Literature DB >> 21610220

Volume of mammographic density and risk of breast cancer.

John A Shepherd1, Karla Kerlikowske, Lin Ma, Frederick Duewer, Bo Fan, Jeff Wang, Serghei Malkov, Eric Vittinghoff, Steven R Cummings.   

Abstract

BACKGROUND: Assessing the volume of mammographic density might more accurately reflect the amount of breast volume at risk of malignant transformation and provide a stronger indication of risk of breast cancer than methods based on qualitative scores or dense breast area.
METHODS: We prospectively collected mammograms for women undergoing screening mammography. We determined the diagnosis of subsequent invasive or ductal carcinoma in situ for 275 cases, selected 825 controls matched for age, ethnicity, and mammography system, and assessed three measures of breast density: percent dense area, fibroglandular volume, and percent fibroglandular volume.
RESULTS: After adjustment for familial breast cancer history, body mass index, history of breast biopsy, and age at first live birth, the ORs for breast cancer risk in the highest versus lowest measurement quintiles were 2.5 (95% CI: 1.5-4.3) for percent dense area, 2.9 (95% CI: 1.7-4.9) for fibroglandular volume, and 4.1 (95% CI: 2.3-7.2) for percent fibroglandular volume. Net reclassification indexes for density measures plus risk factors versus risk factors alone were 9.6% (P = 0.07) for percent dense area, 21.1% (P = 0.0001) for fibroglandular volume, and 14.8% (P = 0.004) for percent fibroglandular volume. Fibroglandular volume improved the categorical risk classification of 1 in 5 women for both women with and without breast cancer.
CONCLUSION: Volumetric measures of breast density are more accurate predictors of breast cancer risk than risk factors alone and than percent dense area. IMPACT: Risk models including dense fibroglandular volume may more accurately predict breast cancer risk than current risk models. ©2011 AACR

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Year:  2011        PMID: 21610220      PMCID: PMC3132306          DOI: 10.1158/1055-9965.EPI-10-1150

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  29 in total

1.  A volumetric method for estimation of breast density on digitized screen-film mammograms.

Authors:  Olga Pawluczyk; Bindu J Augustine; Martin J Yaffe; Dan Rico; Jiwei Yang; Gordon E Mawdsley; Norman F Boyd
Journal:  Med Phys       Date:  2003-03       Impact factor: 4.071

2.  Accuracy of mammographic breast density analysis: results of formal operator training.

Authors:  Sven Prevrhal; John A Shepherd; Rebecca Smith-Bindman; Steven R Cummings; Karla Kerlikowske
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2002-11       Impact factor: 4.254

3.  Predicting breast cancer risk using mammographic density measurements from both mammogram sides and views.

Authors:  Jennifer Stone; Jane Ding; Ruth M L Warren; Stephen W Duffy
Journal:  Breast Cancer Res Treat       Date:  2010-06-11       Impact factor: 4.872

4.  Changes in fibroglandular volume and water content of breast tissue during the menstrual cycle observed by MR imaging at 1.5 T.

Authors:  S J Graham; P L Stanchev; J O Lloyd-Smith; M J Bronskill; D B Plewes
Journal:  J Magn Reson Imaging       Date:  1995 Nov-Dec       Impact factor: 4.813

Review 5.  Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.

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Journal:  Stat Med       Date:  1996-02-28       Impact factor: 2.373

Review 6.  Clinical options for women at high risk for breast cancer.

Authors:  L C Hartmann; T A Sellers; D J Schaid; S Nayfield; C S Grant; J A Bjoraker; J Woods; F Couch
Journal:  Surg Clin North Am       Date:  1999-10       Impact factor: 2.741

7.  Risk for breast cancer development determined by mammographic parenchymal pattern.

Authors:  J N Wolfe
Journal:  Cancer       Date:  1976-05       Impact factor: 6.860

8.  Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study.

Authors:  N F Boyd; J W Byng; R A Jong; E K Fishell; L E Little; A B Miller; G A Lockwood; D L Tritchler; M J Yaffe
Journal:  J Natl Cancer Inst       Date:  1995-05-03       Impact factor: 13.506

9.  [Mammographic density as indicator of breast cancer risk].

