Literature DB >> 28152151

Population-Attributable Risk Proportion of Clinical Risk Factors for Breast Cancer.

Natalie J Engmann1, Marzieh K Golmakani2, Diana L Miglioretti2,3, Brian L Sprague4, Karla Kerlikowske1,5.   

Abstract

IMPORTANCE: Many established breast cancer risk factors are used in clinical risk prediction models, although the proportion of breast cancers explained by these factors is unknown.
OBJECTIVE: To determine the population-attributable risk proportion (PARP) for breast cancer associated with clinical breast cancer risk factors among premenopausal and postmenopausal women. DESIGN, SETTING, AND PARTICIPANTS: Case-control study with 1:10 matching on age, year of risk factor assessment, and Breast Cancer Surveillance Consortium (BCSC) registry. Risk factor data were collected prospectively from January 1, 1996, through October 31, 2012, from BCSC community-based breast imaging facilities. A total of 18 437 women with invasive breast cancer or ductal carcinoma in situ were enrolled as cases and matched to 184 309 women without breast cancer, with a total of 58 146 premenopausal and 144 600 postmenopausal women enrolled in the study. EXPOSURES: Breast Imaging Reporting and Data System (BI-RADS) breast density (heterogeneously or extremely dense vs scattered fibroglandular densities), first-degree family history of breast cancer, body mass index (>25 vs 18.5-25), history of benign breast biopsy, and nulliparity or age at first birth (≥30 years vs <30 years). MAIN OUTCOMES AND MEASURES: Population-attributable risk proportion of breast cancer.
RESULTS: Of the 18 437 women with breast cancer, the mean (SD) age was 46.3 (3.7) years among premenopausal women and 61.7 (7.2) years among the postmenopausal women. Overall, 4747 (89.8%) premenopausal and 12 502 (95.1%) postmenopausal women with breast cancer had at least 1 breast cancer risk factor. The combined PARP of all risk factors was 52.7% (95% CI, 49.1%-56.3%) among premenopausal women and 54.7% (95% CI, 46.5%-54.7%) among postmenopausal women. Breast density was the most prevalent risk factor for both premenopausal and postmenopausal women and had the largest effect on the PARP; 39.3% (95% CI, 36.6%-42.0%) of premenopausal and 26.2% (95% CI, 24.4%-28.0%) of postmenopausal breast cancers could potentially be averted if all women with heterogeneously or extremely dense breasts shifted to scattered fibroglandular breast density. Among postmenopausal women, 22.8% (95% CI, 18.3%-27.3%) of breast cancers could potentially be averted if all overweight and obese women attained a body mass index of less than 25. CONCLUSIONS AND RELEVANCE: Most women with breast cancer have at least 1 breast cancer risk factor routinely documented at the time of mammography, and more than half of premenopausal and postmenopausal breast cancers are explained by these factors. These easily assessed risk factors should be incorporated into risk prediction models to stratify breast cancer risk and promote risk-based screening and targeted prevention efforts.

Entities:  

Mesh:

Year:  2017        PMID: 28152151      PMCID: PMC5540816          DOI: 10.1001/jamaoncol.2016.6326

Source DB:  PubMed          Journal:  JAMA Oncol        ISSN: 2374-2437            Impact factor:   31.777


  44 in total

1.  Mammographic patterns as a predictive biomarker of breast cancer risk: effect of tamoxifen.

Authors:  C Atkinson; R Warren; S A Bingham; N E Day
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  1999-10       Impact factor: 4.254

2.  Population attributable fraction estimation for established breast cancer risk factors: considering the issues of high prevalence and unmodifiability.

Authors:  B Rockhill; C R Weinberg; B Newman
Journal:  Am J Epidemiol       Date:  1998-05-01       Impact factor: 4.897

Review 3.  Assessing women at high risk of breast cancer: a review of risk assessment models.

Authors:  Eitan Amir; Orit C Freedman; Bostjan Seruga; D Gareth Evans
Journal:  J Natl Cancer Inst       Date:  2010-04-28       Impact factor: 13.506

4.  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

5.  Benign breast disease, mammographic breast density, and the risk of breast cancer.

Authors:  Jeffrey A Tice; Ellen S O'Meara; Donald L Weaver; Celine Vachon; Rachel Ballard-Barbash; Karla Kerlikowske
Journal:  J Natl Cancer Inst       Date:  2013-06-06       Impact factor: 13.506

6.  Comparison of risk factors for ductal carcinoma in situ and invasive breast cancer.

Authors:  K Kerlikowske; J Barclay; D Grady; E A Sickles; V Ernster
Journal:  J Natl Cancer Inst       Date:  1997-01-01       Impact factor: 13.506

7.  Prevalence of mammographically dense breasts in the United States.

Authors:  Brian L Sprague; Ronald E Gangnon; Veronica Burt; Amy Trentham-Dietz; John M Hampton; Robert D Wellman; Karla Kerlikowske; Diana L Miglioretti
Journal:  J Natl Cancer Inst       Date:  2014-09-12       Impact factor: 13.506

8.  Proportion of invasive breast cancer attributable to risk factors modifiable after menopause.

Authors:  Brian L Sprague; Amy Trentham-Dietz; Kathleen M Egan; Linda Titus-Ernstoff; John M Hampton; Polly A Newcomb
Journal:  Am J Epidemiol       Date:  2008-06-13       Impact factor: 4.897

9.  Density is in the eye of the beholder: visual versus semi-automated assessment of breast density on standard mammograms.

