Srisawat N, Susantitaphong P, Praditpornsilpa K, Eiam-Ong S. Clinical and subclinical acute kidney injury in multidrug-resistant septic patients treated with colistimethate sodium: Incidence and clinical outcomes. Nephrology. 2020. https://doi.org/10.1111/nep.13663.

    Article  PubMed  Google Scholar 

  36. Sterling M, Al-Ismaili Z, McMahon KR, Piccioni M, Pizzi M, Mottes T, et al. Urine biomarkers of acute kidney injury in noncritically ill, hospitalized children treated with chemotherapy. Pediatr Blood Cancer. 2017. https://doi.org/10.1002/pbc.26538.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Ghadrdan E, Ebrahimpour S, Sadighi S, Chaibakhsh S, Jahangard-Rafsanjani Z. Evaluation of urinary neutrophil gelatinase-associated lipocalin and urinary kidney injury molecule-1 as biomarkers of renal function in cancer patients treated with cisplatin. J Oncol Pharm Pract. 2020. https://doi.org/10.1177/1078155220901756.

    Article  PubMed  Google Scholar 

  38. Shahbazi F, Sadighi S, Dashti-Khavidaki S, Shahi F, Mirzania M. Urine ratio of neutrophil gelatinase-associated lipocalin to creatinine as a marker for early detection of cisplatin-associated nephrotoxicity. Iran J Kidney Dis. 2015;9:306–10.

    PubMed  Google Scholar 

  39. Park SY, Eom JS, Lee JS, Ju YS, Park JY. Neutrophil gelatinase-associated lipocalin as a predictor of acute kidney injury in patients during treatment with colistimethate sodium. Infect Chemother. 2018. https://doi.org/10.3947/ic.2018.50.2.128.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Ostermann M, McCullough PA, Forni LG, Bagshaw SM, Joannidis M, Shi J, et al. Kinetics of urinary cell cycle arrest markers for acute kidney injury following exposure to potential renal insults. Crit Care Med. 2018. https://doi.org/10.1097/CCM.0000000000002847.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Ostermann M, Zarbock A, Goldstein S, Kashani K, Macedo E, Murugan R, et al. Recommendations on acute kidney injury biomarkers from the acute disease quality initiative consensus conference: a consensus statement. JAMA Netw Open. 2020. https://doi.org/10.1001/jamanetworkopen.2020.19209.

    Article  PubMed  Google Scholar 

  42. Törnblom S, Nisula S, Petäjä L, Vaara ST, Haapio M, Pesonen E, et al. Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility—data from the observational FINNAKI study. Ann Intensive Care. 2020. https://doi.org/10.1186/s13613-020-00667-7.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Passov A, Petäjä L, Pihlajoki M, Salminen U-S, Suojaranta R, Vento A, et al. The origin of plasma neutrophil gelatinase-associated lipocalin in cardiac surgery. BMC Nephrol. 2019. https://doi.org/10.1186/s12882-019-1380-4.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Goldstein SL, Krallman KA, Schmerge A, Dill L, Gerhardt B, Chodaparavu P, et al. Urinary neutrophil gelatinase-associated lipocalin rules out nephrotoxic acute kidney injury in children. Pediatr Nephrol. 2021. https://doi.org/10.1007/s00467-020-04898-5.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Vora S. Acute renal failure due to vancomycin toxicity in the setting of unmonitored vancomycin infusion. Proc (Bayl Univ Med Cent). 2016. https://doi.org/10.1080/08998280.2016.11929491.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Mårtensson J, Bellomo R. The rise and fall of NGAL in acute kidney injury. Blood Purif. 2014. https://doi.org/10.1159/000364937.

    Article  PubMed  Google Scholar 

  47. Seo YLW, Kwon OH. Performance evaluation of BioPorto diagnostics’ neutrophil gelatinase-associated lipocalin assay on automated clinical chemistry analyzer Hitachi 7600. J Lab Med Qual Assur. 2013;35:23–8.

    Google Scholar 

  48. abcam. Human KIM1 ELISA Kit (TIM-1)(ab235081). 2021. https://www.abcam.com/human-kim1-elisa-kit-tim-1-ab235081.html. Accessed 22 May 2021.

