Predicting the Future: Machine-Based Learning for MRD Prognostication

Abstract

The prognostic significance of minimal residual disease (MRD) detection in multiple myeloma is well established. Understanding factors that predict for MRD negativity, such as tumor burden, cytogenetic, and immune-related biomarkers, may enable us to improve outcome prediction at diagnosis, and in the future move toward tailored treatment approaches.