Evaluation of urinary biomarkers for prediction of diabetic kidney disease: a propensity score matching analysis

BACKGROUND: The aim of this study was to evaluate the diagnostic value of six urinary biomarkers for prediction of diabetic kidney disease (DKD). METHODS: = 300) according to 24-h urinary albumin excretion rate (24-h UAE). Data on the levels of six studied urinary biomarkers [transferrin (TF), immunoglobulin G (IgG), retinol-binding protein (RBP), β-galactosidase (GAL), N-acetyl-beta-glucosaminidase (NAG), and β2-microglobulin (β2MG)] were obtained. The propensity score matching (PSM) method was applied to eliminate the influences of confounding variables. RESULTS: Patients with DKD had higher levels of all six urinary biomarkers. All indicators demonstrated significantly increased risk of DKD, except for GAL and β2MG. Single RBP yielded the greatest area under the curve (AUC) value of 0.920 compared with the other five markers, followed by TF (0.867) and IgG (0.867). However, GAL, NAG, and β2MG were shown to have a weak prognostic ability. The diagnostic values of the different combinations were not superior to the single RBP. CONCLUSIONS: RBP, TF, and IgG could be used as reliable or good predictors of DKD. The combined use of these biomarkers did not improve DKD detection.