Literature DB >> 29808426

Parenchymal pattern in women with dense breasts. Variation with age and impact on screening outcomes: observations from a UK screening programme.

Laura Ward1, S Heller2, S Hudson3, L Wilkinson3.   

Abstract

OBJECTIVES: To assess patterns of parenchymal tissue on mammography in women with dense breasts and to determine how this varies with age and affects recall to assessment and cancer diagnosis.
METHOD: Breast density data was obtained in women attending routine mammographic screening from April 2013 to March 2015 using automated breast density assessment software. Women with the densest breasts were selected for visual interpretation of parenchymal pattern (PP). One hundred non-assessed women, aged 50, 55, 60, 65 and 69-71 years (total = 500), provided controls. Cases included women recalled for assessment (mastectomy or implants excluded) (total = 280). Mammograms reviewed by ten readers and PP classified as: (1) very smooth; (2) mainly smooth; (3) mixed; (4) mainly nodular; (5) very nodular. The ratio of women in each category at each age and screening outcomes were compared by Pearson's chi-squared test.
RESULTS: Reader agreement for scoring PP was good (intraclass correlation = 0.6302). Proportions of women in each PP category were similar at all ages for controls (p = 0.147) and cases (p = 0.657). The ratio of PP categories did not vary significantly with age in those who underwent biopsy (p = 0.484). Thirty-four cancers were diagnosed. There was a significant correlation between a diagnosis of cancer and nodular PP compared to not nodular PP (p = 0.043).
CONCLUSIONS: The ratio of smooth to nodular pattern in women with the densest breasts did not vary with age. The PP of the breast tissue did not affect likelihood of recall to assessment or biopsy. There was a significant relationship between a nodular parenchymal pattern and diagnosis of cancer. KEY POINTS: • This paper shows that there is good agreement between mammogram readers when classifying mammographic PP on a five-point scale from very smooth to very nodular. • In non-assessed women with the densest breasts, there is no significant change in the proportions of smooth to nodular patterns with increasing age. • The likelihood of recall for further assessment or biopsy at assessment is not related to PP in women with highest breast density. • When recalled for further assessment, significantly more women are diagnosed with cancer in the group with nodular PP on mammography when compared with smooth and mixed patterns.

Entities:  

Keywords:  Breast cancer; Breast density; Breast neoplasms; Cancer screening; Mammography

Mesh:

Substances:

Year:  2018        PMID: 29808426     DOI: 10.1007/s00330-018-5420-4

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  14 in total

1.  Effect of baseline breast density on breast cancer incidence, stage, mortality, and screening parameters: 25-year follow-up of a Swedish mammographic screening.

Authors:  Sherry Yueh-Hsia Chiu; Stephen Duffy; Amy Ming-Fang Yen; Laszlo Tabár; Robert A Smith; Hsiu-Hsi Chen
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-04-20       Impact factor: 4.254

2.  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

3.  Comparison of digital mammography alone and digital mammography plus tomosynthesis in a population-based screening program.

Authors:  Per Skaane; Andriy I Bandos; Randi Gullien; Ellen B Eben; Ulrika Ekseth; Unni Haakenaasen; Mina Izadi; Ingvild N Jebsen; Gunnar Jahr; Mona Krager; Loren T Niklason; Solveig Hofvind; David Gur
Journal:  Radiology       Date:  2013-01-07       Impact factor: 11.105

4.  The Tabár classification of mammographic parenchymal patterns.

Authors:  I T Gram; E Funkhouser; L Tabár
Journal:  Eur J Radiol       Date:  1997-02       Impact factor: 3.528

5.  Mammographic parenchymal patterns and risk of breast cancer at and after a prevalence screen in Singaporean women.

Authors:  R W Jakes; S W Duffy; F C Ng; F Gao; E H Ng
Journal:  Int J Epidemiol       Date:  2000-02       Impact factor: 7.196

6.  Breast cancer screening with tomosynthesis (3D mammography) with acquired or synthetic 2D mammography compared with 2D mammography alone (STORM-2): a population-based prospective study.

Authors:  Daniela Bernardi; Petra Macaskill; Marco Pellegrini; Marvi Valentini; Carmine Fantò; Livio Ostillio; Paolina Tuttobene; Andrea Luparia; Nehmat Houssami
Journal:  Lancet Oncol       Date:  2016-06-23       Impact factor: 41.316

7.  Relationship between mammographic density and breast cancer death in the Breast Cancer Surveillance Consortium.

Authors:  Gretchen L Gierach; Laura Ichikawa; Karla Kerlikowske; Louise A Brinton; Ghada N Farhat; Pamela M Vacek; Donald L Weaver; Catherine Schairer; Stephen H Taplin; Mark E Sherman
Journal:  J Natl Cancer Inst       Date:  2012-08-21       Impact factor: 13.506

8.  Impact of Breast Density Legislation on Breast Cancer Risk Assessment and Supplemental Screening: A Survey of 110 Radiology Facilities.

Authors:  Lina Nayak; Kanae K Miyake; Jessica W T Leung; Elissa R Price; Yueyi I Liu; Bonnie N Joe; Edward A Sickles; William R Thomas; Jafi A Lipson; Bruce L Daniel; Jonathan Hargreaves; R James Brenner; Lawrence W Bassett; Haydee Ojeda-Fournier; Karen K Lindfors; Stephen A Feig; Debra M Ikeda
Journal:  Breast J       Date:  2016-06-14       Impact factor: 2.431

Review 9.  Mammographic density and breast cancer risk: current understanding and future prospects.

Authors:  Norman F Boyd; Lisa J Martin; Martin J Yaffe; Salomon Minkin
Journal:  Breast Cancer Res       Date:  2011-11-01       Impact factor: 6.466

10.  Inter-observer agreement according to three methods of evaluating mammographic density and parenchymal pattern in a case control study: impact on relative risk of breast cancer.

Authors:  Rikke Rass Winkel; My von Euler-Chelpin; Mads Nielsen; Pengfei Diao; Michael Bachmann Nielsen; Wei Yao Uldall; Ilse Vejborg
Journal:  BMC Cancer       Date:  2015-04-12       Impact factor: 4.430

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