Hassan Awada, MD, on AML and Machine Learning: Improving Prognostication
2020 ASH Annual Meeting & Exposition
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).
The ASCO Post Staff
Jorge E. Cortes, MD, of the Georgia Cancer Center at Augusta University, reviews four important studies of treatment advances in chronic myeloid leukemia (CML): nilotinib vs dasatinib in newly diagnosed disease; final 5-year results from the BFORE trial on bosutinib vs imatinib for chronic phase (CP) CML; data from the OPTIC trial on ponatinib for CP-CML; and a novel class of mutated cancer-related genes associated with the Philadelphia translocation (Abstracts 45, 46, 48, 49).
The ASCO Post Staff
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).
The ASCO Post Staff
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).
The ASCO Post Staff
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).
The ASCO Post Staff
Jyoti Nangalia, MBBChir, of Wellcome Sanger Institute and the University of Cambridge, discusses how her team used large-scale whole-genome sequencing to precisely time the origins of a blood cancer and measure how it grew. The information could provide opportunities for early diagnosis and intervention (Abstract LBA-1).