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).
Sagar Lonial, MD, of the Emory University School of Medicine, summarizes key papers presented in a session he co-moderated on how second-generation CAR T cells can be used to treat patients with multiple myeloma (Session 653).
Ari M. Melnick, MD, of Weill Cornell Medicine, discusses the BCL10 mutation in patients with activated B-cell–like diffuse large B-cell lymphoma, and his study results which showed that the mutation should be considered as a biomarker for ibrutinib resistance so that alternative targeted treatments can be prioritized (Abstract 3).
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).
Sara Zarnegar-Lumley, MD, of Vanderbilt University Medical Center, discusses an analysis of a large cohort confirming the age-associated prevalence of IDH mutations in patients, across the age spectrum, with acute myeloid leukemia and therapeutic implications. IDH-mutated genes were found to co-occur frequently with other mutations, some of which favorably impact outcomes in patients younger than 60 (Abstract 388).
Farhad Ravandi, MD, of The University of Texas MD Anderson Cancer Center, offers his expert perspective on key treatment studies in acute myeloid leukemia on the use of gilteritinib, consolidation chemotherapy, venetoclax, cladribine, azacitidine, quizartinib, decitabine, and CPX-351 (Session 616 [Abstracts 24- 29]).
