Literature DB >> 3255294

Mammographic parenchymal features and breast cancer in the breast cancer detection demonstration project.

J Brisson1, A S Morrison, N Khalid.   

Abstract

The Breast Cancer Detection Demonstration Project (BCDDP) screened 283,222 U.S. women for breast cancer by use of mammography and breast palpation. A sample of participants was followed up to determine the subsequent occurrence of breast cancer cases and deaths. We have used information from the BCDDP to evaluate the relation of mammographic parenchymal features to the incidence of and mortality from breast cancer, and to examine changes in this relation with duration of follow-up. We also reevaluated the relations of age, body weight, height, menopause, parity, and age at birth of first child to mammographic features of breast tissue. Among women 35-49 years of age at entry, those whose mammographic features were "glandular" or "homogeneously dense" had a 2.8-fold increase in risk of breast cancer compared to women whose mammographic features were "atrophic or fatty". The increased risk was observed up to 9 years after entry. Among women 50-74 years of age at entry, the risk of breast cancer was elevated by a factor of 1.7 for women with glandular or dense breast parenchyma compared to those with atrophic or fatty breasts. The increase in risk, however, diminished with increasing follow-up. The percentage of women with glandular or dense parenchymal features decreased as age, body weight, and parity increased. The percentage with glandular or dense features increased as height increased, and the percentage decreased with menopause. Mammographic parenchymal features were not associated with age at birth of first child.

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Year:  1988        PMID: 3255294     DOI: 10.1093/jnci/80.19.1534

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  15 in total

1.  Dietary fat and breast cancer risk: the feasibility of a clinical trial of breast cancer prevention.

Authors:  N F Boyd; M Cousins; G Lockwood; D Tritchler
Journal:  Lipids       Date:  1992-10       Impact factor: 1.880

2.  Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience.

Authors:  Yuji Ikedo; Takako Morita; Daisuke Fukuoka; Takeshi Hara; Gobert Lee; Hiroshi Fujita; Etsuo Takada; Tokiko Endo
Journal:  Int J Comput Assist Radiol Surg       Date:  2009-03-14       Impact factor: 2.924

3.  A breast density index for digital mammograms based on radiologists' ranking.

Authors:  J M Boone; K K Lindfors; C S Beatty; J A Seibert
Journal:  J Digit Imaging       Date:  1998-08       Impact factor: 4.056

4.  Mammographic breast density and risk of breast cancer: masking bias or causality?

Authors:  C H van Gils; J D Otten; A L Verbeek; J H Hendriks
Journal:  Eur J Epidemiol       Date:  1998-06       Impact factor: 8.082

Review 5.  A review of the influence of mammographic density on breast cancer clinical and pathological phenotype.

Authors:  Michael S Shawky; Cecilia W Huo; Kara Britt; Erik W Thompson; Michael A Henderson; Andrew Redfern
Journal:  Breast Cancer Res Treat       Date:  2019-06-08       Impact factor: 4.872

6.  Mammographic breast density and breast cancer risk by menopausal status, postmenopausal hormone use and a family history of breast cancer.

Authors:  Lusine Yaghjyan; Graham A Colditz; Bernard Rosner; Rulla M Tamimi
Journal:  Cancer Causes Control       Date:  2012-03-23       Impact factor: 2.506

Review 7.  Clinical management of women at increased risk for breast cancer.

Authors:  V G Vogel; A Yeomans; E Higginbotham
Journal:  Breast Cancer Res Treat       Date:  1993-11       Impact factor: 4.872

8.  Cellular proliferative activity of mammographic normal dense and fatty tissue determined by DNA S phase percentage.

Authors:  P C Stomper; R B Penetrante; S B Edge; M A Arredondo; L E Blumenson; C C Stewart
Journal:  Breast Cancer Res Treat       Date:  1996       Impact factor: 4.872

Review 9.  Breast cancer screening. A brief historical review.

Authors:  J N Wolfe
Journal:  Breast Cancer Res Treat       Date:  1991-05       Impact factor: 4.872

10.  Predictors of mammographic density: insights gained from a novel regression analysis of a twin study.

Authors:  Gillian S Dite; Lyle C Gurrin; Graham B Byrnes; Jennifer Stone; Anoma Gunasekara; Margaret R E McCredie; Dallas R English; Graham G Giles; Jennifer Cawson; Robert A Hegele; Anna M Chiarelli; Martin J Yaffe; Norman F Boyd; John L Hopper
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-12       Impact factor: 4.254

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