Literature DB >> 22143145

Clinical and epidemiological issues in mammographic density.

Valentina Assi1, Jane Warwick, Jack Cuzick, Stephen W Duffy.   

Abstract

High mammographic density is associated with an increased risk of breast cancer, and of all known breast cancer risk factors has the greatest attributable fraction. Mammographic density is estimated to account for 16% of all breast cancers, but can be altered by endogenous and exogenous hormonal factors, and generally declines with age. Confounding factors such as age, parity, menopausal status and BMI make the interpretation of mammographic density particularly challenging. Furthermore, none of the established means of measuring mammographic density are entirely satisfactory because they are time consuming or subjective. It is hoped that by adding information regarding mammographic density to existing models of breast cancer risk assessment, the accuracy of individual risk assessments can be improved. Although mammographic density has clearly been shown to be a powerful factor for predicting the risk of developing breast cancer, its potential role in assessing hormonal preventive regimens and helping to tailor screening algorithms cannot be fully realized until we have more-precise, simple and reproducible density measures.

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Year:  2011        PMID: 22143145     DOI: 10.1038/nrclinonc.2011.173

Source DB:  PubMed          Journal:  Nat Rev Clin Oncol        ISSN: 1759-4774            Impact factor:   66.675


  104 in total

1.  Prospective breast cancer risk prediction model for women undergoing screening mammography.

Authors:  William E Barlow; Emily White; Rachel Ballard-Barbash; Pamela M Vacek; Linda Titus-Ernstoff; Patricia A Carney; Jeffrey A Tice; Diana S M Buist; Berta M Geller; Robert Rosenberg; Bonnie C Yankaskas; Karla Kerlikowske
Journal:  J Natl Cancer Inst       Date:  2006-09-06       Impact factor: 13.506

2.  Validation studies for models projecting the risk of invasive and total breast cancer incidence.

Authors:  J P Costantino; M H Gail; D Pee; S Anderson; C K Redmond; J Benichou; H S Wieand
Journal:  J Natl Cancer Inst       Date:  1999-09-15       Impact factor: 13.506

3.  Case-control study of increased mammographic breast density response to hormone replacement therapy.

Authors:  Celine M Vachon; Thomas A Sellers; Robert A Vierkant; Fang-Fang Wu; Kathleen R Brandt
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2002-11       Impact factor: 4.254

4.  High-risk mammographic parenchymal patterns, hormone replacement therapy and other risk factors: a case-control study.

Authors:  E Sala; R Warren; J McCann; S Duffy; R Luben; N Day
Journal:  Int J Epidemiol       Date:  2000-08       Impact factor: 7.196

5.  Mammographic density, estrogen receptor status and other breast cancer tumor characteristics.

Authors:  Jane Ding; Ruth Warren; Anne Girling; Deborah Thompson; Douglas Easton
Journal:  Breast J       Date:  2010-02-23       Impact factor: 2.431

6.  An automated approach for estimation of breast density.

Authors:  John J Heine; Michael J Carston; Christopher G Scott; Kathleen R Brandt; Fang-Fang Wu; Vernon Shane Pankratz; Thomas A Sellers; Celine M Vachon
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-11       Impact factor: 4.254

7.  A randomized, placebo-controlled trial (NCIC CTG MAP1) examining the effects of letrozole on mammographic breast density and other end organs in postmenopausal women.

Authors:  T Cigler; D Tu; M J Yaffe; B Findlay; S Verma; D Johnston; H Richardson; H Hu; S Qi; P E Goss
Journal:  Breast Cancer Res Treat       Date:  2009-12-06       Impact factor: 4.872

8.  Reproducibility of visual assessment on mammographic density.

Authors:  Jinnan Gao; Ruth Warren; Helen Warren-Forward; John F Forbes
Journal:  Breast Cancer Res Treat       Date:  2007-07-07       Impact factor: 4.872

9.  Visually assessed breast density, breast cancer risk and the importance of the craniocaudal view.

Authors:  Stephen W Duffy; Iris D Nagtegaal; Susan M Astley; Maureen G C Gillan; Magnus A McGee; Caroline R M Boggis; Mary Wilson; Ursula M Beetles; Miriam A Griffiths; Anil K Jain; Jill Johnson; Rita Roberts; Heather Deans; Karen A Duncan; Geeta Iyengar; Pam M Griffiths; Jane Warwick; Jack Cuzick; Fiona J Gilbert
Journal:  Breast Cancer Res       Date:  2008-07-23       Impact factor: 6.466

Review 10.  Mammographic density. Measurement of mammographic density.

