Danai Dima, MD, on Multiple Myeloma: Update on Safety and Efficacy of Teclistamab
2023 ASH
Danai Dima, MD, of the Taussig Cancer Institute, Cleveland Clinic, discusses teclistamab-cqyv, a B-cell maturation antigen approved in October 2022 for patients with relapsed or refractory multiple myeloma who have received at least four prior lines of therapy. Dr. Dima and her team evaluated the real-world safety and efficacy of this agent and found encouraging evidence of efficacy in a real-world setting (Abstract 91).
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
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
Bijal D. Shah, MD, of Moffitt Cancer Center and Research Institute, discusses a matching-adjusted indirect comparison of brexucabtagene autoleucel and pirtobrutinib in patients with relapsed or refractory mantle cell lymphoma who have been previously treated with a BTK inhibitor (Abstract 5136).
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
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).
