Feature Importance of Acute Rejection among Black Kidney Transplant Recipients by Utilizing Random Forest Analysis: An Analysis of the UNOS Database

<b>Background</b>: Black kidney transplant recipients have worse allograft outcomes compared to White recipients. The feature importance and feature interaction network analysis framework of machine learning random forest (RF) analysis may provide an understanding of RF structures to des...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Charat Thongprayoon, Caroline C. Jadlowiec, Napat Leeaphorn, Jackrapong Bruminhent, Prakrati C. Acharya, Chirag Acharya, Pattharawin Pattharanitima, Wisit Kaewput, Boonphiphop Boonpheng, Wisit Cheungpasitporn
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	black race kidney transplant transplantation risk factors feature importance Medicine R
Acceso en línea:	https://doaj.org/article/be0d3cadecf04ff681d3173a1c4ca431
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:be0d3cadecf04ff681d3173a1c4ca431
record_format	dspace
spelling	oai:doaj.org-article:be0d3cadecf04ff681d3173a1c4ca4312021-11-25T18:19:20ZFeature Importance of Acute Rejection among Black Kidney Transplant Recipients by Utilizing Random Forest Analysis: An Analysis of the UNOS Database10.3390/medicines81100662305-6320https://doaj.org/article/be0d3cadecf04ff681d3173a1c4ca4312021-11-01T00:00:00Zhttps://www.mdpi.com/2305-6320/8/11/66https://doaj.org/toc/2305-6320<b>Background</b>: Black kidney transplant recipients have worse allograft outcomes compared to White recipients. The feature importance and feature interaction network analysis framework of machine learning random forest (RF) analysis may provide an understanding of RF structures to design strategies to prevent acute rejection among Black recipients. <b>Methods:</b> We conducted tree-based RF feature importance of Black kidney transplant recipients in United States from 2015 to 2019 in the UNOS database using the number of nodes, accuracy decrease, gini decrease, times_a_root, <i>p</i> value, and mean minimal depth. Feature interaction analysis was also performed to evaluate the most frequent occurrences in the RF classification run between correlated and uncorrelated pairs. <b>Results:</b> A total of 22,687 Black kidney transplant recipients were eligible for analysis. Of these, 1330 (6%) had acute rejection within 1 year after kidney transplant. Important variables in the RF models for acute rejection among Black kidney transplant recipients included recipient age, ESKD etiology, PRA, cold ischemia time, donor age, HLA DR mismatch, BMI, serum albumin, degree of HLA mismatch, education level, and dialysis duration. The three most frequent interactions consisted of two numerical variables, including recipient age:donor age, recipient age:serum albumin, and recipient age:BMI, respectively. <b>Conclusions:</b> The application of tree-based RF feature importance and feature interaction network analysis framework identified recipient age, ESKD etiology, PRA, cold ischemia time, donor age, HLA DR mismatch, BMI, serum albumin, degree of HLA mismatch, education level, and dialysis duration as important variables in the RF models for acute rejection among Black kidney transplant recipients in the United States.Charat ThongprayoonCaroline C. JadlowiecNapat LeeaphornJackrapong BruminhentPrakrati C. AcharyaChirag AcharyaPattharawin PattharanitimaWisit KaewputBoonphiphop BoonphengWisit CheungpasitpornMDPI AGarticleblackracekidney transplanttransplantationrisk factorsfeature importanceMedicineRENMedicines, Vol 8, Iss 66, p 66 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	black race kidney transplant transplantation risk factors feature importance Medicine R
spellingShingle	black race kidney transplant transplantation risk factors feature importance Medicine R Charat Thongprayoon Caroline C. Jadlowiec Napat Leeaphorn Jackrapong Bruminhent Prakrati C. Acharya Chirag Acharya Pattharawin Pattharanitima Wisit Kaewput Boonphiphop Boonpheng Wisit Cheungpasitporn Feature Importance of Acute Rejection among Black Kidney Transplant Recipients by Utilizing Random Forest Analysis: An Analysis of the UNOS Database
