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Structural modeling for Oxford histological classifications of immunoglobulin A nephropathy

In immunoglobulin A nephropathy (IgAN), Cox regression analysis can select independent prognostic variables for renal functional decline (RFD). However, the correlation of the selected histological variables with clinical and/or treatment variables is unknown, thereby making histology-based treatmen...

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Autores principales: Joh, Kensuke, Nakazato, Takashi, Hashiguchi, Akinori, Shimizu, Akira, Katafuchi, Ritsuko, Okonogi, Hideo, Koike, Kentaro, Hirano, Keita, Tsuboi, Nobuo, Kawamura, Tetsuya, Yokoo, Takashi, Narita, Ichiei, Suzuki, Yusuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9462802/
https://www.ncbi.nlm.nih.gov/pubmed/36084046
http://dx.doi.org/10.1371/journal.pone.0268731
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author Joh, Kensuke
Nakazato, Takashi
Hashiguchi, Akinori
Shimizu, Akira
Katafuchi, Ritsuko
Okonogi, Hideo
Koike, Kentaro
Hirano, Keita
Tsuboi, Nobuo
Kawamura, Tetsuya
Yokoo, Takashi
Narita, Ichiei
Suzuki, Yusuke
author_facet Joh, Kensuke
Nakazato, Takashi
Hashiguchi, Akinori
Shimizu, Akira
Katafuchi, Ritsuko
Okonogi, Hideo
Koike, Kentaro
Hirano, Keita
Tsuboi, Nobuo
Kawamura, Tetsuya
Yokoo, Takashi
Narita, Ichiei
Suzuki, Yusuke
author_sort Joh, Kensuke
collection PubMed
description In immunoglobulin A nephropathy (IgAN), Cox regression analysis can select independent prognostic variables for renal functional decline (RFD). However, the correlation of the selected histological variables with clinical and/or treatment variables is unknown, thereby making histology-based treatment decisions unreliable. We prospectively followed 946 Japanese patients with IgAN for a median of 66 mo. and applied structural equation modeling (SEM) to identify direct and indirect effects of histological variables on RFD as a regression line of estimated glomerular filtration rate (eGFR) via clinical variables including amount of proteinuria, eGFR, mean arterial pressure (MAP) at biopsy, and treatment variables such as steroid therapy with/without tonsillectomy (ST) and renin–angiotensin system blocker (RASB). Multi-layered correlations between the variables and RFD were identified by multivariate linear regression analysis and the model’s goodness of fit was confirmed. Only tubular atrophy/interstitial fibrosis (T) had an accelerative direct effect on RFD, while endocapillary hypercellularity and active crescent (C) had an attenuating indirect effect via ST. Segmental sclerosis (S) had an attenuating indirect effect via eGFR and mesangial hypercellularity (M) had accelerative indirect effect for RFD via proteinuria. Moreover, M and C had accelerative indirect effect via proteinuria, which can be controlled by ST. However, both T and S had additional indirect accelerative effects via eGFR or MAP at biopsy, which cannot be controlled by ST. SEM identified a systemic path links between histological variables and RFD via dependent clinical and/or treatment variables. These findings lead to clinically applicable novel methodologies that can contribute to predict treatment outcomes using the Oxford classifications.
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spelling pubmed-94628022022-09-10 Structural modeling for Oxford histological classifications of immunoglobulin A nephropathy Joh, Kensuke Nakazato, Takashi Hashiguchi, Akinori Shimizu, Akira Katafuchi, Ritsuko Okonogi, Hideo Koike, Kentaro Hirano, Keita Tsuboi, Nobuo Kawamura, Tetsuya Yokoo, Takashi Narita, Ichiei Suzuki, Yusuke PLoS One Research Article In immunoglobulin A nephropathy (IgAN), Cox regression analysis can select independent prognostic variables for renal functional decline (RFD). However, the correlation of the selected histological variables with clinical and/or treatment variables is unknown, thereby making histology-based treatment decisions unreliable. We prospectively followed 946 Japanese patients with IgAN for a median of 66 mo. and applied structural equation modeling (SEM) to identify direct and indirect effects of histological variables on RFD as a regression line of estimated glomerular filtration rate (eGFR) via clinical variables including amount of proteinuria, eGFR, mean arterial pressure (MAP) at biopsy, and treatment variables such as steroid therapy with/without tonsillectomy (ST) and renin–angiotensin system blocker (RASB). Multi-layered correlations between the variables and RFD were identified by multivariate linear regression analysis and the model’s goodness of fit was confirmed. Only tubular atrophy/interstitial fibrosis (T) had an accelerative direct effect on RFD, while endocapillary hypercellularity and active crescent (C) had an attenuating indirect effect via ST. Segmental sclerosis (S) had an attenuating indirect effect via eGFR and mesangial hypercellularity (M) had accelerative indirect effect for RFD via proteinuria. Moreover, M and C had accelerative indirect effect via proteinuria, which can be controlled by ST. However, both T and S had additional indirect accelerative effects via eGFR or MAP at biopsy, which cannot be controlled by ST. SEM identified a systemic path links between histological variables and RFD via dependent clinical and/or treatment variables. These findings lead to clinically applicable novel methodologies that can contribute to predict treatment outcomes using the Oxford classifications. Public Library of Science 2022-09-09 /pmc/articles/PMC9462802/ /pubmed/36084046 http://dx.doi.org/10.1371/journal.pone.0268731 Text en © 2022 Joh et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Joh, Kensuke
Nakazato, Takashi
Hashiguchi, Akinori
Shimizu, Akira
Katafuchi, Ritsuko
Okonogi, Hideo
Koike, Kentaro
Hirano, Keita
Tsuboi, Nobuo
Kawamura, Tetsuya
Yokoo, Takashi
Narita, Ichiei
Suzuki, Yusuke
Structural modeling for Oxford histological classifications of immunoglobulin A nephropathy
title Structural modeling for Oxford histological classifications of immunoglobulin A nephropathy
title_full Structural modeling for Oxford histological classifications of immunoglobulin A nephropathy
title_fullStr Structural modeling for Oxford histological classifications of immunoglobulin A nephropathy
title_full_unstemmed Structural modeling for Oxford histological classifications of immunoglobulin A nephropathy
title_short Structural modeling for Oxford histological classifications of immunoglobulin A nephropathy
title_sort structural modeling for oxford histological classifications of immunoglobulin a nephropathy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9462802/
https://www.ncbi.nlm.nih.gov/pubmed/36084046
http://dx.doi.org/10.1371/journal.pone.0268731
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