Predicting breast cancer risk in a racially diverse, community-based sample of potentially high-risk women.

ABSTRACT:

Background

Identifying women with high risk of breast cancer is necessary to study high-risk experiences and deliver risk-management care. Risk prediction models estimate individuals' lifetime risk but have rarely been applied in community-based settings among women not yet receiving specialized care. Therefore, we aimed: (1) to apply three breast cancer risk prediction models (i.e., Gail, Claus, and IBIS) to a racially diverse, community-based sample of women, and (2) to assess risk prediction estimates using survey data.

Methods

An online survey was administered to women who were determined by a screening instrument to have potentially high risk for breast cancer. Risk prediction models were applied using their self-reported family and medical history information. Inclusio

SUBMITTER: Meadows RJ 

PROVIDER: S-EPMC9636513 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature