Neutrophil Gelatinase-Associated Lipocalin Measured on Clinical Laboratory Platforms for the Prediction of Acute Kidney Injury and the Associated Need for Dialysis Therapy: A Systematic Review and Meta-analysis

Am J Kidney Dis. 2020 Dec;76(6):826-841.e1. doi: 10.1053/j.ajkd.2020.05.015. Epub 2020 Jul 15.

Abstract

Rationale & objective: The usefulness of measures of neutrophil gelatinase-associated lipocalin (NGAL) in urine or plasma obtained on clinical laboratory platforms for predicting acute kidney injury (AKI) and AKI requiring dialysis (AKI-D) has not been fully evaluated. We sought to quantitatively summarize published data to evaluate the value of urinary and plasma NGAL for kidney risk prediction.

Study design: Literature-based meta-analysis and individual-study-data meta-analysis of diagnostic studies following PRISMA-IPD guidelines.

Setting & study populations: Studies of adults investigating AKI, severe AKI, and AKI-D in the setting of cardiac surgery, intensive care, or emergency department care using either urinary or plasma NGAL measured on clinical laboratory platforms.

Selection criteria for studies: PubMed, Web of Science, Cochrane Library, Scopus, and congress abstracts ever published through February 2020 reporting diagnostic test studies of NGAL measured on clinical laboratory platforms to predict AKI.

Data extraction: Individual-study-data meta-analysis was accomplished by giving authors data specifications tailored to their studies and requesting standardized patient-level data analysis.

Analytical approach: Individual-study-data meta-analysis used a bivariate time-to-event model for interval-censored data from which discriminative ability (AUC) was characterized. NGAL cutoff concentrations at 95% sensitivity, 95% specificity, and optimal sensitivity and specificity were also estimated. Models incorporated as confounders the clinical setting and use versus nonuse of urine output as a criterion for AKI. A literature-based meta-analysis was also performed for all published studies including those for which the authors were unable to provide individual-study data analyses.

Results: We included 52 observational studies involving 13,040 patients. We analyzed 30 data sets for the individual-study-data meta-analysis. For AKI, severe AKI, and AKI-D, numbers of events were 837, 304, and 103 for analyses of urinary NGAL, respectively; these values were 705, 271, and 178 for analyses of plasma NGAL. Discriminative performance was similar in both meta-analyses. Individual-study-data meta-analysis AUCs for urinary NGAL were 0.75 (95% CI, 0.73-0.76) and 0.80 (95% CI, 0.79-0.81) for severe AKI and AKI-D, respectively; for plasma NGAL, the corresponding AUCs were 0.80 (95% CI, 0.79-0.81) and 0.86 (95% CI, 0.84-0.86). Cutoff concentrations at 95% specificity for urinary NGAL were>580ng/mL with 27% sensitivity for severe AKI and>589ng/mL with 24% sensitivity for AKI-D. Corresponding cutoffs for plasma NGAL were>364ng/mL with 44% sensitivity and>546ng/mL with 26% sensitivity, respectively.

Limitations: Practice variability in initiation of dialysis. Imperfect harmonization of data across studies.

Conclusions: Urinary and plasma NGAL concentrations may identify patients at high risk for AKI in clinical research and practice. The cutoff concentrations reported in this study require prospective evaluation.

Keywords: AKI biomarker; AKI prediction; AKI requiring dialysis (AKI-D); Acute kidney injury (AKI); cut-off value; diagnostic accuracy; meta-analysis; neutrophil gelatinase-associated lipocalin (NGAL); plasma NGAL; renal replacement therapy (RRT); renal risk assessment; urine NGAL.

Publication types

  • Meta-Analysis
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Systematic Review

MeSH terms

  • Acute Kidney Injury / diagnosis*
  • Acute Kidney Injury / metabolism
  • Acute Kidney Injury / therapy
  • Biomarkers / blood
  • Biomarkers / urine
  • Humans
  • Lipocalin-2 / blood*
  • Predictive Value of Tests
  • Renal Dialysis*

Substances

  • Biomarkers
  • Lipocalin-2