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. 2018 Jan:88:48-56.
doi: 10.1016/j.ejca.2017.10.022. Epub 2017 Nov 27.

Mammographic density and breast cancer risk in breast screening assessment cases and women with a family history of breast cancer

Stephen W Duffy  1 , Oliver W E Morrish  2 , Prue C Allgood  3 , Richard Black  4 , Maureen G C Gillan  5 , Paula Willsher  6 , Julie Cooke  7 , Karen A Duncan  8 , Michael J Michell  9 , Hilary M Dobson  10 , Roberta Maroni  11 , Yit Y Lim  12 , Hema N Purushothaman  13 , Tamara Suaris  14 , Susan M Astley  15 , Kenneth C Young  16 , Lorraine Tucker  17 , Fiona J Gilbert  18
Affiliations

Mammographic density and breast cancer risk in breast screening assessment cases and women with a family history of breast cancer

Stephen W Duffy et al. Eur J Cancer. 2018 Jan.

Abstract

Background: Mammographic density has been shown to be a strong independent predictor of breast cancer and a causative factor in reducing the sensitivity of mammography. There remain questions as to the use of mammographic density information in the context of screening and risk management, and of the association with cancer in populations known to be at increased risk of breast cancer.

Aim: To assess the association of breast density with presence of cancer by measuring mammographic density visually as a percentage, and with two automated volumetric methods, Quantra™ and VolparaDensity™.

Methods: The TOMosynthesis with digital MammographY (TOMMY) study of digital breast tomosynthesis in the Breast Screening Programme of the National Health Service (NHS) of the United Kingdom (UK) included 6020 breast screening assessment cases (of whom 1158 had breast cancer) and 1040 screened women with a family history of breast cancer (of whom two had breast cancer). We assessed the association of each measure with breast cancer risk in these populations at enhanced risk, using logistic regression adjusted for age and total breast volume as a surrogate for body mass index (BMI).

Results: All density measures showed a positive association with presence of cancer and all declined with age. The strongest effect was seen with Volpara absolute density, with a significant 3% (95% CI 1-5%) increase in risk per 10 cm3 of dense tissue. The effect of Volpara volumetric density on risk was stronger for large and grade 3 tumours.

Conclusions: Automated absolute breast density is a predictor of breast cancer risk in populations at enhanced risk due to either positive mammographic findings or family history. In the screening context, density could be a trigger for more intensive imaging.

Keywords: Automated volumetric method; Breast cancer risk; Breast cancer screening; Digital breast tomosynthesis; Fibroglandular volume; Mammographic density; Quantra; Volpara.

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