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Clinical and epidemiological issues in mammographic density

Nature Reviews Clinical Oncology volume 9, pages 33–40 (2012)Cite this article

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Abstract

High mammographic density is associated with an increased risk of breast cancer, and of all known breast cancer risk factors has the greatest attributable fraction. Mammographic density is estimated to account for 16% of all breast cancers, but can be altered by endogenous and exogenous hormonal factors, and generally declines with age. Confounding factors such as age, parity, menopausal status and BMI make the interpretation of mammographic density particularly challenging. Furthermore, none of the established means of measuring mammographic density are entirely satisfactory because they are time consuming or subjective. It is hoped that by adding information regarding mammographic density to existing models of breast cancer risk assessment, the accuracy of individual risk assessments can be improved. Although mammographic density has clearly been shown to be a powerful factor for predicting the risk of developing breast cancer, its potential role in assessing hormonal preventive regimens and helping to tailor screening algorithms cannot be fully realized until we have more-precise, simple and reproducible density measures.

Key Points

  • Mammographic density appears as white areas on a mammogram and it comprises fibroglandular tissue, stroma and epithelium within the breast

  • The current ways of measuring mammographic density are time consuming and subjective

  • Mammographic density is one of the most important indicators of breast cancer risk; the greater the mammographic density the greater the breast cancer risk

  • Mammographic density can be altered by endogenous and exogenous hormonal factors, and generally declines with age

  • Models to predict a woman's risk of breast cancer from her mammographic density and other risk factors are currently being developed

  • Mammographic density has considerable potential in risk stratification and in monitoring the effects of interventions in risk alteration, but further work on measuring density and risk prediction is required

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Figure 1: Mammograms of a breast with very low and high density.
Figure 2: A schematic representation of some of the methods for assessing mammographic density.

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Acknowledgements

V. Assi is supported by a PhD studentship from Cancer Research UK.

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  1. Center for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK

    Valentina Assi, Jane Warwick, Jack Cuzick & Stephen W. Duffy

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J. Warwick and S. Duffy researched the data for the article, provided a substantial contribution to discussions of the content, wrote the article and edited the manuscript before submission. V. Assi contributed to researching the data for the article, discussions of the content and writing the article and J. Cuzick contributed to discussions of the content and editing the manuscript before submission.

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Correspondence to Stephen W. Duffy.

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Assi, V., Warwick, J., Cuzick, J. et al. Clinical and epidemiological issues in mammographic density. Nat Rev Clin Oncol 9, 33–40 (2012). https://doi.org/10.1038/nrclinonc.2011.173

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