Steven M. Horwitz, MD, of Memorial Sloan Kettering Cancer Center, discusses phase II data from the Primo trial, which support continued evaluation of duvelisib as a treatment option for relapsed or refractory peripheral T-cell lymphoma due to consistent response rates (Abstract 44).
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).
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).
Paul G. Richardson, MD, of Dana-Farber Cancer Institute, gives his expert perspective on three important studies in multiple myeloma: long-term results from the IFM 2009 trial on early vs late autologous stem cell transplant in patients with newly diagnosed disease; the effect of high-dose melphalan on mutational burden in relapsed disease; and daratumumab plus lenalidomide, bortezomib, and dexamethasone in transplant-eligible patients with newly diagnosed disease (Abstracts 143, 61, and 549).
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).
