Methods used to assess the performance of biomarkers for the diagnosis of acute kidney injury: a systematic review and meta-analysis

Biomarkers. 2018 Dec;23(8):766-772. doi: 10.1080/1354750X.2018.1493616. Epub 2018 Aug 23.

Abstract

Purpose: Methods used to explore biomarkers for acute kidney injury (AKI) might have a major impact on the results and the use of these biomarkers. We evaluated the methods used to investigate biomarkers of AKI.

Materials and methods: A systematic review and meta-analysis were performed using a computerized search of the MEDLINE and the EMBASE databases (PROSPERO CRD42017059618). Articles reporting biomarker's performance to diagnose AKI were included. The outcome included a description of the methods used to assess the performance of biomarkers to diagnose AKI.

Results: Among the 295 included studies, assessment of biomarkers was the primary endpoint in 284 with sample size calculation in only 8% of cases. Eighty-five percent of the studies summarized the performance of biomarkers with receiver operating characteristic (ROC) curves; however, 74 studies (25%) did not provide the threshold, sensibility or specificity. A total of 176 studies evaluated more than one biomarker, and only 25% combined biomarkers to increase diagnostic performance. We determined that the definition of AKI and study design impacted the diagnostic performance using uNGAL (urinary neutrophil gelatinase-associated lipocalin) as an example. Major publication bias was identified.

Conclusions: Most articles that reported biomarkers of AKI performance present methodological weaknesses. Basic rules should be provided to increase the quality of reporting in this area.

Keywords: Biomarkers; acute kidney injury; methodological review.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Acute Kidney Injury / diagnosis*
  • Animals
  • Biomarkers / analysis*
  • Data Accuracy
  • Humans
  • Lipocalin-2
  • Methods
  • Publication Bias
  • ROC Curve
  • Sensitivity and Specificity

Substances

  • Biomarkers
  • Lipocalin-2