Navigating Continuous and Fixed-Duration Therapies for Treatment-Naive CLL
Panelist discusses how patient preference significantly impacts treatment selection and describes the process of involving patients in treatment decisions while considering disease characteristics, cytogenetics, and the fact that higher-risk patients may fare better with specific regimens.
Video content above is prompted by the following:
Patient preference plays a crucial role in chronic lymphocytic leukemia (CLL) treatment selection, with physicians increasingly involving patients in shared decision-making processes. When counseling newly diagnosed CLL patients requiring therapy, oncologists present detailed comparisons of continuous vs fixed duration options, including expected visit schedules, adverse effect profiles, and quality of life considerations. This collaborative approach recognizes that CLL patients have diverse needs, lifestyles, and priorities that significantly impact treatment adherence and satisfaction.
The complexity of CLL treatment decisions extends beyond patient preference to include disease-specific factors such as cytogenetics and genetic mutations. CLL is not a uniform disease, with patients presenting varying risk levels based on genetic abnormalities that influence treatment response and long-term outcomes. High-risk vs low-risk disease classifications help guide therapy selection, as emerging long-term follow-up data suggests certain patient populations may benefit more from specific treatment regimens than others.
Bruton tyrosine kinase (BTK) inhibitor selection in frontline CLL has evolved with the development of next-generation agents like acalabrutinib and zanubrutinib, which offer improved safety profiles compared to ibrutinib. While ibrutinib combinations, particularly with venetoclax in the CAPTIVATE study, demonstrated the first dual oral fixed-duration approach, newer BTK inhibitors in combination with venetoclax show promising efficacy data. The choice between these agents often depends on physician familiarity, patient-specific factors, and available clinical trial data supporting optimal combinations for individual risk profiles.
