Radiographic Density, Cancer, Inheritance and Acquired Risk in Twins

Abstract

Computerized mammographic density measurements have been linked to breast cancer risk; the greater the breast density, the higher the risk of breast cancer. Our goals are to confirm if these observations are true within pairs of identical twins, to determine the heritability mammographic density, and to determine if adult exposures and experiences related to breast cancer risk result in modifications of mammographic density. We are interviewing both members of up to 2500 twin pairs registered in the California Twin Program about the risk factors of interest, collecting mammograms from each twin, scanning the films and measuring the densities, and comparing the measurements between co-twins in light of zygosity, past experiences, and the appearance of subsequent breast cancer. Thus far we have identified 1922 potentially eligible individuals from 961 pairs, contacted 1255, and have obtained the cooperation of 1043 or 83%. We have received formal signed consents for (temporary) release of the mammograms from 806 twins, and have received and scanned 1319 of the 1364 mammograms from 646 of these, including both twins from 307 pairs. Cooperation from twins and their providers has been excellent. Results will not be available until blinded readings of the scanned films are available.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1999
Accession Number
ADA381130

Entities

People

  • Thomas M. Mack

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Animals
  • Biomedical Research
  • Breast Cancer
  • California
  • Continents
  • Cooperation
  • Federal Law
  • Films
  • Interviewing
  • Laboratory Animals
  • Materials
  • Measurement
  • Neoplasms
  • Observation
  • Recombinant Dna
  • Risk Factors
  • Scanning

Fields of Study

  • Medicine
  • Physics

Readers

  • Clinical Trial Research.
  • Molecular and genetic basis of cancer.
  • Oncology and Biomarker-Based Cancer Detection.