Mammographic density, breast cancer risk and risk prediction.
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.
Vachon
Celine M
CM
Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA. vachon.celine@mayo.edu
van Gils
Carla H
CH
Sellers
Thomas A
TA
Ghosh
Karthik
K
Pruthi
Sandhya
S
Brandt
Kathleen R
KR
Pankratz
V Shane
VS
D015982:Bias; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000208:ethnology / Q000473:pathology*; D005260:Female; D006801:Humans; D008327:Mammography; D015233:Models, Statistical; D016017:Odds Ratio; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors