Risk prediction methods

Cancer Epidemiology And Genetics

Investigators

Linked publications & trials

Abstract

We developed a relative risk model for projecting breast cancer risk that includes mammographic density, weight, family history, age at first live birth and number of previous breast biopsies. The model has modestly higher discriminatory power than the "Gail model" that does not include mammographic density. We coupled this model with data on the distribution of risk factors in the general population and with age-specific breast cancer rates from NCIs Surveillance, Epidemiology and End Results Program to develop a model for absolute invasive breast cancer risk based on the factors above.<br><br>We published data showing that NCIs Breast Cancer Risk Assessment Tool is well calibrated when applied to Italian populations.<br><br>We developed a model for projecting the risk of Breast Cancer for African American women based on data from the Cancer and Reproductive Experiences Study and SEER rates. This model usually produces higher risk projections than NCIs current Breast Cancer Risk Assessment Tool for women aged 50 and older, but somewhat lower risks in young women. This work includes assessment of the validity of the model with independent data from the Womens Health Initiative.<br><br>We submitted for publication absolute risk models for proximal and distal colon cancer and for rectal cancer. These models produce an absolute risk for the earliest of proximal colon cancer, distal colon cancer and rectal cancer. We also assessed the validity of the models using independent data from the AARP Cohort.<br>