Remaining Challenges in Predicting Patient Outcomes for Diffuse Large B-cell Lymphoma

Overview

Journal Expert Rev Hematol

Specialty Hematology

Date 2019 Sep 13

PMID 31513757

Citations 15

Authors

R Andrew Harkins

Andres Chang

Sharvil P Patel

Michelle J Lee

Jordan S Goldstein

Selin Merdan

Christopher R Flowers

Jean L Koff

Affiliations

Soon will be listed here.

Abstract

Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma and is an aggressive malignancy with heterogeneous outcomes. Diverse methods for DLBCL outcomes assessment ranging from clinical to genomic have been developed with variable predictive and prognostic success. The authors provide an overview of the various methods currently used to estimate prognosis in DLBCL patients. Models incorporating cell of origin, genomic features, sociodemographic factors, treatment effectiveness measures, and machine learning are described. The clinical and genetic heterogeneity of DLBCL presents distinct challenges in predicting response to therapy and overall prognosis. Successful integration of predictive and prognostic tools in clinical trials and in a standard clinical workflow for DLBCL will likely require a combination of methods incorporating clinical, sociodemographic, and molecular factors with the aid of machine learning and high-dimensional data analysis.

Citing Articles

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