Building a Better Model: A Personalized Breast Cancer Risk Model Incorporating Breast Density to Stratify Risk and Improve Application of Resources

Abstract

This project is aimed at meeting informational needs by moving the nation from guidelines based on population averages to recommendations based on an individual s risk beginning with personalized mammography screening decisions. This will be done by increasing the ability to predict a women s risk of developing breast cancer by adding a strong risk factor breast density to current risk-assessment equations or algorithms. Our plan is, over three years, to build and initially validate a comprehensive breast cancer risk model. The overall work will require the recruitment of 1000 cases (breast cancer patients) and 3000 controls (non-breast cancer patients) from whom we will collect extensive risk factor information and breast density based on digital mammograms previously obtained at UVa. Breast cancer risk information is largely already available for cases though patients will be requested to validate and complete data. The recruitment of 3000 control patients will require engagement with the community through appropriate messaging and marketing. The measurement of breast density using automated methods will be optimized during this study through the evaluation of outlier correction, comparison of several different software methods, precision measurement, and evaluation of variation by mammography machine vendor. Once the model is complete, tested nationally, and proven accurate, it will be available for widespread use within five to six years.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2013
Accession Number
ADA600478

Entities

People

  • Jennifer A Harvey
  • M. Yaffe
  • Wendy F. Cohn

Organizations

  • University of Virginia

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Biomedical Research
  • Breast Cancer
  • Cancer Screening
  • Commerce
  • Data Acquisition
  • Data Sets
  • Detection
  • Families (Human)
  • Health Care
  • Health Services
  • Institutional Review Board
  • Medical Personnel
  • Mobile Phones
  • Neoplasms
  • Social Media
  • Two Dimensional

Fields of Study

  • Medicine

Readers

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