Risk-stratification in diffuse large B-cell lymphoma in the rituximab era

Abstract

Introduction. Diffuse large B-cell lymphoma represents a group of entities characterized by pathological and biological heterogeneity and different clinical outcomes. Due to pronounced heterogeneity, prognostic biomarkers are of great importance in identifying high-risk patients who might benefit from more aggressive approaches or new therapeutic modalities. Several prognostic score systems have been established and applied to predict the survival of patients with diffuse B-large cell lymphoma. The first established prognostic system for NHL patients is the International Prognostic Index, its variations Revised International Prognostic Index and National Comprehensive Cancer Network- International Prognostic Index were subsequently introduced in the era of immunochemotherapy. As the discriminative power of clinical scores is suboptimal, other strategies have been explored in order to improve risk stratification, especially in the high-risk group of patients who have the highest risk of treatment failure. In this regard, there is a tendency to integrate genetic and molecular biomarkers and prognostic somatic mutations into standardized and personalized models for risk stratification that would have a wide application in routine clinical practice. The results of recent studies based on machine learning methods have shown that the best risk stratification is achieved by a combination of clinical, genetic and molecular parameters, as well as a combination of clinical parameters with new quantitative Positron Emission Tomography parameters, such as Metabolic Tumor Volume and dissemination features and analysis of circulating tumor DNA levels. This paper provides an overview of studies in which these new risk stratification models were analyzed.