Clinical and Multiomic Features Differentiate Young Black and White Breast Cancer Cohorts Derived by Machine Learning Approaches.
Journal:
Clinical breast cancer
PMID:
39706709
Abstract
BACKGROUND: There are documented differences in Breast cancer (BrCA) presentations and outcomes between Black and White patients. In addition to molecular factors, socioeconomic, racial, and clinical factors result in disparities in outcomes for women in the United States. Using machine learning and unsupervised biclustering methods within a multiomics framework, here we sought to shed light on the biological and clinical underpinnings of observed differences between Black and White BrCA patients.