Literature DB >> 27130893

Racial Differences in Quantitative Measures of Area and Volumetric Breast Density.

Anne Marie McCarthy1, Brad M Keller1, Lauren M Pantalone1, Meng-Kang Hsieh1, Marie Synnestvedt1, Emily F Conant1, Katrina Armstrong1, Despina Kontos1.   

Abstract

BACKGROUND: Increased breast density is a strong risk factor for breast cancer and also decreases the sensitivity of mammographic screening. The purpose of our study was to compare breast density for black and white women using quantitative measures.
METHODS: Breast density was assessed among 5282 black and 4216 white women screened using digital mammography. Breast Imaging-Reporting and Data System (BI-RADS) density was obtained from radiologists' reports. Quantitative measures for dense area, area percent density (PD), dense volume, and volume percent density were estimated using validated, automated software. Breast density was categorized as dense or nondense based on BI-RADS categories or based on values above and below the median for quantitative measures. Logistic regression was used to estimate the odds of having dense breasts by race, adjusted for age, body mass index (BMI), age at menarche, menopause status, family history of breast or ovarian cancer, parity and age at first birth, and current hormone replacement therapy (HRT) use. All statistical tests were two-sided.
RESULTS: There was a statistically significant interaction of race and BMI on breast density. After accounting for age, BMI, and breast cancer risk factors, black women had statistically significantly greater odds of high breast density across all quantitative measures (eg, PD nonobese odds ratio [OR] = 1.18, 95% confidence interval [CI] = 1.02 to 1.37, P = .03, PD obese OR = 1.26, 95% CI = 1.04 to 1.53, P = .02). There was no statistically significant difference in BI-RADS density by race.
CONCLUSIONS: After accounting for age, BMI, and other risk factors, black women had higher breast density than white women across all quantitative measures previously associated with breast cancer risk. These results may have implications for risk assessment and screening.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Mesh:

Year:  2016        PMID: 27130893      PMCID: PMC5939658          DOI: 10.1093/jnci/djw104

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


  69 in total

1.  Risk factors and tumor characteristics of interval cancers by mammographic density.

Authors:  Johanna Holm; Keith Humphreys; Jingmei Li; Alexander Ploner; Abbas Cheddad; Mikael Eriksson; Sven Törnberg; Per Hall; Kamila Czene
Journal:  J Clin Oncol       Date:  2015-02-02       Impact factor: 44.544

2.  The association of breast density with breast cancer mortality in African American and white women screened in community practice.

Authors:  Shengfan Zhang; Julie S Ivy; Kathleen M Diehl; Bonnie C Yankaskas
Journal:  Breast Cancer Res Treat       Date:  2012-11-10       Impact factor: 4.872

3.  Misclassification of Breast Imaging Reporting and Data System (BI-RADS) Mammographic Density and Implications for Breast Density Reporting Legislation.

Authors:  Charlotte C Gard; Erin J Aiello Bowles; Diana L Miglioretti; Stephen H Taplin; Carolyn M Rutter
Journal:  Breast J       Date:  2015-07-01       Impact factor: 2.431

4.  Diagnostic performance of digital versus film mammography for breast-cancer screening.

Authors:  Etta D Pisano; Constantine Gatsonis; Edward Hendrick; Martin Yaffe; Janet K Baum; Suddhasatta Acharyya; Emily F Conant; Laurie L Fajardo; Lawrence Bassett; Carl D'Orsi; Roberta Jong; Murray Rebner
Journal:  N Engl J Med       Date:  2005-09-16       Impact factor: 91.245

5.  Age-specific trends in mammographic density: the Minnesota Breast Cancer Family Study.

Authors:  Linda E Kelemen; V Shane Pankratz; Thomas A Sellers; Kathy R Brandt; Alice Wang; Carol Janney; Zachary S Fredericksen; James R Cerhan; Celine M Vachon
Journal:  Am J Epidemiol       Date:  2008-04-02       Impact factor: 4.897

6.  Evaluating the effectiveness of using standard mammogram form to predict breast cancer risk: case-control study.

Authors:  Jane Ding; Ruth Warren; Iqbal Warsi; Nick Day; Deborah Thompson; Michael Brady; Christopher Tromans; Ralph Highnam; Douglas Easton
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-05       Impact factor: 4.254

7.  Mammographic density and breast cancer risk: evaluation of a novel method of measuring breast tissue volumes.

Authors:  Norman Boyd; Lisa Martin; Anoma Gunasekara; Olga Melnichouk; Gord Maudsley; Chris Peressotti; Martin Yaffe; Salomon Minkin
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2009-06       Impact factor: 4.254

8.  Breast cancer risk factors in relation to breast density (United States).

Authors:  Linda Titus-Ernstoff; Anna N A Tosteson; Claudia Kasales; Julia Weiss; Martha Goodrich; Elizabeth E Hatch; Patricia A Carney
Journal:  Cancer Causes Control       Date:  2006-12       Impact factor: 2.506

9.  Digital mammographic density and breast cancer risk: a case-control study of six alternative density assessment methods.

