Urinary podocalyxin as a biomarker to diagnose membranous nephropathy

Takahiro Imaizumi, Masahiro Nakatochi, Shin'ichi Akiyama, Makoto Yamaguchi, Hiroyuki Kurosawa, Yoshiaki Hirayama, Takayuki Katsuno, Naotake Tsuboi, Masanori Hara, Shoichi Maruyama

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21 Citations (Scopus)


Background: A non-invasive diagnostic marker of membranous nephropathy (MN) is desirable. The urinary level of podocalyxin (PCX) is higher in various glomerular diseases, including MN. The aim of this study was to construct a diagnostic model of MN with the combination of urinary PCX and clinical parameters. Methods: We performed this cross-sectional study to construct the diagnostic models for MN by using data and samples from the multicenter kidney biopsy registry of Nagoya University and its affiliated hospitals. Urinary (u-) PCX was measured by sandwich ELISA. We constructed 3 types of diagnostic models in 105 training samples: u-PCX univariate model, the combined model of clinical parameters other than u-PCX (clinical model), and the combined model of both u-PCX and clinical parameters (combined model). We assessed the clinical usefulness of the diagnostic models through the comparison of c-statistics and decision curve analysis (DCA) in 209 validation samples. Results: The clinical model consisted of age, glomerular filtration rate, and diabetes mellitus. In the training cohort, the c-statistics were 0.868 [95% CI, 0.799-0.937] in the combined model. In the validation cohort, sensitivity was 80.5% and specificity was 73.5% on the cut-off value. The net benefit of the combined model was better between threshold probabilities of 40-80% in DCA. Conclusions: In this study, we demonstrated the utility of u-PCX as a diagnostic marker for MN and the clinical usefulness of the diagnostic models, through the combination of u-PCX and clinical parameters including age, glomerular filtration rate, and diabetes mellitus.

Original languageEnglish
Article numbere0163507
JournalPloS one
Issue number9
Publication statusPublished - 09-2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General


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