  49. Biotech R. Human TIM-1 ELISA. 2021. https://www.raybiotech.com/human-tim-1-elisa/?gclid=Cj0KCQjw16KFBhCgARIsALB0g8IuQmyni3tMwY0EjDO-_KQuZ_8DwB03MjzrRBEnN-lkfJMvlGMB8iEaArphEALw_wcB. Accessed 22 May 2021.

  50. Biotech R. Human FABP2 ELISA. 2021. https://www.raybiotech.com/human-fabp2-elisa/?gclid=Cj0KCQjw16KFBhCgARIsALB0g8JJo9qiHmUeQVxUgKIRnPd_wELwFpgu4LqTHGJJ_PRDR5LoIh_dkIYaAjVdEALw_wcB. Accessed 2 May 2021.

  51. Biotech R. Human FABP2 ELISA. 2021. https://www.raybiotech.com/human-fabp2-elisa/?gclid=Cj0KCQjw16KFBhCgARIsALB0g8JJo9qiHmUeQVxUgKIRnPd_wELwFpgu4LqTHGJJ_PRDR5LoIh_dkIYaAjVdEALw_wcB. Accessed 22 May 2021.

  52. Diapharma. CMIC Human L-FABP (FABP1) ELISA. 2021. https://diapharma.com/product/biomarkers/metabolic-syndrome/human-urine-l-fabp-fabp1-elisa-kit/. Accessed 22 May 2021.

  53. abcam. Human IL-18 ELISA Kit (ab215539). 2021. https://www.abcam.com/human-il-18-elisa-kit-ab215539.html. Accessed 22 May 2021.

  54. Guzzi LM, Bergler T, Binnall B, Engelman DT, Forni L, Germain MJ, et al. Clinical use of [TIMP-2]•[IGFBP7] biomarker testing to assess risk of acute kidney injury in critical care: guidance from an expert panel. Crit Care. 2019. https://doi.org/10.1186/s13054-019-2504-8.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Medical A. NephroCheck. https://www.nephrocheck.com/us/. Accessed 22 May 2021.

Download references

Author information

Authors and Affiliations

  1. University of Pittsburgh, School of Pharmacy, Pittsburgh, PA, USA

    Ravi J. Desai & Christina L. Kazarov

  2. Massachusetts College of Pharmacy and Health Sciences, Boston, MA, USA

    Adrian Wong

  3. University of Pittsburgh, School of Pharmacy, 6462 Salk Hall, 3507 Terrace St, Pittsburgh, PA, 15261, USA

    Sandra L. Kane-Gill

Authors
  1. Ravi J. Desai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christina L. Kazarov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Adrian Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sandra L. Kane-Gill
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sandra L. Kane-Gill.

Ethics declarations

Funding

The authors did not receive any funding for the research or authorship of this study.

Conflicts of interest

Ravi Desai, Christina L. Kazarov, and Adrian Wong have no disclosures to declare. Sandra L. Kane-Gill declares the following: Organizational Leadership: President-Elect of the Society of Critical Care Medicine (SCCM); National Institute of Diabetes and Digestive and Kidney Diseases and National Center for Complementary and Integrative Health grant funding.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

Data and materials are available in the electronic supplementary material.

Code availability

Not applicable.

Authors’ contributions

Ravi Desai contributed to the study conceptualization, search execution, article screening, manuscript writing, and project oversight. Christina Kazarov contributed to the study conceptualization, article screening, and manuscript writing. Sandra Kane-Gill contributed to the study conceptualization, manuscript writing, and project oversight. Adrian Wong contributed to the study conceptualization and manuscript writing. All authors read and approved the final version of this manuscript.

Supplementary Information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Desai, R.J., Kazarov, C.L., Wong, A. et al. Kidney Damage and Stress Biomarkers for Early Identification of Drug-Induced Kidney Injury: A Systematic Review. Drug Saf 45, 839–852 (2022). https://doi.org/10.1007/s40264-022-01202-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40264-022-01202-2