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).
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]).
Caron A. Jacobson, MD, of the Dana-Farber Cancer Institute, discusses results from the ZUMA-9 C2 study, an ongoing trial that is exploring axicabtagene ciloleucel in patients with relapsed or refractory large B-cell lymphoma (Abstract 2100).
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).
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).
Lena E. Winestone, MD, MSHP, of the University of California, San Francisco and Benioff Children’s Hospital, reviews different aspects of bias in treatment delivery, including patient selection for clinical trials; racial and ethnic disparities in survival for indolent non-Hodgkin diffuse large B-cell lymphomas; and end-of-life hospitalization of patients with multiple myeloma, as well as outcome disparities (Abstracts 207-212).
