Feasibility of risk assessment for breast cancer molecular subtypes.

ABSTRACT:

Purpose

Few breast cancer risk assessment models account for the risk profiles of different tumor subtypes. This study evaluated whether a subtype-specific approach improves discrimination.

Methods

Among 3389 women who had a screening mammogram and were later diagnosed with invasive breast cancer we performed multinomial logistic regression with tumor subtype as the outcome and known breast cancer risk factors as predictors. Tumor subtypes were defined by expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) based on immunohistochemistry. Discrimination was assessed with the area under the receiver operating curve (AUC). Absolute risk of each subtype was estimated by proportioning Gail absolute risk estimates by

SUBMITTER: McCarthy AM 

PROVIDER: S-EPMC11452472 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature