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 myelofibrosisA controlled trial for preventing priapism in sickle cell anemia: hydroxyurea plus placebo vs hydroxyurea plus tadalafilHallmarks of T-cell exhaustion and antigen experience are absent in multiple myeloma from diagnosis to maintenance therapy

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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