Research
Chronic Malignancies Working Party (CMWP)
A new machine learning model developed by the EBMT significantly improves the assessment of transplant risks in patients with myelofibrosis. This tool outperforms traditional statistical methods by more accurately identifying high-risk individuals, including a subgroup with a 40% chance of mortality within a year post-transplant.
Published in Blood, the model is based on data from over 5,000 patients and aims to support clinicians in making more informed decisions about allogeneic stem cell transplantation—the only curative treatment for myelofibrosis.
To learn more, watch the EBMT TV interview with study’s lead authors, Juan Carlos Hernández-Boluda and Adrián Mosquera Orgueira and read the press release.