Projecting Absolute Invasive Breast Cancer Risk in White Women With a Model That Includes Mammographic Density (original) (raw)

Journal Article

,

Affiliations of authors: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA (JC); Information Management Services, Rockville, MD (DP, RA); Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (BG, CS, MHG); Cancer Genetics and Epidemiology Program, Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC (CB); Medical School, Rouen University Hospital, Inserm U 657, Rouen, France (JB)

Correspondence to: Mitchell H. Gail, MD, PhD, Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892 (e-mail: gailm@mail.nih.gov ).

Search for other works by this author on:

,

Affiliations of authors: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA (JC); Information Management Services, Rockville, MD (DP, RA); Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (BG, CS, MHG); Cancer Genetics and Epidemiology Program, Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC (CB); Medical School, Rouen University Hospital, Inserm U 657, Rouen, France (JB)

Search for other works by this author on:

,

Affiliations of authors: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA (JC); Information Management Services, Rockville, MD (DP, RA); Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (BG, CS, MHG); Cancer Genetics and Epidemiology Program, Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC (CB); Medical School, Rouen University Hospital, Inserm U 657, Rouen, France (JB)

Search for other works by this author on:

,

Affiliations of authors: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA (JC); Information Management Services, Rockville, MD (DP, RA); Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (BG, CS, MHG); Cancer Genetics and Epidemiology Program, Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC (CB); Medical School, Rouen University Hospital, Inserm U 657, Rouen, France (JB)

Search for other works by this author on:

,

Affiliations of authors: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA (JC); Information Management Services, Rockville, MD (DP, RA); Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (BG, CS, MHG); Cancer Genetics and Epidemiology Program, Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC (CB); Medical School, Rouen University Hospital, Inserm U 657, Rouen, France (JB)

Search for other works by this author on:

,

Affiliations of authors: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA (JC); Information Management Services, Rockville, MD (DP, RA); Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (BG, CS, MHG); Cancer Genetics and Epidemiology Program, Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC (CB); Medical School, Rouen University Hospital, Inserm U 657, Rouen, France (JB)

Search for other works by this author on:

,

Affiliations of authors: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA (JC); Information Management Services, Rockville, MD (DP, RA); Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (BG, CS, MHG); Cancer Genetics and Epidemiology Program, Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC (CB); Medical School, Rouen University Hospital, Inserm U 657, Rouen, France (JB)

Search for other works by this author on:

Affiliations of authors: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA (JC); Information Management Services, Rockville, MD (DP, RA); Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (BG, CS, MHG); Cancer Genetics and Epidemiology Program, Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC (CB); Medical School, Rouen University Hospital, Inserm U 657, Rouen, France (JB)

Search for other works by this author on:

Revision received:

05 June 2006

Published:

06 September 2006

• • Article contents
  • Figures & tables
  • Video
  • Audio
  • Supplementary Data
• Cite

Cite

Jinbo Chen, David Pee, Rajeev Ayyagari, Barry Graubard, Catherine Schairer, Celia Byrne, Jacques Benichou, Mitchell H. Gail, Projecting Absolute Invasive Breast Cancer Risk in White Women With a Model That Includes Mammographic Density, JNCI: Journal of the National Cancer Institute, Volume 98, Issue 17, 6 September 2006, Pages 1215–1226, https://doi.org/10.1093/jnci/djj332
Close

