Ann-Kathrin Eisfeld, MD, of The Ohio State University Comprehensive Cancer Center, discusses SEER data showing that patients with acute myeloid leukemia who are Black and younger than age 60 may have poor survival outcomes, a disparity that should be addressed and further studied to establish molecular risk profiles (Abstract 6).
Steven M. Horwitz, MD, of Memorial Sloan Kettering Cancer Center, discusses data from the largest multicenter retrospective analysis of allogeneic hematopoietic transplantation, which supports its curative potential in patients with mature T-cell lymphoma, a group marked by poor survival and limited treatment options (Abstract 41).
Smita Bhatia, MD, MPH, and Radhika Gangaraju, MD, both of the Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, discuss findings that showed survivors of bone marrow transplants are at a 7- to 12-fold higher risk of coronary heart disease than a sibling comparison group. They recommend aggressive management of cardiovascular risk factors to prevent morbidity from heart disease in this patient population (Abstract 73).
Matthew S. Davids, MD, of Dana-Farber Cancer Institute, summarizes three key studies from a session he co-moderated on ibrutinib plus venetoclax for first-line treatment of patients with chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL), long-term responses to these agents for relapsed and refractory CLL, and undetectable minimal residual disease following fixed-duration treatment with venetoclax and rituximab for CLL (Abstracts 123, 124, and 125).
Curtis Lachowiez, MD, of The University of Texas MD Anderson Cancer Center, discusses an interim analysis of a phase Ib/II study showing that venetoclax plus chemotherapy represents an effective regimen, particularly in patients with newly diagnosed and relapsed or refractory acute myeloid leukemia. The regimen appears to be an effective bridge to hematopoietic stem cell transplantation (Abstract 332).
Hassan Awada, MD, of the Taussig Cancer Institute, Cleveland Clinic Foundation, discusses the use of newer machine-learning techniques to help decipher a set of prognostic subgroups that could predict survival, thus potentially improving on traditional methods and moving acute myeloid leukemia into the era of personalized medicine (Abstract 34).
