Variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation

Abstract Allogeneic hematopoietic cell transplantation (allo-HCT) is a potentially curative procedure for a large number of diseases. However, the greatest barriers to the success of allo-HCT are relapse and graft-versus-host-disease (GVHD). Many studies have examined the reconstitution of the immun...

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Autores principales:	Chloé Pasin, Ryan H. Moy, Ran Reshef, Andrew J. Yates
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d189775a3d294f46bb035df567f29fdd
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spelling	oai:doaj.org-article:d189775a3d294f46bb035df567f29fdd2021-12-02T14:06:19ZVariable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation10.1038/s41598-021-82562-02045-2322https://doaj.org/article/d189775a3d294f46bb035df567f29fdd2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82562-0https://doaj.org/toc/2045-2322Abstract Allogeneic hematopoietic cell transplantation (allo-HCT) is a potentially curative procedure for a large number of diseases. However, the greatest barriers to the success of allo-HCT are relapse and graft-versus-host-disease (GVHD). Many studies have examined the reconstitution of the immune system after allo-HCT and searched for factors associated with clinical outcome. Serum biomarkers have also been studied to predict the incidence and prognosis of GVHD. However, the use of multiparametric immunophenotyping has been less extensively explored: studies usually focus on preselected and predefined cell phenotypes and so do not fully exploit the richness of flow cytometry data. Here we aimed to identify cell phenotypes present 30 days after allo-HCT that are associated with clinical outcomes in 37 patients participating in a trial relating to the prevention of GVHD, derived from 82 flow cytometry markers and 13 clinical variables. To do this we applied variable selection methods in a competing risks modeling framework, and identified specific subsets of T, B, and NK cells associated with relapse. Our study demonstrates the value of variable selection methods for mining rich, high dimensional clinical data and identifying potentially unexplored cell subpopulations of interest.Chloé PasinRyan H. MoyRan ReshefAndrew J. YatesNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chloé Pasin Ryan H. Moy Ran Reshef Andrew J. Yates Variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation
description	Abstract Allogeneic hematopoietic cell transplantation (allo-HCT) is a potentially curative procedure for a large number of diseases. However, the greatest barriers to the success of allo-HCT are relapse and graft-versus-host-disease (GVHD). Many studies have examined the reconstitution of the immune system after allo-HCT and searched for factors associated with clinical outcome. Serum biomarkers have also been studied to predict the incidence and prognosis of GVHD. However, the use of multiparametric immunophenotyping has been less extensively explored: studies usually focus on preselected and predefined cell phenotypes and so do not fully exploit the richness of flow cytometry data. Here we aimed to identify cell phenotypes present 30 days after allo-HCT that are associated with clinical outcomes in 37 patients participating in a trial relating to the prevention of GVHD, derived from 82 flow cytometry markers and 13 clinical variables. To do this we applied variable selection methods in a competing risks modeling framework, and identified specific subsets of T, B, and NK cells associated with relapse. Our study demonstrates the value of variable selection methods for mining rich, high dimensional clinical data and identifying potentially unexplored cell subpopulations of interest.
format	article
author	Chloé Pasin Ryan H. Moy Ran Reshef Andrew J. Yates
author_facet	Chloé Pasin Ryan H. Moy Ran Reshef Andrew J. Yates
author_sort	Chloé Pasin
title	Variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation
title_short	Variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation
title_full	Variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation
title_fullStr	Variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation
title_full_unstemmed	Variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation
title_sort	variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/d189775a3d294f46bb035df567f29fdd
work_keys_str_mv	AT chloepasin variableselectionmethodsforpredictingclinicaloutcomesfollowingallogeneichematopoieticcelltransplantation AT ryanhmoy variableselectionmethodsforpredictingclinicaloutcomesfollowingallogeneichematopoieticcelltransplantation AT ranreshef variableselectionmethodsforpredictingclinicaloutcomesfollowingallogeneichematopoieticcelltransplantation AT andrewjyates variableselectionmethodsforpredictingclinicaloutcomesfollowingallogeneichematopoieticcelltransplantation
_version_	1718392052223311872

Variable selection methods for predicting clinical outcomes following allogeneic hematopoietic cell transplantation

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