Predicting early progression in follicular lymphoma

Follicular lymphoma is the most common indolent lymphoma and is associated with slow tumor growth, long responses to frontline therapy and—generally—favorable outcomes. However, a subset of patients has a more aggressive course with early progression after standard therapy. Recent evidence has demonstrated that 10–20% of patients who are treated with immunochemotherapy experience relapse within 24 months of diagnosis and these patients have a significantly worse outcome compared to those who do not. While well-established clinical risk factors allow to predict outcomes, risk-stratification is improved when considering molecular attributes such as gene mutations or gene expression profiles. Similarly, functional imaging allows to estimate the burden of disease prior to initiating therapy and provides useful information at the end of frontline therapy, allowing to distinguish those patients who achieve a complete metabolic response and have superior survival from patients who have residual, metabolically active lymphoma. Ongoing work focuses on predicting early progression with greater accuracy, which would enable the study of risk-adapted management strategies. Increasingly, risk indices are recognized to have differential prognostic impact based on the specific treatment under consideration. It is conceivable that future risk stratification will not only provide an estimate of prognosis, but also inform the most appropriate treatment choice. Herein, we describe the existing and emerging risk-stratification tools, based on clinical, molecular and imaging attributes, and review their ability to predict early progression.