Literature DB >> 35315524

Association of contralateral breast cancer risk with mammographic density defined at higher-than-conventional intensity thresholds.

Gordon P Watt1, Julia A Knight2,3, Tuong L Nguyen4, Anne S Reiner1, Kathleen E Malone5, Esther M John6, Charles F Lynch7, Jennifer D Brooks3, Meghan Woods1, Xiaolin Liang1, Leslie Bernstein8, Malcolm C Pike1, John L Hopper4, Jonine L Bernstein1.   

Abstract

Mammographic dense area (MDA) is an established predictor of future breast cancer risk. Recent studies have found that risk prediction might be improved by redefining MDA in effect at higher-than-conventional intensity thresholds. We assessed whether such higher-intensity MDA measures gave stronger prediction of subsequent contralateral breast cancer (CBC) risk using the Women's Environment, Cancer, and Radiation Epidemiology (WECARE) Study, a population-based CBC case-control study of ≥1 year survivors of unilateral breast cancer diagnosed between 1990 and 2008. Three measures of MDA for the unaffected contralateral breast were made at the conventional intensity threshold ("Cumulus") and at two sequentially higher-intensity thresholds ("Altocumulus" and "Cirrocumulus") using the CUMULUS software and mammograms taken up to 3 years prior to the first breast cancer diagnosis. The measures were fitted separately and together in multivariable-adjusted logistic regression models of CBC (252 CBC cases and 271 unilateral breast cancer controls). The strongest association with CBC was MDA defined using the highest intensity threshold, Cirrocumulus (odds ratio per adjusted SD [OPERA] 1.40, 95% CI 1.13-1.73); and the weakest association was MDA defined at the conventional threshold, Cumulus (1.32, 95% CI 1.05-1.66). In a model fitting the three measures together, the association of CBC with Cirrocumulus was unchanged (1.40, 95% CI 0.97-2.05), and the lower brightness measures did not contribute to the CBC model fit. These results suggest that MDA defined at a high-intensity threshold is a better predictor of CBC risk and has the potential to improve CBC risk stratification beyond conventional MDA measures.
© 2022 UICC.

Entities:  

Keywords:  breast cancer; cancer survivors; mammographic density; risk stratification

Mesh:

Year:  2022        PMID: 35315524      PMCID: PMC9420749          DOI: 10.1002/ijc.34001

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.316


  14 in total

1.  Odds per adjusted standard deviation: comparing strengths of associations for risk factors measured on different scales and across diseases and populations.

Authors:  John L Hopper
Journal:  Am J Epidemiol       Date:  2015-10-31       Impact factor: 4.897

2.  The quantitative analysis of mammographic densities.

Authors:  J W Byng; N F Boyd; E Fishell; R A Jong; M J Yaffe
Journal:  Phys Med Biol       Date:  1994-10       Impact factor: 3.609

3.  Explaining variance in the cumulus mammographic measures that predict breast cancer risk: a twins and sisters study.

Authors:  Tuong L Nguyen; Daniel F Schmidt; Enes Makalic; Gillian S Dite; Jennifer Stone; Carmel Apicella; Minh Bui; Robert J Macinnis; Fabrice Odefrey; Jennifer N Cawson; Susan A Treloar; Melissa C Southey; Graham G Giles; John L Hopper
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-10-15       Impact factor: 4.254

4.  Dose-dependent effect of mammographic breast density on the risk of contralateral breast cancer.

Authors:  Marzana Chowdhury; David Euhus; Maureen O'Donnell; Tracy Onega; Pankaj K Choudhary; Swati Biswas
Journal:  Breast Cancer Res Treat       Date:  2018-03-06       Impact factor: 4.872

5.  Mammographic breast density is associated with the development of contralateral breast cancer.

Authors:  Akshara Raghavendra; Arup K Sinha; Huong T Le-Petross; Naveen Garg; Limin Hsu; Modesto Patangan; Therese Bartholomew Bevers; Yu Shen; Arun Banu; Debu Tripathy; Isabelle Bedrosian; Carlos H Barcenas
Journal:  Cancer       Date:  2017-01-30       Impact factor: 6.860

6.  Breast Cancer Risk and Mammographic Density Assessed with Semiautomated and Fully Automated Methods and BI-RADS.

Authors:  Abra M Jeffers; Weiva Sieh; Jafi A Lipson; Joseph H Rothstein; Valerie McGuire; Alice S Whittemore; Daniel L Rubin
Journal:  Radiology       Date:  2016-09-05       Impact factor: 11.105

7.  Breast Cancer Risk Associations with Digital Mammographic Density by Pixel Brightness Threshold and Mammographic System.

Authors:  Tuong L Nguyen; Yoon-Ho Choi; Ye K Aung; Christopher F Evans; Nhut H Trinh; Shuai Li; Gillian S Dite; Myeong-Seong Kim; Patrick C Brennan; Mark A Jenkins; Joohon Sung; Yun-Mi Song; John L Hopper
Journal:  Radiology       Date:  2017-10-16       Impact factor: 11.105

8.  The association of mammographic density with risk of contralateral breast cancer and change in density with treatment in the WECARE study.

Authors:  Julia A Knight; Kristina M Blackmore; Jing Fan; Kathleen E Malone; Esther M John; Charles F Lynch; Celine M Vachon; Leslie Bernstein; Jennifer D Brooks; Anne S Reiner; Xiaolin Liang; Meghan Woods; Jonine L Bernstein
Journal:  Breast Cancer Res       Date:  2018-03-22       Impact factor: 6.466

9.  Predicting interval and screen-detected breast cancers from mammographic density defined by different brightness thresholds.

Authors:  Tuong L Nguyen; Ye K Aung; Shuai Li; Nhut Ho Trinh; Christopher F Evans; Laura Baglietto; Kavitha Krishnan; Gillian S Dite; Jennifer Stone; Dallas R English; Yun-Mi Song; Joohon Sung; Mark A Jenkins; Melissa C Southey; Graham G Giles; John L Hopper
Journal:  Breast Cancer Res       Date:  2018-12-13       Impact factor: 6.466

10.  Mammographic density defined by higher than conventional brightness threshold better predicts breast cancer risk for full-field digital mammograms.

Authors:  Tuong Linh Nguyen; Ye Kyaw Aung; Christopher Francis Evans; Choi Yoon-Ho; Mark Anthony Jenkins; Joohon Sung; John Llewelyn Hopper; Yun-Mi Song
Journal:  Breast Cancer Res       Date:  2015-11-18       Impact factor: 6.466

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  1 in total

1.  Genetic Aspects of Mammographic Density Measures Associated with Breast Cancer Risk.

Authors:  Shuai Li; Tuong L Nguyen; Tu Nguyen-Dumont; James G Dowty; Gillian S Dite; Zhoufeng Ye; Ho N Trinh; Christopher F Evans; Maxine Tan; Joohon Sung; Mark A Jenkins; Graham G Giles; John L Hopper; Melissa C Southey
Journal:  Cancers (Basel)       Date:  2022-06-02       Impact factor: 6.575

  1 in total

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