%0 Journal Article %A Martinez-Laperche, Carolina %A Buces, Elena %A Aguilera-Morillo, M Carmen %A Picornell, Antoni %A Gonzalez-Rivera, Milagros %A Lillo, Rosa %A Santos, Nazly %A Martin-Antonio, Beatriz %A Guillem, Vicent %A Nieto, Jose B %A Gonzalez, Marcos %A de-la-Camara, Rafael %A Brunet, Salut %A Jimenez-Velasco, Antonio %A Espigado, Ildefonso %A Vallejo, Carlos %A Sampol, Antonia %A Bellon, Jose Maria %A Serrano, David %A Kwon, Mi %A Gayoso, Jorge %A Balsalobre, Pascual %A Urbano-Izpizua, Alvaro %A Solano, Carlos %A Gallardo, David %A Diez-Martin, Jose Luis %A Romo, Juan %A Buño, Ismael %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 < .001) and extensive cGVHD (P < .001). The novel predictive models proposed here improve the prediction of severe GVHD after allo-SCT. This approach could facilitate personalized risk-adapted clinical management of patients undergoing allo-SCT. %K Graft-versus-host disease %K Acute graft-versus-host disease %K Allogeneic stem cell transplantation %K Predictive model %K Cytokine gene polymorphism %K Single nucleotide polymorphisms %K Genetic risk factors %K Clinical variables %K Risk stratification %~