Tycel J. Phillips, MD, on Marginal Zone Lymphoma: Efficacy and Safety of Parsaclisib
2020 ASH Annual Meeting & Exposition
Tycel J. Phillips, MD, of the University of Michigan Rogel Cancer Center, discusses phase II data from the CITADEL-204 study, showing that patients with relapsed or refractory marginal zone lymphoma who were not previously treated with a Bruton’s tyrosine kinase inhibitor achieved rapid and durable responses with single-agent parsaclisib. Comparable results were also observed in patients with nodal, extranodal, or splenic disease (Abstract 338).
Paul G. Richardson, MD, of Dana-Farber Cancer Institute, gives his expert perspective on three important studies in multiple myeloma: long-term results from the IFM 2009 trial on early vs late autologous stem cell transplant in patients with newly diagnosed disease; the effect of high-dose melphalan on mutational burden in relapsed disease; and daratumumab plus lenalidomide, bortezomib, and dexamethasone in transplant-eligible patients with newly diagnosed disease (Abstracts 143, 61, and 549).
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
Christian Marinaccio, PhD Candidate, of Northwestern University, describes research he is conducting in the laboratory of John D. Crispino, PhD, which shows the loss of the tumor suppressor gene LKB1/STK11 facilitates progression of myeloproliferative neoplasms to acute myeloid leukemia (Abstract 1).
The ASCO Post Staff
Meletios A. Dimopoulos, MD, of the University of Athens, discusses data from the phase III APOLLO study, which evaluated the use of subcutaneous daratumumab plus pomalidomide and dexamethasone, vs pomalidomide and dexamethasone alone, in patients with relapsed or refractory multiple myeloma (Abstract 412).
The ASCO Post Staff
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).
