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Title
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Urinary protein biomarker panel for the diagnosis of antibody-mediated rejection in kidney transplant recipients
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Author
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Abstract
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| Introduction: Antibody-mediated rejection (ABMR) impacts kidney allograft outcome. The diagnosis is made based on findings from invasive kidney transplant biopsy specimens. The aim of this study was to identify a noninvasive urinary protein biomarker for ABMR after kidney transplantation. Methods: We performed a multicenter case-control study to identify a urinary biomarker for ABMR (training cohort, n = 249) and an independent, prospective multicenter cohort study for validation (n = 391). We used concomitant biopsies to classify the samples according to the Banff classification. After untargeted protein identification and quantification, we used a support vector machine to train the model in the training cohort. The primary endpoint was the diagnostic accuracy of the urinary biomarker for ABMR in the validation cohort. Results: We identified a set of 10 urinary proteins that accurately discriminated patients with (n = 60) and without (n = 189) ABMR in the training cohort with an area under the curve (AUC) of 0.98 (95% confidence interval [CI], 0.96-1.00). The diagnostic accuracy was maintained in the validation cohort (AUC, 0.88; 95% CI, 0.8-0.93) for discriminating the presence (n = 43) from the absence (n = 348) of ABMR. The negative predictive value of the 10-protein marker set for exclusion of ABMR was 0.99, and the positive predictive value was 0.33. The diagnostic accuracy was independent of the reason for performing the biopsy, time after transplantation, and better than the accuracy of gross proteinuria (AUC, 0.76). Conclusions: We identified and validated a urinary protein biomarker set that can be used to exclude ABMR. (C) 2020 International Society of Nephrology. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
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Language
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English
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Source (journal)
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Kidney International Reports. - [S.l.]
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Publication
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[S.l.]
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Elsevier
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2020
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ISSN
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2468-0249
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DOI
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10.1016/J.EKIR.2020.06.018
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Volume/pages
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5
:9
(2020)
, p. 1448-1458
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ISI
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000568662700010
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Pubmed ID
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32954069
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Full text (Publisher's DOI)
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Full text (open access)
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