Evaluation of Neutrophil Gelatinase-Associated Lipocalin and Cystatin C in Early Diagnosis of Chronic Kidney Disease in the Absence of the Gold Standard

Fatemeh Masaebi; Mehdi Azizmohammad Looha; Zhuoyu Wang; Elaheh Zarean; Malihe Nasiri; Faranak Kazerouni; Fatemeh Gharishvandi; Farid Zayeri

doi:10.31661/gmj.v9i0.1698

Evaluation of Neutrophil Gelatinase-Associated Lipocalin and Cystatin C in Early Diagnosis of Chronic Kidney Disease in the Absence of the Gold Standard

Galen Med J. 2020 Jun 22:9:e1698. doi: 10.31661/gmj.v9i0.1698. eCollection 2020.

Authors

Fatemeh Masaebi¹, Mehdi Azizmohammad Looha¹, Zhuoyu Wang², Elaheh Zarean³, Malihe Nasiri⁴, Faranak Kazerouni⁵, Fatemeh Gharishvandi⁶, Farid Zayeri⁷

Affiliations

¹ Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
² Zhuoyu Wang, Academy of Medical Engineering and Translational Medicine, Tianjin University.
³ Modeling in Health Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran.
⁴ Faculty of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
⁵ Department of Laboratory Medicine, School of Allied Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
⁶ Department of Clinical Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
⁷ Proteomics Research Center and Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Abstract

Background: Glomerular filtration rate (GFR) is considered as a gold standard of kidney function. However, using GFR as the gold standard is not common in clinical practice, because its direct measurement is usually expensive, cumbersome, and invasive. In the present study, we assessed the predictive power of two other biomarkers, Cystatin-C (Cys-C) and Neutrophil Gelatinase-Associated Lipocalin (NGAL) for early detection of chronic kidney diseases (CKD) in the absence of a gold standard.

Materials and methods: In this study, 72 patients who referred to the Shohadaye Tajrish Hospital of Tehran, Iran, for measuring their kidney function were studied. The ELISA method was utilized for measuring plasma NGAL (PNGAL) and serum Cys-C (SCys-C). The Bayesian latent class modeling approach was applied to asses the predictive power of these biomarkers.

Results: While both the biomarkers had rather high sensitivities (PNGAL=91%, SCys-C= 89%), the specificity of SCys-C biomarker was very lower than the one of PNGAL (SCys-C=56%, PNGAL=94%). The estimated area under the receiver operating characteristic (ROC) curve for SCys-C as the single biomarker for the diagnosis of CKD was about 0.76, while a similar estimate for PNGAL was 0.93. The added value of PNGAL to SCys-C for the diagnosis of CKD in terms of the ROC curve was about 0.19, while the added value of SCys-C to PNGAL was less than 0.02.

Conclusion: In general, our findings suggest that PNGAL can be utilized as a single reliable biomarker for early detection of CKD. In addition, results showed that when a perfect gold standard is not available, Bayesian approaches to latent class models could lead to more precise sensitivity and specificity estimates of imperfect tests.

Keywords: Bayesian Approach; Chronic Kidney Diseases; Cystatin C; Latent Class Model; Neutrophil Gelatinase-Associated Lipocalin; Sensitivity; Specificity.