Epstein-Barr virus(EBV)reactivation is one of the most important infections after hematopoietic stem cell transplantation(HSCT)using haplo-identical related donors(HID).We aimed to establish a comprehensive model with...Epstein-Barr virus(EBV)reactivation is one of the most important infections after hematopoietic stem cell transplantation(HSCT)using haplo-identical related donors(HID).We aimed to establish a comprehensive model with machine learning,which could predict EBV reactivation after HID HSCT with anti-thymocyte globulin(ATG)for graft-versus-host disease(GVHD)prophylaxis.We enrolled 470 consecutive acute leukemia patients,60%of them(n=282)randomly selected as a training cohort,the remaining 40%(n=188)as a validation cohort.The equation was as follows:Probability(EBV reactivation)=1/1+exp(−Y),where Y=0.0250×(age)–0.3614×(gender)+0.0668×(underlying disease)–0.6297×(disease status before HSCT)–0.0726×(disease risk index)–0.0118×(hematopoietic cell transplantation-specific comorbidity index[HCT-CI]score)+1.2037×(human leukocyte antigen disparity)+0.5347×(EBV serostatus)+0.1605×(conditioning regimen)–0.2270×(donor/recipient gender matched)+0.2304×(donor/recipient relation)–0.0170×(mononuclear cell counts in graft)+0.0395×(CD34+cell count in graft)–2.4510.The threshold of probability was 0.4623,which separated patients into low-and high-risk groups.The 1-year cumulative incidence of EBV reactivation in the low-and high-risk groups was 11.0%versus 24.5%(P<.001),10.7%versus 19.3%(P=.046),and 11.4%versus 31.6%(P=.001),respectively,in total,training and validation cohorts.The model could also predict relapse and survival after HID HSCT.We established a comprehensive model that could predict EBV reactivation in HID HSCT recipients using ATG for GVHD prophylaxis.展开更多
基金the Program of the National Natural Science Foundation of China(grant number 82170208)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(grant number 81621001)+2 种基金the CAMS Innovation Fund for Medical Sciences(CIFMS)(grant number 2019-I2M-5-034)the Key Program of the National Natural Science Foundation of China(grant number 81930004)the Fundamental Research Funds for the Central Universities,National Natural Science Foundation of China(No.62102008).
文摘Epstein-Barr virus(EBV)reactivation is one of the most important infections after hematopoietic stem cell transplantation(HSCT)using haplo-identical related donors(HID).We aimed to establish a comprehensive model with machine learning,which could predict EBV reactivation after HID HSCT with anti-thymocyte globulin(ATG)for graft-versus-host disease(GVHD)prophylaxis.We enrolled 470 consecutive acute leukemia patients,60%of them(n=282)randomly selected as a training cohort,the remaining 40%(n=188)as a validation cohort.The equation was as follows:Probability(EBV reactivation)=1/1+exp(−Y),where Y=0.0250×(age)–0.3614×(gender)+0.0668×(underlying disease)–0.6297×(disease status before HSCT)–0.0726×(disease risk index)–0.0118×(hematopoietic cell transplantation-specific comorbidity index[HCT-CI]score)+1.2037×(human leukocyte antigen disparity)+0.5347×(EBV serostatus)+0.1605×(conditioning regimen)–0.2270×(donor/recipient gender matched)+0.2304×(donor/recipient relation)–0.0170×(mononuclear cell counts in graft)+0.0395×(CD34+cell count in graft)–2.4510.The threshold of probability was 0.4623,which separated patients into low-and high-risk groups.The 1-year cumulative incidence of EBV reactivation in the low-and high-risk groups was 11.0%versus 24.5%(P<.001),10.7%versus 19.3%(P=.046),and 11.4%versus 31.6%(P=.001),respectively,in total,training and validation cohorts.The model could also predict relapse and survival after HID HSCT.We established a comprehensive model that could predict EBV reactivation in HID HSCT recipients using ATG for GVHD prophylaxis.
