Validation of the acute leukemia‐EBMT score for prediction of mortality following allogeneic stem cell transplantation in a multi‐center GITMO cohort

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.

An Integrative Scoring System for Survival Prediction Following Umbilical Cord Blood Transplantation in Acute Leukemia

“…Its potential applications include pretransplant risk assessment and stratification, interpretation and analysis of retrospective data, patient counseling during informed consent sessions, and tailoring transplant regimens or referring to alternative treatments according to transplantation risk. The score's discrimination (i.e., AUC) is comparable to similar prognostic models in HSCT (26,28,38); integration of detailed data on comorbidities, transplant regimens, and the genetic features of the disease may further enhance predictive accuracy, allowing for individualized prediction rather than stratification.…”

Biomarkers for Allogeneic HCT Outcomes

“…In a retrospective study of 28,236 HCT-patients from the European Blood and Marrow Transplantation (EBMT) registry, 10/20 variables were selected by the alternating decision tree (ADTree) model for overall mortality at 100 days post-HCT which performed better than the classical EBMT score (AUC of 0.701 vs. 0.646, p < 0.001) (46). Using the same algorithm, they confirmed this finding in a smaller cohort of 1,848 patients from the Italian Transplantation registry (GITMO) (AUC of 0.698 for day 100 mortality) (47). Furthermore, a recent study from the Japanese Transplant Registry asked with similar method (ADTree) if they would predict aGVHD grade II-IV in a cohort of 26,695 HCT patients.…”

Improved prognosis with additional medium‐dose VP16 to CY/TBI in allogeneic transplantation for high risk ALL in adults

“…Subgroup analyses of NRM examining patient age also supported the rationale for the addition of VP16. Herein, NRM was strongly associated with patient age, as in other reports, but no significant difference in NRM was found between the VP16/CY/TBI and CY/TBI regimens in each patient age group. These data indicate that patients who are tolerant to CY/TBI, as the myeloablative regimen, are also tolerant to VP16/CY/TBI, especially in the cohort mainly composed of younger patients, and suggest that the indications for the VP16/CY/TBI regimen should be the same as those for the CY/TBI regimen from the viewpoint of adverse events and NRM.…”