Evaluation and comparison of different breast cancer prognosis scores based on gene expression data.

ABSTRACT:

Background

Breast cancer is one of the three most common cancers worldwide and is the most common malignancy in women. Treatment approaches for breast cancer are diverse and varied. Clinicians must balance risks and benefits when deciding treatments, and models have been developed to support this decision-making. Genomic risk scores (GRSs) may offer greater clinical value than standard clinicopathological models, but there is limited evidence as to whether these models perform better than the current clinical standard of care.

Methods

PREDICT and GRSs were adapted using data from the original papers. Univariable Cox proportional hazards models were produced with breast cancer-specific survival (BCSS) as the outcome. Independent predictors of BCSS were used to build multivari

SUBMITTER: Chowdhury A 

PROVIDER: S-EPMC9906838 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature