Open AccessIntegrating Clinical and Polygenic Factors to Predict Breast Cancer Risk in Women Undergoing Genetic Testing
Author(s) -
Elisha Hughes,
Placede Tshiaba,
Susanne Wagner,
Thaddeus Judkins,
Eric T. Rosenthal,
Benjamin B. Roa,
Shan Gallagher,
Stephanie Meek,
Kathryn Dalton,
Wade Hedegard,
Carol A. Adami,
Danna Grear,
Susan M. Domchek,
Judy E. Garber,
Johnathan M. Lancaster,
Jeffrey N. Weitzel,
Allison W. Kurian,
Jerry S. Lanchbury,
Alexander Gutin,
Mark E. Robson
Publication year - 2021
Publication title -
jco precision oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.405
H-Index - 22
ISSN - 2473-4284
DOI - 10.1200/po.20.00246
Subject(s) - medicine , breast cancer , confounding , family history , logistic regression , cohort , oncology , polygenic risk score , risk assessment , framingham risk score , cancer , single nucleotide polymorphism , disease , genotype , genetics , gene , computer security , biology , computer science
Screening and prevention decisions for women at increased risk of developing breast cancer depend on genetic and clinical factors to estimate risk and select appropriate interventions. Integration of polygenic risk into clinical breast cancer risk estimators can improve discrimination. However, correlated genetic effects must be incorporated carefully to avoid overestimation of risk.