This article is part of a series on Mammographic density, edited by Norman F Boyd.

Review

Mammographic density, breast cancer risk and risk prediction

Celine M Vachon¹ , Carla H van Gils² , Thomas A Sellers³ , Karthik Ghosh¹ , Sandhya Pruthi¹ , Kathleen R Brandt¹ and V Shane Pankratz¹

¹  Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA

²  University Medical Center Utrecht, PO Box 85500, 3508 GA Utrecht, The Netherlands

³  H Lee Moffitt Cancer Center & Research Institute, 12902 Magnolia Drive Tampa, FL 33612, USA

author email corresponding author email

Breast Cancer Research 2007, 9:217doi:10.1186/bcr1829

Published:	20 December 2007

Abstract

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models.