Authors:  Giske Ursin
Journal:  Tidsskr Nor Laegeforen       Date:  2003-12-04

10.  A mammographic image analysis method to detect and measure changes in breast density.

Authors:  Kostas Marias; Christian Behrenbruch; Ralph Highnam; Santilal Parbhoo; Alexander Seifalian; Michael Brady
Journal:  Eur J Radiol       Date:  2004-12       Impact factor: 3.528

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  82 in total

1.  A novel automated mammographic density measure and breast cancer risk.

Authors:  John J Heine; Christopher G Scott; Thomas A Sellers; Kathleen R Brandt; Daniel J Serie; Fang-Fang Wu; Marilyn J Morton; Beth A Schueler; Fergus J Couch; Janet E Olson; V Shane Pankratz; Celine M Vachon
Journal:  J Natl Cancer Inst       Date:  2012-07-03       Impact factor: 13.506

2.  Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging.

Authors:  Said Pertuz; Elizabeth S McDonald; Susan P Weinstein; Emily F Conant; Despina Kontos
Journal:  Radiology       Date:  2015-10-21       Impact factor: 11.105

3.  The effect of change in body mass index on volumetric measures of mammographic density.

Authors:  Vicki Hart; Katherine W Reeves; Susan R Sturgeon; Nicholas G Reich; Lynnette Leidy Sievert; Karla Kerlikowske; Lin Ma; John Shepherd; Jeffrey A Tice; Amir Pasha Mahmoudzadeh; Serghei Malkov; Brian L Sprague
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-08-27       Impact factor: 4.254

4.  Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors: automated measurement development for full field digital mammography.

Authors:  E E Fowler; T A Sellers; B Lu; J J Heine
Journal:  Med Phys       Date:  2013-11       Impact factor: 4.071

5.  Methods for assessing and representing mammographic density: an analysis of 4 case-control studies.

Authors:  Christy G Woolcott; Shannon M Conroy; Chisato Nagata; Giske Ursin; Celine M Vachon; Martin J Yaffe; Ian S Pagano; Celia Byrne; Gertraud Maskarinec
Journal:  Am J Epidemiol       Date:  2013-10-11       Impact factor: 4.897

6.  Effect of Vitamin D Supplementation on Breast Cancer Biomarkers: CALGB 70806 (Alliance) Study Design and Baseline Data.

Authors:  Ogheneruona Apoe; Sin-Ho Jung; Heshan Liu; Drew K Seisler; Jayne Charlamb; Patricia Zekan; Lili X Wang; Gary W Unzeitig; Judy Garber; James Marshall; Marie Wood
Journal:  Am J Hematol Oncol       Date:  2016-07

7.  Changes in breast cancer risk distribution among Vermont women using screening mammography.

Authors:  Kenyon C Bolton; John L Mace; Pamela M Vacek; Sally D Herschorn; Ted A James; Jeffrey A Tice; Karla Kerlikowske; Berta M Geller; Donald L Weaver; Brian L Sprague
Journal:  J Natl Cancer Inst       Date:  2014-06-23       Impact factor: 13.506

8.  Association of multiple genetic variants with breast cancer susceptibility in the Han Chinese population.

Authors:  Xu Li; Wenjing Zou; Ming Liu; Wei Cao; Yonghong Jiang; Gaili An; Yuzheng Wang; Shangke Huang; Xinhan Zhao
Journal:  Oncotarget       Date:  2016-12-20

9.  Dietary Fat Intake During Adolescence and Breast Density Among Young Women.

Authors:  Seungyoun Jung; Olga Goloubeva; Catherine Klifa; Erin S LeBlanc; Linda G Snetselaar; Linda Van Horn; Joanne F Dorgan
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2016-05-19       Impact factor: 4.254

10.  Reported mammographic density: film-screen versus digital acquisition.

Authors:  Jennifer A Harvey; Charlotte C Gard; Diana L Miglioretti; Bonnie C Yankaskas; Karla Kerlikowske; Diana S M Buist; Berta A Geller; Tracy L Onega
Journal:  Radiology       Date:  2012-12-18       Impact factor: 11.105

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