Navbar Search Filter Mobile Enter search term Search

Abstract

Background: To improve the discriminatory power of the Gail model for predicting absolute risk of invasive breast cancer, we previously developed a relative risk model that incorporated mammographic density (DENSITY) from data on white women in the Breast Cancer Detection Demonstration Project (BCDDP). That model also included the variables age at birth of first live child (AGEFLB), number of affected mother or sisters (NUMREL), number of previous benign breast biopsy examinations (NBIOPS), and weight (WEIGHT). In this study, we developed the corresponding model for absolute risk. Methods: We combined the relative risk model with data on the distribution of the variables AGEFLB, NUMREL, NBIOPS, and WEIGHT from the 2000 National Health Interview Survey, with data on the conditional distribution of DENSITY given other risk factors in BCDDP, with breast cancer incidence rates from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute, and with national mortality rates. Confidence intervals (CIs) accounted for variability of estimates of relative risks and of risk factor distributions. We compared the absolute 5-year risk projections from the new model with those from the Gail model on 1744 white women. Results: Attributable risks of breast cancer associated with DENSITY, AGEFLB, NUMREL, NBIOPS, and WEIGHT were 0.779 (95% CI = 0.733 to 0.819) and 0.747 (95% CI = 0.702 to 0.788) for women younger than 50 years and 50 years or older, respectively. The model predicted higher risks than the Gail model for women with a high percentage of dense breast area. However, the average risk projections from the new model in various age groups were similar to those from the Gail model, suggesting that the new model is well calibrated. Conclusions: This new model for absolute invasive breast cancer risk in white women promises modest improvements in discriminatory power compared with the Gail model but needs to be validated with independent data.

© The Author 2006. Published by Oxford University Press.

Topic:

• epidemiology
• child
• mothers
• breast
• mortality
• breast cancer
• breast biopsy
• surveillance, medical
• breast cancer risk assessment tool
• invasive breast cancer
• national cancer institute
• national health interview survey
• risk, attributable
• health service demonstration project

You do not currently have access to this article.

Personal account

• Sign in with email/username & password
• Get email alerts
• Save searches
• Purchase content
• Activate your purchase/trial code
• Add your ORCID iD

Get help with access

Institutional access

Access to content on Oxford Academic is often provided through institutional subscriptions and purchases. If you are a member of an institution with an active account, you may be able to access content in one of the following ways:

IP based access

Typically, access is provided across an institutional network to a range of IP addresses. This authentication occurs automatically, and it is not possible to sign out of an IP authenticated account.

Sign in through your institution

Choose this option to get remote access when outside your institution. Shibboleth/Open Athens technology is used to provide single sign-on between your institution’s website and Oxford Academic.

1. Click Sign in through your institution.
2. Select your institution from the list provided, which will take you to your institution's website to sign in.
3. When on the institution site, please use the credentials provided by your institution. Do not use an Oxford Academic personal account.
4. Following successful sign in, you will be returned to Oxford Academic.

If your institution is not listed or you cannot sign in to your institution’s website, please contact your librarian or administrator.

Sign in with a library card

Enter your library card number to sign in. If you cannot sign in, please contact your librarian.

Society Members

Society member access to a journal is achieved in one of the following ways:

Sign in through society site

Many societies offer single sign-on between the society website and Oxford Academic. If you see ‘Sign in through society site’ in the sign in pane within a journal:

1. Click Sign in through society site.
2. When on the society site, please use the credentials provided by that society. Do not use an Oxford Academic personal account.
3. Following successful sign in, you will be returned to Oxford Academic.

If you do not have a society account or have forgotten your username or password, please contact your society.

Sign in using a personal account

Some societies use Oxford Academic personal accounts to provide access to their members. See below.

Personal account

A personal account can be used to get email alerts, save searches, purchase content, and activate subscriptions.

Some societies use Oxford Academic personal accounts to provide access to their members.

Viewing your signed in accounts

Click the account icon in the top right to:

• View your signed in personal account and access account management features.
• View the institutional accounts that are providing access.

Signed in but can't access content

Oxford Academic is home to a wide variety of products. The institutional subscription may not cover the content that you are trying to access. If you believe you should have access to that content, please contact your librarian.

Institutional account management

For librarians and administrators, your personal account also provides access to institutional account management. Here you will find options to view and activate subscriptions, manage institutional settings and access options, access usage statistics, and more.

Purchase

Short-term Access

To purchase short-term access, please sign in to your personal account above.

Don't already have a personal account? Register

Projecting Absolute Invasive Breast Cancer Risk in White Women With a Model That Includes Mammographic Density - 24 Hours access

EUR €38.00

GBP £33.00

USD $41.00

Rental

This article is also available for rental through DeepDyve.

Citations

Views

Altmetric

Metrics

Total Views 3,011

2,193 Pageviews

818 PDF Downloads

Since 11/1/2016

Citations

271 Web of Science

×

Email alerts

Citing articles via

• Latest

• Most Read

• Most Cited

More from Oxford Academic