Predictive models may help in determining the risk/benefit ratio of allogeneic hematopoietic stem cell transplantation (HSCT) in acute leukemia (AL). Using a machine-learning algorithm we have previously developed the AL- European Society for Blood and Marrow Transplantation (EBMT) score for prediction of mortality following transplantation. We report here the first external validation of the AL-EBMT score in a cohort of AL patients from the Italian national transplantation network. A total of 1848 patients transplanted between the years 2000-2014 were analyzed. The median age was 45.9. Indications for HSCT were Acute Myeloid Leukemia (68.1%) and Acute Lymphoblastic Leukemia (31.9%). The majority of patients were in first complete remission (60.4%), and received myeloablative conditioning (81.3%). Median follow-up was 2 years. The score was well-calibrated for prediction of day 100 mortality and 2-year overall survival (OS), leukemia free survival (LFS), and nonrelapse related mortality, with corresponding area under the receiver-operator curves of 0.698, 0.651, 0.653, and 0.651, respectively. Increasing score intervals were associated with a decreasing probability of 2-year OS and LFS. The highest scoring group was associated with a hazard ratio of 3.16, 2.8, and 2.27 for 2-year OS, LFS, and NRM, respectively. In conclusion, the AL-EBMT score identified three distinct risk groups and was predictive of OS. It is a valid tool for stratifying the risk of acute leukemia patients undergoing allogeneic HSCT.
Validation of the acute leukemia-EBMT score for prediction of mortality following allogeneic stem cell transplantation in a multi-center GITMO cohort / R. Shouval, F. Bonifazi, J. Fein, C. Boschini, E. Oldani, M. Labopin, R. Raimondi, N. Sacchi, O. Dabash, R. Unger, M. Mohty, A. Rambaldi, A. Nagler. - In: AMERICAN JOURNAL OF HEMATOLOGY. - ISSN 0361-8609. - 92:5(2017 May), pp. 429-434. [10.1002/ajh.24677]
Validation of the acute leukemia-EBMT score for prediction of mortality following allogeneic stem cell transplantation in a multi-center GITMO cohort
A. RambaldiPenultimo
;
2017
Abstract
Predictive models may help in determining the risk/benefit ratio of allogeneic hematopoietic stem cell transplantation (HSCT) in acute leukemia (AL). Using a machine-learning algorithm we have previously developed the AL- European Society for Blood and Marrow Transplantation (EBMT) score for prediction of mortality following transplantation. We report here the first external validation of the AL-EBMT score in a cohort of AL patients from the Italian national transplantation network. A total of 1848 patients transplanted between the years 2000-2014 were analyzed. The median age was 45.9. Indications for HSCT were Acute Myeloid Leukemia (68.1%) and Acute Lymphoblastic Leukemia (31.9%). The majority of patients were in first complete remission (60.4%), and received myeloablative conditioning (81.3%). Median follow-up was 2 years. The score was well-calibrated for prediction of day 100 mortality and 2-year overall survival (OS), leukemia free survival (LFS), and nonrelapse related mortality, with corresponding area under the receiver-operator curves of 0.698, 0.651, 0.653, and 0.651, respectively. Increasing score intervals were associated with a decreasing probability of 2-year OS and LFS. The highest scoring group was associated with a hazard ratio of 3.16, 2.8, and 2.27 for 2-year OS, LFS, and NRM, respectively. In conclusion, the AL-EBMT score identified three distinct risk groups and was predictive of OS. It is a valid tool for stratifying the risk of acute leukemia patients undergoing allogeneic HSCT.File | Dimensione | Formato | |
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