For the majority of patients with newly diagnosed follicular lymphoma (FL), current treatments, while not curative, allow for long remission durations. However, several important needs remain unaddressed. Studies have consistently shown that ~20% of patients with FL experience disease progression within 2 years of first-line treatment, and consequently have a 50% risk of death in 5 years. Better characterization of this group of patients at diagnosis may provide insight into those in need of alternate or intensive therapies, facilitate a precision approach to inform clinical trials, and allow for improved patient counseling. Prognostic methods to date have employed clinical parameters, genomic methods, and a wide assortment of biological and biochemical markers, but none so far has been able to adequately identify this high-risk population. Advances in the first-line treatment of FL with chemoimmunotherapy have led to a median progression-free survival (PFS) of approximately 7 years; creating a challenge in the development of clinical trials where PFS is a primary end point. A surrogate end point that accurately predicts PFS would allow for new treatments to reach patients with FL sooner, or lessen toxicity, time, and expense to those patients requiring little to no therapy. Quality of response to treatment may predict PFS and overall survival in FL; as such complete response rates, either alone or in conjunction with PET imaging or minimal residual disease negativity, are being studied as surrogates, with complete response at 30months after induction providing the strongest surrogacy evidence to date. A better understanding of how to optimize quality of life in the context of this chronic illness is another important focus deserving of further study. Ongoing efforts to address these important unmet needs are herein discussed.
CITATION STYLE
Casulo, C., Nastoupil, L., Fowler, N. H., Friedberg, J. W., & Flowers, C. R. (2017, September 1). Unmet needs in the first-line treatment of follicular lymphoma. Annals of Oncology. Oxford University Press. https://doi.org/10.1093/annonc/mdx189
Mendeley helps you to discover research relevant for your work.