The European Society for Blood and Marrow Transplantation - Alternating Decision Tree (EBMT-ADT) prediction model for mortality 100 days following allogeneic hematopoietic stem cell transplantation

The EBMT-ADT is machine learning based prediction model, developed and validated on a cohort of 28,236 acute leukemia patients from the EBMT Acute Leukemia Working Party registry. It estimates the risk for overall mortality 100 days following an allogeneic hematopoietic transplantation (Shouval R, Labopin M, et. al., Journal of Clinical Oncology, 2015). Though not defined as the primary objective of the study, the model is also predictive of outcomes 2 years post-transplant.

Choose which of the following features apply to your patient:

Age of recipient at allogeneic hematopoietic stem cell transplantation (allo-HSCT)

Karnofsky performance status at time of allo-HSCT

Diagnosis

Disease stage

Interval (days) from diagnosis to transplant:

Less than 142 days

Donor recipient CMV serostatus combination

Donor type

Conditioning

Annual number of allo-HSCTs performed in the transplant medical center


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