Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • My Cart

Search

  • Advanced search
Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

Research Articles

Inference about Causation from Examination of Familial Confounding: Application to Longitudinal Twin Data on Mammographic Density Measures that Predict Breast Cancer Risk

Jennifer Stone, Gillian S. Dite, Graham G. Giles, Jennifer Cawson, Dallas R. English and John L. Hopper
Jennifer Stone
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Gillian S. Dite
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Graham G. Giles
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jennifer Cawson
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dallas R. English
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John L. Hopper
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1158/1055-9965.EPI-12-0051 Published July 2012
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Figure 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1.

    A, square root dense area by age at time 1 and time 2. Random sample of N = 100 subjects. B, square root percentage dense area by age at time 1 and time 2. Random sample of N = 100 subjects.

  • Figure 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 2.

    A, age- and BMI-adjusted square root dense area at time 1 versus time 2. B, age- and BMI-adjusted square-root percentage dense area at time 1 versus time 2.

Tables

  • Figures
  • Table 1.

    Mean and SD of characteristics of subjects by zygosity

    CharacteristicMonozygotic pairs (N = 204) Mean (SD)Dizygotic pairs (N = 123) Mean (SD)
    Age at mammogram time 1, y49.75 (7.71)50.76 (8.61)
    Age at mammogram time 2, y57.61 (7.87)58.83 (8.60)
    Difference in age between times 1 and 2, y7.87 (1.57)8.06 (1.45)
    BMI at time 1, kg/m224.75 (4.17)25.12 (4.44)
    BMI at time 2, kg/m225.65 (4.33)25.95 (4.58)
    Dense area at time 1, cm230.77 (21.65)32.73 (23.70)
    Dense area at time 2, cm225.87 (20.01)28.76 (23.16)
    Percent dense area at time 129.92 (17.96)30.37 (18.60)
    Percent dense area at time 222.64 (15.78)23.41 (15.91)
  • Table 2.

    Estimates and SEs of the cross-time correlation between 2 mammograms within the same individual and of the cross-time cross-twin correlation between time 1 mammogram in one twin and time 2 mammogram in the other twin

    Dense areaaPercent dense areaa
    Estimate (SE)PEstimate (SE)P
    Correlation within same individual0.86 (0.01)<0.0010.82 (0.01)<0.001
    Monozygotic cross-correlation0.71 (0.03)<0.0010.65 (0.03)<0.001
    Dizygotic cross-correlation0.25 (0.07)<0.0010.20 (0.08)0.01
    • ↵aResiduals after square root transformation and adjustment for age and BMI.

  • Table 3.

    Regression estimates and SEs of association between mammographic measures at time 2 and mammographic measures at time 1 adjusting for co-twin and/or zygosity; N = 654

    Dense areaaPercent dense areaa
    Estimate (SE)PEstimate (SE)P
    Model I
     Self0.86 (0.021)<0.0010.77 (0.022)<0.001
     Co-twin
    Model IIa
     Self
     Co-twin0.78 (0.024)<0.0010.66 (0.027)<0.001
    Model IIb
     Self
     Co-twin
      MZ0.84 (0.031)<0.0010.73 (0.035)<0.001
      DZ0.63 (0.042)<0.0010.42 (0.046)<0.001
    Model IIIa
     Self0.83 (0.020)<0.0010.75 (0.023)<0.001
     Co-twin0.063 (0.022)0.0040.066 (0.023)0.004
    Model IIIb
     Self0.82 (0.020)<0.0010.74 (0.025)<0.001
     Co-twin
      MZ0.090 (0.031)0.0040.100 (0.032)0.002
      DZ0.035 (0.031)0.30.029 (0.033)0.4
    • ↵aResiduals after square root transformation and adjustment for age and BMI.

PreviousNext
Back to top
Cancer Epidemiology Biomarkers & Prevention: 21 (7)
July 2012
Volume 21, Issue 7
  • Table of Contents
  • Table of Contents (PDF)

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Cancer Epidemiology, Biomarkers & Prevention article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Inference about Causation from Examination of Familial Confounding: Application to Longitudinal Twin Data on Mammographic Density Measures that Predict Breast Cancer Risk
(Your Name) has forwarded a page to you from Cancer Epidemiology, Biomarkers & Prevention
(Your Name) thought you would be interested in this article in Cancer Epidemiology, Biomarkers & Prevention.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Inference about Causation from Examination of Familial Confounding: Application to Longitudinal Twin Data on Mammographic Density Measures that Predict Breast Cancer Risk
Jennifer Stone, Gillian S. Dite, Graham G. Giles, Jennifer Cawson, Dallas R. English and John L. Hopper
Cancer Epidemiol Biomarkers Prev July 1 2012 (21) (7) 1149-1155; DOI: 10.1158/1055-9965.EPI-12-0051

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Inference about Causation from Examination of Familial Confounding: Application to Longitudinal Twin Data on Mammographic Density Measures that Predict Breast Cancer Risk
Jennifer Stone, Gillian S. Dite, Graham G. Giles, Jennifer Cawson, Dallas R. English and John L. Hopper
Cancer Epidemiol Biomarkers Prev July 1 2012 (21) (7) 1149-1155; DOI: 10.1158/1055-9965.EPI-12-0051
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Disclosure of Potential Conflicts of Interest
    • Authors' Contributions
    • Grant Support
    • Acknowledgments
    • References
  • Figures & Data
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • Urinary Melatonin in Relation to Breast Cancer Risk
  • Endometrial Cancer and Ovarian Cancer Cross-Cancer GWAS
  • Risk Factors of Subsequent CNS Tumor after Pediatric Cancer
Show more Research Articles
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook   Twitter   LinkedIn   YouTube   RSS

Articles

  • Online First
  • Current Issue
  • Past Issues

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Cancer Epidemiology, Biomarkers & Prevention

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Cancer Epidemiology, Biomarkers & Prevention
eISSN: 1538-7755
ISSN: 1055-9965

Advertisement