Literature DB >> 9690746

Mammographic breast density and risk of breast cancer: masking bias or causality?

C H van Gils1, J D Otten, A L Verbeek, J H Hendriks.   

Abstract

Masking bias is hypothesized to explain associations between breast density and breast cancer risk. Tumours in dense breasts may be concealed at the initial examination, but manifest themselves in later years, suggesting an increase in breast cancer incidence. We studied the association between breast density and breast cancer risk in 0, 1-2, 3-4 and 5-6 year periods between initial examination and diagnosis. We studied 359 cases and 922 referents, identified in a breast cancer screening programme in Nijmegen, The Netherlands. Breast density was assessed at the initial examination and classified as 'dense' (if > 25% of the breast was composed of density) or 'lucent' (< or = 25% density). In women examined with mid-1970s film screen mammography, we found that at time 0 the odds ratio (OR) for women with dense breasts compared to those with lucent breasts was 1.4 (95% confidence interval (CI): 0.7-6.2). After a 3-4 year period the risk was increased to 3.3 (95% CI: 1.5-7.1). Then, the risk decreased again (OR: 1.2, 95% CI: 0.6-2.7). This rise and decline in risk are in accordance with the masking hypothesis. The observation, however, that the risk at time 0 does not appear to be lower for women with dense breasts than for those with lucent breasts, seems to be inconsistent with the masking hypothesis and may be indicative of causality. The same analysis were performed in women whose initial screening examination was done with current high-quality mammography. Due to the small size of this study group no firm conclusions could be drawn, but it seems as if masking bias could still play a role with high-quality mammography.

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Year:  1998        PMID: 9690746     DOI: 10.1023/a:1007423824675

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  19 in total

1.  Long term breast cancer screening in Nijmegen, The Netherlands: the nine rounds from 1975-92.

Authors:  J D Otten; J A van Dijck; P G Peer; H Straatman; A L Verbeek; M Mravunac; J H Hendriks; R Holland
Journal:  J Epidemiol Community Health       Date:  1996-06       Impact factor: 3.710

2.  The oblique view of mammography.

Authors:  B Lundgren
Journal:  Br J Radiol       Date:  1977-09       Impact factor: 3.039

Review 3.  Mammographic parenchymal patterns and breast cancer risk.

Authors:  A F Saftlas; M Szklo
Journal:  Epidemiol Rev       Date:  1987       Impact factor: 6.222

4.  Short communication: breast parenchymal patterns and their changes with age.

Authors:  C H van Gils; J D Otten; A L Verbeek; J H Hendriks
Journal:  Br J Radiol       Date:  1995-10       Impact factor: 3.039

5.  Breast patterns as an index of risk for developing breast cancer.

Authors:  J N Wolfe
Journal:  AJR Am J Roentgenol       Date:  1976-06       Impact factor: 3.959

6.  Symmetry of projection in the quantitative analysis of mammographic images.

Authors:  J W Byng; N F Boyd; L Little; G Lockwood; E Fishell; R A Jong; M J Yaffe
Journal:  Eur J Cancer Prev       Date:  1996-10       Impact factor: 2.497

7.  Mammographic densities and risk of breast cancer.

Authors:  A F Saftlas; R N Hoover; L A Brinton; M Szklo; D R Olson; M Salane; J N Wolfe
Journal:  Cancer       Date:  1991-06-01       Impact factor: 6.860

8.  Mammographic parenchymal features and breast cancer in the breast cancer detection demonstration project.

Authors:  J Brisson; A S Morrison; N Khalid
Journal:  J Natl Cancer Inst       Date:  1988-12-07       Impact factor: 13.506

9.  Bias and the association of mammographic parenchymal patterns with breast cancer.

Authors:  N F Boyd; B O'Sullivan; J E Campbell; E Fishell; I Simor; G Cooke; T Germanson
Journal:  Br J Cancer       Date:  1982-02       Impact factor: 7.640

10.  The predictive value of positive test results in screening for breast cancer by mammography in the Nijmegen programme.

Authors:  P H Peeters; A L Verbeek; J H Hendriks; R Holland; M Mravunac
Journal:  Br J Cancer       Date:  1987-11       Impact factor: 7.640

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  25 in total

Review 1.  Clinical and epidemiological issues in mammographic density.

Authors:  Valentina Assi; Jane Warwick; Jack Cuzick; Stephen W Duffy
Journal:  Nat Rev Clin Oncol       Date:  2011-12-06       Impact factor: 66.675

2.  Combination of two-dimensional shear wave elastography with ultrasound breast imaging reporting and data system in the diagnosis of breast lesions: a new method to increase the diagnostic performance.

Authors:  Dan-Dan Li; Hui-Xiong Xu; Le-Hang Guo; Xiao-Wan Bo; Xiao-Long Li; Rong Wu; Jun-Mei Xu; Yi-Feng Zhang; Kun Zhang
Journal:  Eur Radiol       Date:  2015-12-29       Impact factor: 5.315

3.  Prediction of near-term breast cancer risk based on bilateral mammographic feature asymmetry.

Authors:  Maxine Tan; Bin Zheng; Pandiyarajan Ramalingam; David Gur
Journal:  Acad Radiol       Date:  2013-12       Impact factor: 3.173

4.  Evaluation of the kinetic properties of background parenchymal enhancement throughout the phases of the menstrual cycle.

Authors:  Alana R Amarosa; Jason McKellop; Ana Paula Klautau Leite; Melanie Moccaldi; Tess V Clendenen; James S Babb; Anne Zeleniuch-Jacquotte; Linda Moy; Sungheon Kim
Journal:  Radiology       Date:  2013-05-08       Impact factor: 11.105

5.  An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization.

Authors:  Yiqiu Shen; Nan Wu; Jason Phang; Jungkyu Park; Kangning Liu; Sudarshini Tyagi; Laura Heacock; S Gene Kim; Linda Moy; Kyunghyun Cho; Krzysztof J Geras
Journal:  Med Image Anal       Date:  2020-12-16       Impact factor: 8.545

6.  Validation of a method for measuring the volumetric breast density from digital mammograms.

Authors:  O Alonzo-Proulx; N Packard; J M Boone; A Al-Mayah; K K Brock; S Z Shen; M J Yaffe
Journal:  Phys Med Biol       Date:  2010-05-12       Impact factor: 3.609

7.  Mammographic density and markers of socioeconomic status: a cross-sectional study.

Authors:  Zoe Aitken; Kate Walker; Bernardine H Stegeman; Petra A Wark; Sue M Moss; Valerie A McCormack; Isabel dos Santos Silva
Journal:  BMC Cancer       Date:  2010-02-09       Impact factor: 4.430

8.  Mammographic breast density as a risk factor for breast cancer: awareness in a recently screened clinical sample.

Authors:  Suzanne C O'Neill; Kara Grace Leventhal; Marie Scarles; Chalanda N Evans; Erini Makariou; Edward Pien; Shawna Willey
Journal:  Womens Health Issues       Date:  2014-04-13

9.  Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model.

Authors:  Jeffrey A Tice; Steven R Cummings; Rebecca Smith-Bindman; Laura Ichikawa; William E Barlow; Karla Kerlikowske
Journal:  Ann Intern Med       Date:  2008-03-04       Impact factor: 25.391

Review 10.  Beyond mammography: new frontiers in breast cancer screening.

Authors:  Jennifer S Drukteinis; Blaise P Mooney; Chris I Flowers; Robert A Gatenby
Journal:  Am J Med       Date:  2013-04-03       Impact factor: 4.965

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