William G. Wierda, MD, PhD, on Use of Pirtobrutinib for Richter Transformation: Updated Efficacy and Safety Results
2023 ASH
William G. Wierda, MD, PhD, of The University of Texas MD Anderson Cancer Center, discusses results from the phase I/II BRUIN study, which shows encouraging response and overall survival in patients with Richter transformation. Although this condition remains a challenging diagnosis, pirtobrutinib represents a potential treatment option that warrants further investigation, according to Dr. Wierda (Abstract 1737).
The ASCO Post Staff
Adam S. Kittai, MD, of The Ohio State University, discusses his data supporting the use of CAR T-cell therapy for patients with Richter’s transformation. Given the high response rate to CD19 CAR T-cell treatment, along with early relapse in most patients, allogeneic stem cell transplantation at response should also be considered, he says (Abstract 108).
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
Hamish S. Scott, PhD, and Chris Hahn, PhD, both of Australia’s SA Pathology and Centre for Cancer, discuss ERG, a new predisposition gene for bone marrow failure and hematologic malignancy. Identifying causal germline ERG variants has direct clinical implications for diagnosis, counseling, surveillance, and treatment strategies, according to Drs. Scott and Hahn (Abstract LBA5).
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).
