
Treatment Sequencing Considerations
Expert panel shares real-world steps to start CD20xCD3 bispecifics for relapsed DLBCL, coordinating outpatient care and managing CRS/ICANS.
Dr. Lori Muffly from Stanford University and Dr. Jae Park from Memorial Sloan Kettering Cancer Center introduce this OncLive Insights program on CAR T-cell therapies in relapsed/refractory acute lymphoblastic leukemia. The discussion begins with treatment sequencing challenges in first relapse, where multiple therapeutic options now exist including targeted immunotherapies and CAR T-cell therapy.
Dr. Park emphasizes that treatment selection requires establishing the therapy goal, whether transplant remains an option and what approach will most likely achieve minimal residual disease (MRD)-negative remission. Key decision factors include prior treatment history, particularly frontline blinatumomab or inotuzumab exposure, disease burden, extramedullary disease status, and central nervous system (CNS) involvement. For high-burden disease patients, intravenous blinatumomab may be suboptimal, favoring CAR T-cell therapy or inotuzumab for CD38-antibody-naïve patients without liver disease.
The complexity extends beyond simple algorithmic approaches, as patient-specific factors including antigen expression status (CD19/CD22), current comorbidities, and individual disease characteristics influence optimal therapy selection. Dr. Park notes that even conventional chemotherapy may be reasonable for patients with late-relapse who remain chemosensitive. This individualized approach necessitates specialized center expertise for careful review before treatment selection.
Dr. Muffly agrees that ALL treatment cannot follow one-size-fits-all pathways because of significant patient individuality and multifactorial decision-making requirements. The discussion establishes the foundation that effective treatment sequencing requires comprehensive patient assessment beyond simple treatment history, considering disease biology, patient factors, and therapeutic goals to optimize outcomes in this complex disease landscape.






































































