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Donor-derived Cell-free DNA Combined With Histology Improves Prediction of Estimated Glomerular Filtration Rate Over Time in Kidney Transplant Recipients Compared With Histology Alone

Higher Banff inflammation and chronicity scores on kidney transplant biopsies are associated with poorer graft survival, although histology alone has limitations in predicting outcomes. We investigated if integrating donor-derived cell-free DNA (dd-cfDNA, Allosure; CareDx, Inc.) with Banff biopsy sc...

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Autores principales: Huang, Edmund, Gillespie, Matthew, Ammerman, Noriko, Vo, Ashley, Lim, Kathlyn, Peng, Alice, Najjar, Reiad, Sethi, Supreet, Jordan, Stanley C., Mirocha, James, Haas, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581058/
https://www.ncbi.nlm.nih.gov/pubmed/33134504
http://dx.doi.org/10.1097/TXD.0000000000001027
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author Huang, Edmund
Gillespie, Matthew
Ammerman, Noriko
Vo, Ashley
Lim, Kathlyn
Peng, Alice
Najjar, Reiad
Sethi, Supreet
Jordan, Stanley C.
Mirocha, James
Haas, Mark
author_facet Huang, Edmund
Gillespie, Matthew
Ammerman, Noriko
Vo, Ashley
Lim, Kathlyn
Peng, Alice
Najjar, Reiad
Sethi, Supreet
Jordan, Stanley C.
Mirocha, James
Haas, Mark
author_sort Huang, Edmund
collection PubMed
description Higher Banff inflammation and chronicity scores on kidney transplant biopsies are associated with poorer graft survival, although histology alone has limitations in predicting outcomes. We investigated if integrating donor-derived cell-free DNA (dd-cfDNA, Allosure; CareDx, Inc.) with Banff biopsy scores into a predictive model for estimated glomerular filtration rate over time can improve prognostic assessment versus histology alone. METHODS. We identified 180 kidney transplant patients with dd-cfDNA assessed within 1 mo of biopsy. Using linear mixed–effects models, a prediction model of Banff histology scores and dd-cfDNA on estimated glomerular filtration rate over time was derived. Nested models were compared using the likelihood-ratio test, Akaike Information Criterion, and Bayesian Information Criterion to assess if inclusion of dd-cfDNA into a model consisting of Banff biopsy scores would improve model fit. RESULTS. Univariate models identified significant covariate-by-time interactions for cg = 3 versus <3 (coefficient: −1.3 mL/min/1.73 m(2)/mo; 95% confidence interval [CI], −2.4 to −0.2; P = 0.02) and ci + ct ≥ 3 versus <3 (coefficient: −0.7 mL/min/1.73 m(2)/mo; 95% CI, −1.3 to −0.1; P = 0.03) and a trend toward significant covariate-by-time interaction for dd-cfDNA (coefficient: −0.5 mL/min/1.73 m(2)/mo; 95% CI, −1.0 to 0.1; P = 0.08). Addition of acute inflammation (i, t, and v), microvascular inflammation (g and ptc), and inflammation in area of interstitial fibrosis and tubular atrophy scores to chronicity scores (cg ≥ 3 and ci + ct ≥ 3) did not improve model fit. However, a model including dd-cfDNA with cg and ci + ct with covariate-by-time interactions had a better model fit compared with cg and ci + ct alone (likelihood-ratio test statistic = 21.1; df = 2; P < 0.001). CONCLUSIONS. Addition of dd-cfDNA to Banff biopsy scores provided better prognostic assessment over biopsy characteristics alone.
