Computer Simulation of Breast Cancer Screening

Abstract

Breast cancer will affect approximately 12.5% of the women in the United States, and currently mammographic screening is considered the best way to reduce mortality from this disease through early detection. There is much controversy concerning the most appropriate screening parameters such as starting age, the screening interval, and the stopping age. Long term multi-center clinical trials are the traditional approach to evaluating the efficacy of a medical test such as mammography, however clinical trials are expensive and lengthy. This grant focuses on the use of computer simulation techniques for evaluating the screening efficacy of mammography. Breast cancer growth rates, incidence rates, multiracial population demographics, death rates, breast cancer prognosis factors, breast density considerations, detection versus diameter probabilities, and other pertinent data have been computer fit and incorporated into a breast cancer screening simulator. The simulator is capable of producing many types of results data, including survival curves, tumor size distributions at detection, and "years of life saved" statistics. We are currently in the process of validating the simulator output with the results from respected clinical trials. Once validated, the screening simulator will be useful for studying ways in which the timing of the mammography examination can be optimized.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1999
Accession Number
ADA383107

Entities

People

  • John M. Boone

Organizations

  • University of California

Tags

DTIC Thesaurus Topics

  • Body Weight
  • Breast Cancer
  • Cancer Screening
  • Clinical Trials
  • Computer Simulations
  • Computers
  • Databases
  • Demography
  • Detection
  • Diseases And Disorders
  • Gray Scale
  • Health Services
  • Medical Personnel
  • Neoplasms
  • Simulations
  • Simulators
  • Statistics

Fields of Study

  • Medicine

Readers

  • Computational Modeling and Simulation
  • Oncology and Biomarker-Based Cancer Detection.
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.