An AI model for transplant risk in myelofibrosis; preventing priapism in men with sickle cell anemia; hallmarks of T cell exhaustion absent in newly diagnosed MM

In this week's episode, we'll learn about using AI to assess transplant risk in myelofibrosis. In a step toward personalized medicine, researchers report on a machine learning model that identifies 25% of patients with poor outcomes. After that: preventing priapism in men with sickle cell anemia. A recent phase 2 feasibility study shows high rates of recruitment, retention, and adherence to oral therapies, coupled with a significant reduction in the risk of this difficult complication. Finally, new research indicates that hallmarks of terminal T-cell exhaustion are absent in multiple myeloma, from diagnosis through maintenance therapy. We explore these provocative and counterintuitive findings arising from profiling of blood and marrow samples.

Featured Articles:

• Use of machine learning techniques to predict poor survival after hematopoietic cell transplantation for myelofibrosis
• A controlled trial for preventing priapism in sickle cell anemia: hydroxyurea plus placebo vs hydroxyurea plus tadalafil
• Hallmarks of T-cell exhaustion and antigen experience are absent in multiple myeloma from diagnosis to maintenance therapy

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Stay up to date on the latest research and reviews for both clinical and basic hematology with Blood podcast, published weekly in conjunction with each issue of Blood. Additionally, Blood review series podcasts feature in depth discussion with authors of recently published review articles. Subscribe and never miss a new episode.