Literature DB >> 17009106

Ethnic and geographic differences in mammographic density and their association with breast cancer incidence.

Gertraud Maskarinec1, Ian Pagano, Zhao Chen, Chisato Nagata, Inger Torhild Gram.   

Abstract

The objective of this pooled analysis was to compare differences in dense areas and percent mammographic densities to breast cancer incidence in populations at different breast cancer risk. The data set included 1,327 women aged 40-80: Caucasians from Norway, Arizona, and Hawaii, Japanese from Hawaii and Japan, Latina from Arizona, and Native Hawaiians from Hawaii. One reader performed computer-assisted quantitative density assessment for all mammographic films. Multiple linear regression models evaluated the influence of the covariates on breast density. Spearman correlation coefficients (r (s)) estimated the association between breast density and breast cancer incidence for the seven populations. After adjustment for covariates, ethnicity, but not location, was significantly associated with breast density. In the full model, 19% of the variation in the dense areas and 46% in the variation of percent densities were explained by measured risk factors. Native Hawaiians had the largest dense areas and women in Japan the smallest, whereas percent densities were highest among Native Hawaiians and Japanese in Hawaii and lowest among Norwegian women. The mean age-adjusted dense area had the strongest association with breast cancer incidence (r (s) = 0.93, P = 0.003); the relation with percent density was considerably weaker (r (s) = 0.32, P = 0.48). The correlation between age-adjusted dense area and breast cancer incidence remained strong after selectively removing individual data points. This comparison of mammographic densities suggests that, on a group level, age-adjusted dense areas may reflect breast cancer incidence better than percent densities.

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Year:  2006        PMID: 17009106     DOI: 10.1007/s10549-006-9387-5

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  43 in total

1.  International Consortium on Mammographic Density: Methodology and population diversity captured across 22 countries.

Authors:  Valerie A McCormack; Anya Burton; Isabel dos-Santos-Silva; John H Hipwell; Caroline Dickens; Dorria Salem; Rasha Kamal; Mikael Hartman; Charmaine Pei Ling Lee; Kee-Seng Chia; Vahit Ozmen; Mustafa Erkin Aribal; Anath Arzee Flugelman; Martín Lajous; Ruy Lopez-Riduara; Megan Rice; Isabelle Romieu; Giske Ursin; Samera Qureshi; Huiyan Ma; Eunjung Lee; Carla H van Gils; Johanna O P Wanders; Sudhir Vinayak; Rose Ndumia; Steve Allen; Sarah Vinnicombe; Sue Moss; Jong Won Lee; Jisun Kim; Ana Pereira; Maria Luisa Garmendia; Reza Sirous; Mehri Sirous; Beata Peplonska; Agnieszka Bukowska; Rulla M Tamimi; Kimberly Bertrand; Chisato Nagata; Ava Kwong; Celine Vachon; Christopher Scott; Beatriz Perez-Gomez; Marina Pollan; Gertraud Maskarinec; Graham Giles; John Hopper; Jennifer Stone; Nadia Rajaram; Soo-Hwang Teo; Shivaani Mariapun; Martin J Yaffe; Joachim Schüz; Anna M Chiarelli; Linda Linton; Norman F Boyd
Journal:  Cancer Epidemiol       Date:  2015-12-24       Impact factor: 2.984

2.  Does patient age affect the PPV3 of ACR BI-RADS Ultrasound categories 4 and 5 in the diagnostic setting?

Authors:  Yue Hu; Yaping Yang; Ran Gu; Liang Jin; Shiyu Shen; Fengtao Liu; Hongli Wang; Jingsi Mei; Xiaofang Jiang; Qiang Liu; Fengxi Su
Journal:  Eur Radiol       Date:  2018-01-04       Impact factor: 5.315

3.  The relationship between terminal duct lobular unit features and mammographic density among Chinese breast cancer patients.

Authors:  Hyuna Sung; Changyuan Guo; Erni Li; Jing Li; Ruth M Pfeiffer; Jennifer L Guida; Renata Cora; Nan Hu; Joseph Deng; Jonine D Figueroa; Mark E Sherman; Gretchen L Gierach; Ning Lu; Xiaohong R Yang
Journal:  Int J Cancer       Date:  2019-01-07       Impact factor: 7.396

4.  Equol-producing status, isoflavone intake, and breast density in a sample of U.S. Chinese women.

Authors:  Marilyn Tseng; Celia Byrne; Mindy S Kurzer; Carolyn Y Fang
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-09-09       Impact factor: 4.254

5.  Volume of mammographic density and risk of breast cancer.

Authors:  John A Shepherd; Karla Kerlikowske; Lin Ma; Frederick Duewer; Bo Fan; Jeff Wang; Serghei Malkov; Eric Vittinghoff; Steven R Cummings
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-05-24       Impact factor: 4.254

6.  Portable impulse-radar detector for breast cancer: a pilot study.

Authors:  Shinsuke Sasada; Norio Masumoto; Hang Song; Keiko Kajitani; Akiko Emi; Takayuki Kadoya; Koji Arihiro; Takamaro Kikkawa; Morihito Okada
Journal:  J Med Imaging (Bellingham)       Date:  2018-06-13

7.  Alcohol intake over the life course and mammographic density.

Authors:  Julie D Flom; Jennifer S Ferris; Parisa Tehranifar; Mary Beth Terry
Journal:  Breast Cancer Res Treat       Date:  2009-01-29       Impact factor: 4.872

8.  High-background parenchymal enhancement in the contralateral breast is an imaging biomarker for favorable prognosis in patients with triple-negative breast cancer treated with chemotherapy.

Authors:  Chuanhui Xu; Jinhui Yu; Feifei Wu; Xuemei Li; Dongmin Hu; Guiming Chen; Gang Wu
Journal:  Am J Transl Res       Date:  2021-05-15       Impact factor: 4.060

9.  Increases in serum estrone sulfate level are associated with increased mammographic density during menopausal hormone therapy.

Authors:  Carolyn J Crandall; Min Guan; Gail A Laughlin; Giske A Ursin; Frank Z Stanczyk; Sue A Ingles; Elizabeth Barrett-Connor; Gail A Greendale
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-07       Impact factor: 4.254

10.  Mammographic density and epithelial histopathologic markers.

Authors:  Martijn Verheus; Gertraud Maskarinec; Eva Erber; Jana S Steude; Jeffrey Killeen; Brenda Y Hernandez; J Mark Cline
Journal:  BMC Cancer       Date:  2009-06-13       Impact factor: 4.430

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