Ibrahim Aldoss, MD, on KMT2A-Rearranged Acute Leukemia: New Data on Revumenib Monotherapy
2023 ASH
Ibrahim Aldoss, MD, of City of Hope National Medical Center, discusses phase II safety and efficacy results from the Augment-101 study. This trial showed that patients with heavily pretreated, relapsed or refractory KMT2-rearranged acute leukemia benefited from monotherapy with the menin-KMT2A inhibitor revumenib, with high overall response rates and undetectable measurable residual disease (Abstract LBA-5).
The ASCO Post Staff
Mazyar Shadman, MD, MPH, of the University of Washington, discusses new data suggesting that in patients with relapsed large B-cell lymphoma who achieve a complete response, treatment with autologous transplantation may be associated with a lower relapse rate and improved progression-free survival compared with CAR T-cell therapy, including those with early treatment failure (Abstract 781).
The ASCO Post Staff
Mikkael A. Sekeres, MD, of the Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine, reviews key abstracts from ASH 2023 on treatment of myelofibrosis, chronic lymphocytic leukemia, large B-cell lymphoma, and acute myeloid leukemia (Abstracts 620, 631, 781, 425).
The ASCO Post Staff
Sarah C. Rutherford, MD, of Weill Cornell Medicine, discusses findings of the SWOG S1826 study, which showed nivolumab plus AVD (doxorubicin, vinblastine, and dacarbazine) improved progression-free and event-free survival and seemed to be better tolerated than brentuximab vedotin plus AVD in patients aged 60 and older with advanced-stage Hodgkin lymphoma (Abstract 181).
The ASCO Post Staff
Jeffrey E. Rubnitz, MD, PhD, of St. Jude Children’s Research Hospital, discusses study findings suggesting that pharmacogenomic differences between Black and White patients should be considered when tailoring induction regimens to improve outcomes of all patients and bridge the racial disparity gap in acute myeloid leukemia treatment (Abstract 386).
The ASCO Post Staff
Andrew Srisuwananukorn, MD, of The Ohio State University Comprehensive Cancer Center, discusses a novel artificial intelligence model that can distinguish between prefibrotic primary myelofibrosis and essential thrombocythemia. This proposed model may assist clinicians in identifying patients who may benefit from disease-specific therapies or enrollment in clinical trials (Abstract 901).
