%0 Journal Article
%A Martínez-Laperche, Carolina
%A Buces, Elena
%A Aguilera-Morillo, M Carmen
%A Picornell, Antoni
%A González-Rivera, Milagros
%A Lillo, Rosa
%A Santos, Nazly
%A Martín-Antonio, Beatriz
%A Guillem, Vicent
%A Nieto, José B
%A González, Marcos
%A de la Cámara, Rafael
%A Brunet, Salut
%A Jiménez-Velasco, Antonio
%A Espigado, Ildefonso
%A Vallejo, Carlos
%A Sampol, Antonia
%A Bellón, José María
%A Serrano, David
%A Kwon, Mi
%A Gayoso, Jorge
%A Balsalobre, Pascual
%A Urbano-Izpizua, Álvaro
%A Solano, Carlos
%A Gallardo, David
%A Díez-Martín, José Luis
%A Romo, Juan
%A Buño, Ismael
%A GVHD/Immunotherapy Committee of the Spanish Group for Hematopoietic Transplantation
%T A novel predictive approach for GVHD after allogeneic SCT based on clinical variables and cytokine gene polymorphisms.
%D 2018
%U http://hdl.handle.net/10668/12734
%X Despite considerable advances in our understanding of the pathophysiology of graft-versus-host disease (GVHD), its prediction remains unresolved and depends mainly on clinical data. The aim of this study is to build a predictive model based on clinical variables and cytokine gene polymorphism for predicting acute GVHD (aGVHD) and chronic GVHD (cGVHD) from the analysis of a large cohort of HLA-identical sibling donor allogeneic stem cell transplant (allo-SCT) patients. A total of 25 SNPs in 12 cytokine genes were evaluated in 509 patients. Data were analyzed using a linear regression model and the least absolute shrinkage and selection operator (LASSO). The statistical model was constructed by randomly selecting 85% of cases (training set), and the predictive ability was confirmed based on the remaining 15% of cases (test set). Models including clinical and genetic variables (CG-M) predicted severe aGVHD significantly better than models including only clinical variables (C-M) or only genetic variables (G-M). For grades 3-4 aGVHD, the correct classification rates (CCR1) were: 100% for CG-M, 88% for G-M, and 50% for C-M. On the other hand, CG-M and G-M predicted extensive cGVHD better than C-M (CCR1: 80% vs. 66.7%, respectively). A risk score was calculated based on LASSO multivariate analyses. It was able to correctly stratify patients who developed grades 3-4 aGVHD (P
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