Authors:  Amanda Eng; Zoe Gallant; John Shepherd; Valerie McCormack; Jingmei Li; Mitch Dowsett; Sarah Vinnicombe; Steve Allen; Isabel dos-Santos-Silva
Journal:  Breast Cancer Res       Date:  2014-09-20       Impact factor: 6.466

10.  Volumetric breast density estimation from full-field digital mammograms: a validation study.

Authors:  Albert Gubern-Mérida; Michiel Kallenberg; Bram Platel; Ritse M Mann; Robert Martí; Nico Karssemeijer
Journal:  PLoS One       Date:  2014-01-21       Impact factor: 3.240

View more
  24 in total

1.  Acceptability of an Interactive Computer-Animated Agent to Promote Patient-Provider Communication About Breast Density: a Mixed Method Pilot Study.

Authors:  Christine Gunn; Ariel Maschke; Timothy Bickmore; Mark Kennedy; Margaret F Hopkins; Michael D C Fishman; Michael K Paasche-Orlow; Erica T Warner
Journal:  J Gen Intern Med       Date:  2020-01-09       Impact factor: 5.128

2.  Agreement between Breast Percentage Density Estimations from Standard-Dose versus Synthetic Digital Mammograms: Results from a Large Screening Cohort Using Automated Measures.

Authors:  Emily F Conant; Brad M Keller; Lauren Pantalone; Aimilia Gastounioti; Elizabeth S McDonald; Despina Kontos
Journal:  Radiology       Date:  2017-01-25       Impact factor: 11.105

3.  Vitamin A: A Potential Intervention for Breast Cancer Racial Disparities.

Authors:  Michelle D Holmes; Cheng Peng
Journal:  J Nutr       Date:  2021-12-03       Impact factor: 4.798

4.  Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction.

Authors:  Aimilia Gastounioti; Christine Damases Kasi; Christopher G Scott; Kathleen R Brandt; Matthew R Jensen; Carrie B Hruska; Fang F Wu; Aaron D Norman; Emily F Conant; Stacey J Winham; Karla Kerlikowske; Despina Kontos; Celine M Vachon
Journal:  Radiology       Date:  2020-05-12       Impact factor: 11.105

5.  Automated and Clinical Breast Imaging Reporting and Data System Density Measures Predict Risk for Screen-Detected and Interval Cancers: A Case-Control Study.

Authors:  Karla Kerlikowske; Christopher G Scott; Amir P Mahmoudzadeh; Lin Ma; Stacey Winham; Matthew R Jensen; Fang Fang Wu; Serghei Malkov; V Shane Pankratz; Steven R Cummings; John A Shepherd; Kathleen R Brandt; Diana L Miglioretti; Celine M Vachon
Journal:  Ann Intern Med       Date:  2018-05-01       Impact factor: 25.391

6.  Characteristics Associated with Participation in ENGAGED 2 - A Web-based Breast Cancer Risk Communication and Decision Support Trial.

Authors:  Karen J Wernli; Erin A Bowles; Sarah Knerr; Kathleen A Leppig; Kelly Ehrlich; Hongyuan Gao; Marc D Schwartz; Suzanne C O'Neill
Journal:  Perm J       Date:  2020-12

7.  Breast Cancer Population Attributable Risk Proportions Associated with Body Mass Index and Breast Density by Race/Ethnicity and Menopausal Status.

Authors:  Michael C S Bissell; Karla Kerlikowske; Brian L Sprague; Jeffery A Tice; Charlotte C Gard; Katherine Y Tossas; Garth H Rauscher; Amy Trentham-Dietz; Louise M Henderson; Tracy Onega; Theresa H M Keegan; Diana L Miglioretti
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-07-29       Impact factor: 4.254

8.  Understanding the response of mammography facilities to breast density notification.

Authors:  Louise M Henderson; Mary W Marsh; Kathryn Earnhardt; Michael Pritchard; Thad S Benefield; Robert P Agans; Sheila S Lee
Journal:  Cancer       Date:  2020-09-14       Impact factor: 6.860

9.  Risk factors for breast cancer subtypes among Black women undergoing screening mammography.

Authors:  Tara M Friebel-Klingner; Sarah Ehsan; Emily F Conant; Despina Kontos; Susan M Domchek; Anne Marie McCarthy
Journal:  Breast Cancer Res Treat       Date:  2021-08-03       Impact factor: 4.872

10.  Breast Density Awareness and Knowledge in a Mammography Screening Cohort of Predominantly Hispanic Women: Does Breast Density Notification Matter?

Authors:  Jessica D Austin; Mariangela Agovino; Carmen B Rodriguez; Mary Beth Terry; Rachel C Shelton; Ying Wei; Elise Desperito; Karen M Schmitt; Rita Kukafka; Parisa Tehranifar
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2021-08-04       Impact factor: 4.254

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.