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).
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).
Nitin Jain, MD, of The University of Texas MD Anderson Cancer Center, reviews six important abstracts on CAR T-cell treatments for B-cell acute lymphoblastic leukemia (ALL): successful 24-hour manufacture of CAR T-cell therapy; ALLCAR19, a novel fast-off rate therapy; donor-derived CD19-targeted treatment; CAR 2.0 therapy to manage post-transplant relapse; UCART22, allogeneic engineered T cells expressing anti-CD22 chimeric antigen receptor; and inotuzumab ozogamicin in pediatric CD-22–positive disease (Session 614, Abstracts 159-164).
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).
Corey Cutler, MD, MPH, of Dana-Farber Cancer Institute, discusses results from a multicenter trial that compared reduced-intensity allogeneic hematopoietic cell transplantation to hypomethylating therapy or best supportive care in patients aged 50 to 75 with advanced myelodysplastic syndromes (Abstract 75).
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).
