||1U01CA249866-01 Interpret this number
||Harvard School Of Public Health
||Multifactoral Breast Cancer Risk Prediction Accounting for Ethnic and Tumor Diversity
Breast cancer risk assessment tools are widely used in clinical practice to guide decisions regarding screening
timing and modality, life-style interventions, genetic testing, preventive therapy, and risk-reducing surgery.
Although a number of tools are used in practice, they face various challenges including: (i) modest
discriminatory ability due to lack of a unified model that incorporates a comprehensive set of risk-factors; (ii)
inability to produce sub-type specific risk, especially considering aggressive subtypes of breast cancer and/or
prophylactic endocrine therapy that is effective only for hormone receptor positive tumors; (iii) lack of data to
build models for different ethnic populations; and, (iv) scant validation of models, especially in healthcare
settings where models can be widely disseminated in practice. In this proposal, we will assimilate and analyze
data on a large and diverse sample of women from studies participating in the NCI Cohort Consortium to
develop a comprehensive tool that will predict breast cancer risk, overall and by sub-types, across major ethnic
groups in the US. We further propose to prospectively validate the model in different clinical settings, including
a risk-stratified screening trial. In Aim 1 we will develop a comprehensive model for predicting absolute risk of
overall breast cancer for women from multiple ethnicities, incorporating information on family history; polygenic
risk-scores (PRS); anthropometric, life-style and reproductive factors; hormonal biomarkers; and
mammographic density. In Aim 2 we will tailor these risk models to specific breast cancer subtypes, notably
estrogen receptor negative and positive cancers. In Aim 3 we will evaluate the validity of these risk prediction
models in integrated health care systems, mammography registries, and an ongoing risk-based
mammographic screening trial in the US. The resulting models could be used in diverse clinical settings to
guide preventive therapy or risk-stratified screening programs, increasing the number of breast cancer deaths
prevented while minimizing overdiagnosis and overtreatment.
Potential utility of risk stratification for multicancer screening with liquid biopsy tests.
, Scharpf R.B.
, Garcia-Closas M.
, Visvanathan K.
, Velculescu V.E.
, Chatterjee N.
NPJ precision oncology, 2023-04-22; 7(1), p. 39.
Polygenic risk scores for prediction of breast cancer in Korean women.
, Ho W.K.
, Park S.
, Easton D.F.
, Teo S.H.
, Jung K.J.
, Kraft P.
International journal of epidemiology, 2022-11-07; , .