A New Model for the Estimation of Breast Cancer Risk
Abstract
Cancer risk is the probability that cancer will occur in a given population. Research on cancer risk seeks to identify populations with a high probability of developing cancer. The goal of this research is to merge a computerized analysis of mammograms, which characterizes the breast pattern, with information of a woman's personal and family histories into a novel model for use in estimating risk of breast cancer. The specific aims include 1. Creating a database of mammograms, along with tabulated clinical information of women at low risk and high risk for breast cancer; 2. Developing a new model using computer methods for merging mammographic information with clinical information; and 3. Evaluating the efficacies of the new model compared to currently used methods of risk assessment. The main hypothesis to he tested is that given a group of women, the new computerized risk model that merges computerized analyses of mammograms with clinical information should yield a novel way for identifying those women at risk for breast cancer. To date, we have shown that computer-extracted features of mammographic parenchymal patterns can be used in the prediction of breast cancer risk. This has been demonstrated (on the developing database) using three approaches: (1) correlation with clinical models of Gail and Claus, (2) separation between women at low risk and those with a positive gene testing result, and (3) separation between women at low risk and those that have breast cancer. In addition, we have shown, in a preliminary study, that the inclusion of the mammographic features with age increase the predictive power over the use of age alone in the prediction of breast cancer risk.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 2001
- Accession Number
- ADA398217
Entities
People
- Maryellen Lissak Giger
Organizations
- University of Chicago