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spelling pubmed-75810582020-10-29 Donor-derived Cell-free DNA Combined With Histology Improves Prediction of Estimated Glomerular Filtration Rate Over Time in Kidney Transplant Recipients Compared With Histology Alone Huang, Edmund Gillespie, Matthew Ammerman, Noriko Vo, Ashley Lim, Kathlyn Peng, Alice Najjar, Reiad Sethi, Supreet Jordan, Stanley C. Mirocha, James Haas, Mark Transplant Direct Kidney Transplantation Higher Banff inflammation and chronicity scores on kidney transplant biopsies are associated with poorer graft survival, although histology alone has limitations in predicting outcomes. We investigated if integrating donor-derived cell-free DNA (dd-cfDNA, Allosure; CareDx, Inc.) with Banff biopsy scores into a predictive model for estimated glomerular filtration rate over time can improve prognostic assessment versus histology alone. METHODS. We identified 180 kidney transplant patients with dd-cfDNA assessed within 1 mo of biopsy. Using linear mixed–effects models, a prediction model of Banff histology scores and dd-cfDNA on estimated glomerular filtration rate over time was derived. Nested models were compared using the likelihood-ratio test, Akaike Information Criterion, and Bayesian Information Criterion to assess if inclusion of dd-cfDNA into a model consisting of Banff biopsy scores would improve model fit. RESULTS. Univariate models identified significant covariate-by-time interactions for cg = 3 versus <3 (coefficient: −1.3 mL/min/1.73 m(2)/mo; 95% confidence interval [CI], −2.4 to −0.2; P = 0.02) and ci + ct ≥ 3 versus <3 (coefficient: −0.7 mL/min/1.73 m(2)/mo; 95% CI, −1.3 to −0.1; P = 0.03) and a trend toward significant covariate-by-time interaction for dd-cfDNA (coefficient: −0.5 mL/min/1.73 m(2)/mo; 95% CI, −1.0 to 0.1; P = 0.08). Addition of acute inflammation (i, t, and v), microvascular inflammation (g and ptc), and inflammation in area of interstitial fibrosis and tubular atrophy scores to chronicity scores (cg ≥ 3 and ci + ct ≥ 3) did not improve model fit. However, a model including dd-cfDNA with cg and ci + ct with covariate-by-time interactions had a better model fit compared with cg and ci + ct alone (likelihood-ratio test statistic = 21.1; df = 2; P < 0.001). CONCLUSIONS. Addition of dd-cfDNA to Banff biopsy scores provided better prognostic assessment over biopsy characteristics alone. Lippincott Williams & Wilkins 2020-07-15 /pmc/articles/PMC7581058/ /pubmed/33134504 http://dx.doi.org/10.1097/TXD.0000000000001027 Text en Copyright © 2020 The Author(s). Transplantation Direct. Published by Wolters Kluwer Health, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Kidney Transplantation
Huang, Edmund
Gillespie, Matthew
Ammerman, Noriko
Vo, Ashley
Lim, Kathlyn
Peng, Alice
Najjar, Reiad
Sethi, Supreet
Jordan, Stanley C.
Mirocha, James
Haas, Mark
Donor-derived Cell-free DNA Combined With Histology Improves Prediction of Estimated Glomerular Filtration Rate Over Time in Kidney Transplant Recipients Compared With Histology Alone
title Donor-derived Cell-free DNA Combined With Histology Improves Prediction of Estimated Glomerular Filtration Rate Over Time in Kidney Transplant Recipients Compared With Histology Alone
title_full Donor-derived Cell-free DNA Combined With Histology Improves Prediction of Estimated Glomerular Filtration Rate Over Time in Kidney Transplant Recipients Compared With Histology Alone
title_fullStr Donor-derived Cell-free DNA Combined With Histology Improves Prediction of Estimated Glomerular Filtration Rate Over Time in Kidney Transplant Recipients Compared With Histology Alone
title_full_unstemmed Donor-derived Cell-free DNA Combined With Histology Improves Prediction of Estimated Glomerular Filtration Rate Over Time in Kidney Transplant Recipients Compared With Histology Alone
title_short Donor-derived Cell-free DNA Combined With Histology Improves Prediction of Estimated Glomerular Filtration Rate Over Time in Kidney Transplant Recipients Compared With Histology Alone
title_sort donor-derived cell-free dna combined with histology improves prediction of estimated glomerular filtration rate over time in kidney transplant recipients compared with histology alone
topic Kidney Transplantation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581058/
https://www.ncbi.nlm.nih.gov/pubmed/33134504
http://dx.doi.org/10.1097/TXD.0000000000001027
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