Authors:  Martin J Yaffe
Journal:  Breast Cancer Res       Date:  2008-06-19       Impact factor: 6.466

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  41 in total

1.  Risk analysis: A dense issue.

Authors:  Duncan Graham-Rowe
Journal:  Nature       Date:  2012-05-30       Impact factor: 49.962

2.  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

3.  Does accelerated hypofractionated adjuvant whole-breast radiotherapy increase mammographic density or change mammographic features?

Authors:  Silvia Bagnera; Luisella Milanesio; Piero B Brachet Cota; Carla Berrino; Aldo Cataldi; Giovanni Gatti; Guido Mondini; Ovidio Paino; Erika G Comello; Renzo Orlassino; Massimo Pasquino; Domenico Cante; Maria R La Porta; Sebastiano Patania; Giovanni La Valle
Journal:  Br J Radiol       Date:  2015-09-22       Impact factor: 3.039

4.  Distribution of mammographic density and its influential factors among Chinese women.

Authors:  Hongji Dai; Ye Yan; Peishan Wang; Peifang Liu; Yali Cao; Li Xiong; Yahong Luo; Tie Pan; Xiangjun Ma; Jie Wang; Zhenhua Yang; Xueou Liu; Chuan Chen; Yubei Huang; Yi Li; Yaogang Wang; Xishan Hao; Zhaoxiang Ye; Kexin Chen
Journal:  Int J Epidemiol       Date:  2014-03-16       Impact factor: 7.196

Review 5.  Mammographic density is not a worthwhile examination to distinguish high cancer risk women in screening.

Authors:  Catherine Colin; Anne-Marie Schott; Pierre-Jean Valette
Journal:  Eur Radiol       Date:  2014-06-28       Impact factor: 5.315

6.  Correlation of breast tissue histology and optical signatures to improve margin assessment techniques.

Authors:  Stephanie Kennedy; Matthew Caldwell; Torre Bydlon; Christine Mulvey; Jenna Mueller; Lee Wilke; William Barry; Nimmi Ramanujam; Joseph Geradts
Journal:  J Biomed Opt       Date:  2016-06-01       Impact factor: 3.170

7.  The role of cone-beam breast-CT for breast cancer detection relative to breast density.

Authors:  Susanne Wienbeck; Johannes Uhlig; Susanne Luftner-Nagel; Antonia Zapf; Alexey Surov; Eva von Fintel; Vera Stahnke; Joachim Lotz; Uwe Fischer
Journal:  Eur Radiol       Date:  2017-07-04       Impact factor: 5.315

8.  A novel functional infrared imaging system coupled with multiparametric computerised analysis for risk assessment of breast cancer.

Authors:  Tamar Sella; Miri Sklair-Levy; Maya Cohen; Mona Rozin; Myra Shapiro-Feinberg; Tanir M Allweis; Eugene Libson; David Izhaky
Journal:  Eur Radiol       Date:  2012-12-06       Impact factor: 5.315

Review 9.  Future directions in cancer prevention.

Authors:  Asad Umar; Barbara K Dunn; Peter Greenwald
Journal:  Nat Rev Cancer       Date:  2012-11-15       Impact factor: 60.716

10.  Breast cancer diagnosis from screening in trinidad and tobago: opportunities for cancer prevention.

Authors:  Marlon D Joseph; Lorna Thorpe; Carey Annandsingh; George Laquis; Joycelyn Lee Young; Jamie Kwasniewski; Roy Lee; Emanuela Taioli
Journal:  J Immigr Minor Health       Date:  2014-06
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