Martinez-Laperche, CarolinaBuces, ElenaAguilera-Morillo, M CarmenPicornell, AntoniGonzalez-Rivera, MilagrosLillo, RosaSantos, NazlyMartin-Antonio, BeatrizGuillem, VicentNieto, Jose BGonzalez, Marcosde-la-Camara, RafaelBrunet, SalutJimenez-Velasco, AntonioEspigado, IldefonsoVallejo, CarlosSampol, AntoniaBellon, Jose MariaSerrano, DavidKwon, MiGayoso, JorgeBalsalobre, PascualUrbano-Izpizua, AlvaroSolano, CarlosGallardo, DavidDiez-Martin, Jose LuisRomo, JuanBuño, Ismael2023-01-252023-01-252018-07-24Martínez-Laperche C, Buces E, Aguilera-Morillo MC, Picornell A, González-Rivera M, Lillo R, et al. A novel predictive approach for GVHD after allogeneic SCT based on clinical variables and cytokine gene polymorphisms. Blood Adv. 2018 Jul 24;2(14):1719-1737.http://hdl.handle.net/10668/12734Despite 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.enGraft-versus-host diseaseAcute graft-versus-host diseaseAllogeneic stem cell transplantationPredictive modelCytokine gene polymorphismSingle nucleotide polymorphismsGenetic risk factorsClinical variablesRisk stratificationAdolescentAdultAgedAllograftsChildChild, PreschoolCytokinesFemaleFollow-Up StudiesGraft vs Host DiseaseHematologic NeoplasmsHumansInfantInfant, NewbornMaleMiddle AgedModels, GeneticPolymorphism, GeneticRetrospective StudiesStem Cell Transplantationresearch article30030270Restricted AccessEnfermedad injerto contra huéspedTrasplante de células madre hematopoyéticaHermanosAntígenos de histocompatibilidad clase ICitoquinasMedicina de precisiónFrecuencia génica10.1182/bloodadvances.20170115022473-9537PMC6058238https://ashpublications.org/bloodadvances/article-pdf/2/14/1719/881097/advances011502.pdfhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6058238/pdf