description	<b>Background</b>: Black kidney transplant recipients have worse allograft outcomes compared to White recipients. The feature importance and feature interaction network analysis framework of machine learning random forest (RF) analysis may provide an understanding of RF structures to design strategies to prevent acute rejection among Black recipients. <b>Methods:</b> We conducted tree-based RF feature importance of Black kidney transplant recipients in United States from 2015 to 2019 in the UNOS database using the number of nodes, accuracy decrease, gini decrease, times_a_root, <i>p</i> value, and mean minimal depth. Feature interaction analysis was also performed to evaluate the most frequent occurrences in the RF classification run between correlated and uncorrelated pairs. <b>Results:</b> A total of 22,687 Black kidney transplant recipients were eligible for analysis. Of these, 1330 (6%) had acute rejection within 1 year after kidney transplant. Important variables in the RF models for acute rejection among Black kidney transplant recipients included recipient age, ESKD etiology, PRA, cold ischemia time, donor age, HLA DR mismatch, BMI, serum albumin, degree of HLA mismatch, education level, and dialysis duration. The three most frequent interactions consisted of two numerical variables, including recipient age:donor age, recipient age:serum albumin, and recipient age:BMI, respectively. <b>Conclusions:</b> The application of tree-based RF feature importance and feature interaction network analysis framework identified recipient age, ESKD etiology, PRA, cold ischemia time, donor age, HLA DR mismatch, BMI, serum albumin, degree of HLA mismatch, education level, and dialysis duration as important variables in the RF models for acute rejection among Black kidney transplant recipients in the United States.
format	article
author	Charat Thongprayoon Caroline C. Jadlowiec Napat Leeaphorn Jackrapong Bruminhent Prakrati C. Acharya Chirag Acharya Pattharawin Pattharanitima Wisit Kaewput Boonphiphop Boonpheng Wisit Cheungpasitporn
author_facet	Charat Thongprayoon Caroline C. Jadlowiec Napat Leeaphorn Jackrapong Bruminhent Prakrati C. Acharya Chirag Acharya Pattharawin Pattharanitima Wisit Kaewput Boonphiphop Boonpheng Wisit Cheungpasitporn
author_sort	Charat Thongprayoon
title	Feature Importance of Acute Rejection among Black Kidney Transplant Recipients by Utilizing Random Forest Analysis: An Analysis of the UNOS Database
title_short	Feature Importance of Acute Rejection among Black Kidney Transplant Recipients by Utilizing Random Forest Analysis: An Analysis of the UNOS Database
title_full	Feature Importance of Acute Rejection among Black Kidney Transplant Recipients by Utilizing Random Forest Analysis: An Analysis of the UNOS Database
title_fullStr	Feature Importance of Acute Rejection among Black Kidney Transplant Recipients by Utilizing Random Forest Analysis: An Analysis of the UNOS Database
title_full_unstemmed	Feature Importance of Acute Rejection among Black Kidney Transplant Recipients by Utilizing Random Forest Analysis: An Analysis of the UNOS Database
title_sort	feature importance of acute rejection among black kidney transplant recipients by utilizing random forest analysis: an analysis of the unos database
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/be0d3cadecf04ff681d3173a1c4ca431
work_keys_str_mv	AT charatthongprayoon featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase AT carolinecjadlowiec featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase AT napatleeaphorn featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase AT jackrapongbruminhent featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase AT prakraticacharya featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase AT chiragacharya featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase AT pattharawinpattharanitima featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase AT wisitkaewput featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase AT boonphiphopboonpheng featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase AT wisitcheungpasitporn featureimportanceofacuterejectionamongblackkidneytransplantrecipientsbyutilizingrandomforestanalysisananalysisoftheunosdatabase
_version_	1718411343744204800

Feature Importance of Acute Rejection among Black Kidney Transplant Recipients by Utilizing Random Forest Analysis: An Analysis of the UNOS Database

Ejemplares similares