Meletios A. Dimopoulos, MD, on Multiple Myeloma: Daratumumab, Pomalidomide, and Dexamethasone
2020 ASH Annual Meeting & Exposition
Meletios A. Dimopoulos, MD, of the University of Athens, discusses data from the phase III APOLLO study, which evaluated the use of subcutaneous daratumumab plus pomalidomide and dexamethasone, vs pomalidomide and dexamethasone alone, in patients with relapsed or refractory multiple myeloma (Abstract 412).
Andrew D. Zelenetz, MD, PhD, of Memorial Sloan Kettering Cancer Center, offers his expert views on five treatment studies in mantle cell lymphoma focusing on the next-generation BTK inhibitor LOXO-305; lisocabtagene maraleucel; minimal residual disease monitoring following autologous stem cell transplantation with or without rituximab maintenance; the antibody-drug conjugate VLS-101; and venetoclax, lenalidomide, and rituximab (Abstracts 117, 118, 120, 121, 122).
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).
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).
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).
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).