Authors:  M B I Lobbes; J P M Cleutjens; V Lima Passos; C Frotscher; M J Lahaye; K B M I Keymeulen; R G Beets-Tan; J Wildberger; C Boetes
Journal:  Insights Imaging       Date:  2011-11-20

10.  The proportion of postmenopausal breast cancer cases in the Netherlands attributable to lifestyle-related risk factors.

Authors:  W A van Gemert; C I Lanting; R A Goldbohm; P A van den Brandt; H G Grooters; E Kampman; L A L M Kiemeney; F E van Leeuwen; E M Monninkhof; E de Vries; P H Peeters; S G Elias
Journal:  Breast Cancer Res Treat       Date:  2015-06-05       Impact factor: 4.872

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  68 in total

1.  Lifestyle Interventions for Breast Cancer Prevention.

Authors:  Justin C Brown; Jennifer A Ligibel
Journal:  Curr Breast Cancer Rep       Date:  2018-07-03

2.  Capsule Commentary on Schifferdecker et al., Knowledge and Perception of Breast Density, Screening Mammography, and Supplemental Screening: in Search of "Informed".

Authors:  H Douglas Walden
Journal:  J Gen Intern Med       Date:  2020-06       Impact factor: 5.128

3.  Incidence of Ductal Carcinoma In Situ in the United States, 2000-2014.

Authors:  Marc D Ryser; Laura H Hendrix; Mathias Worni; Yiling Liu; Terry Hyslop; E Shelley Hwang
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-06-11       Impact factor: 4.254

4.  Childhood body size and midlife mammographic breast density in foreign-born and U.S.-born women in New York City.

Authors:  Shweta Athilat; Cynthia Joe; Carmen B Rodriguez; Mary Beth Terry; Parisa Tehranifar
Journal:  Ann Epidemiol       Date:  2018-08-18       Impact factor: 3.797

5.  Affibody-Indocyanine Green Based Contrast Agent for Photoacoustic and Fluorescence Molecular Imaging of B7-H3 Expression in Breast Cancer.

Authors:  Rakesh Bam; Makenna Laffey; Katharine Nottberg; Patrick S Lown; Benjamin J Hackel; Katheryne E Wilson
Journal:  Bioconjug Chem       Date:  2019-05-24       Impact factor: 4.774

6.  Computer-aided assessment of breast density: comparison of supervised deep learning and feature-based statistical learning.

Authors:  Songfeng Li; Jun Wei; Heang-Ping Chan; Mark A Helvie; Marilyn A Roubidoux; Yao Lu; Chuan Zhou; Lubomir M Hadjiiski; Ravi K Samala
Journal:  Phys Med Biol       Date:  2018-01-09       Impact factor: 3.609

7.  Alcohol and Tobacco Use in Relation to Mammographic Density in 23,456 Women.

Authors:  Laurel A Habel; Weiva Sieh; Russell B McBride; Kezhen Fei; Joseph H Rothstein; Stacey E Alexeeff; Xiaoyu Song; Lori C Sakoda; Valerie McGuire; Ninah Achacoso; Luana Acton; Rhea Y Liang; Jafi A Lipson; Martin J Yaffe; Daniel L Rubin; Alice S Whittemore
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-02-17       Impact factor: 4.254

8.  Milk intake and mammographic density in premenopausal women.

Authors:  Yunan Han; Xiaoyu Zong; Yize Li; Graham A Colditz; Adetunji T Toriola
Journal:  Breast Cancer Res Treat       Date:  2018-11-20       Impact factor: 4.872

9.  Primary Care Provider Experience with Breast Density Legislation in Massachusetts.

Authors:  Christine M Gunn; Nancy R Kressin; Kristina Cooper; Cinthya Marturano; Karen M Freund; Tracy A Battaglia
Journal:  J Womens Health (Larchmt)       Date:  2018-01-17       Impact factor: 2.681

Review 10.  Breast density implications and supplemental screening.

Authors:  Athina Vourtsis; Wendie A Berg
Journal:  Eur Radiol       Date:  2018-09-25       Impact factor: 5.315

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