Women with the highest mammographic density have a four to six-fold increased risk of breast cancer when compared to the ones with the least dense breasts. Mammographic breast density has also been associated with a wide array of factors related to the risk of breast cancer including age, menopausal status, age at first live birth, parity, body mass index, physical activity, alcohol consumption, hormone replacement therapy, endogenous levels of IGF-I and prolactin, family history of breast cancer, tamoxifen use and others. A question of interest is whether mammographic density is in the pathway by which these factors are related to breast cancer. To address this question, we conducted causal mediation analyses on two datasets using a newly developed statistical approach based on the counterfactual framework to examine the extent to which mammographic density acts as a mediator. The first dataset is pooled from four case-control studies performed in the western Washington state, contains 547 breast cancer cases (ascertained from a local Surveillance, Epidemiology, and End Results Program registry) and 472 controls (ascertained by random digit dialing) who had screening mammograms under age 50. The second dataset is from the Mayo Mammography Health Study (MMHS), which is a prospective cohort, comprised of 19,924 women (51.2% adjusted response rate) ages 35 and over, residing in the tri-state region (Minnesota, Iowa, and Wisconsin) surrounding the Mayo Clinic in Rochester, MN, without a history of breast cancer, who were scheduled for a screening mammogram at the Mayo Clinic between October 2003 and September 2006. Previous analyses from these two datasets have shown associations between some breast cancer risk factors and mammographic density. Results showed that mammographic density partially mediated the associations for some breast cancer risk factors such as breast calcifications, being parous, history of breast biopsy/aspiration/lumpectomy, and current use of hormone replacement therapy (HRT), but not factors such as a first-degree family history of breast cancer and age at first live birth, history of smoking, age at menopause. These results help us better understand the pathways and mechanisms whereby a risk factor may cause breast cancer. It also helps inform and refine clinical and public health interventions for breast cancer by assessing the relative importance of different pathways
