Mammographic density, breast cancer risk and risk prediction

Celine M. Vachon, Carla H. van Gils, Thomas A. Sellers, Karthik Ghosh, Sandhya Pruthi, Kathleen R. Brandt, V. Shane Pankratz

Research output: Contribution to journalReview articlepeer-review

233 Scopus citations


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.

Original languageEnglish (US)
Article number217
JournalBreast Cancer Research
Issue number6
StatePublished - Dec 20 2007

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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