The Influence of Mammographic Density on Breast Cancer Risk

High mammographic breast density (HBD) is a well-established risk factor for increased breast cancer (BC) incidence (1-4) and later stage of breast cancer diagnosis (5, 6). Mechanistically, HBD may mask BC at screening and result in interval BC being diagnosed at a later stage (5, 7-12). Biologically, HBD may be associated with increased cell proliferation and a general increase in mitogenic factors (13). However, the biological mechanisms through which HBD may operate to increase BC risk are not clearly defined, and its potential role in tumor progression and BC aggressiveness remains a debated issue. Given that most of the conclusions with regards to HBD and BC risk are based on primarily monoracial (non-Latina White women) studies, not much is known regarding if HBD affects women across various races and ethnicities differently. These racial/ethnic differences are particularly relevant within the context of existing racial/ethnic breast cancer mortality disparities in the United States where non-Latina Black (NLB) women, despite their lower BC incidence, are more likely to die from the disease compared to their non-Latina White (NLW) counterparts (14-17). While differential access to care, comorbidities, and BC aggressiveness are suggested in the literature as contributors to this difference (18-24), the potential impact of breast density on this disparity has not been explored. Understanding the effects of HBD on BC risk in a diverse cohort would add to the scarce literature regarding the effect of HBD across various race/ethnicities. In this dissertation, the researcher proposes to explore whether breast density differs across racial/ethnic groups and what factors may account for these differences. Additionally, the researcher proposes to explore the association between high breast density and breast cancer incidence, aggressiveness, and stage at diagnosis in a cohort of diverse women presenting for breast cancer screening at a large healthcare network in Metropolitan Chicago, with the following aims: Aim 1: To explore how breast density (BD) may differ by race/ethnicity and other individual level factors (BMI, age, hormonal) Aim 2: To explore if BD impacts breast cancer (BC) risk by subtype Aim 3: To explore potential mechanisms through which BD influences breast cancer stage at diagnosi

Trends in Attaining Mammography Quality Benchmarks With Repeated Participation in a Quality Measurement Program: Going Beyond the Mammography Quality Standards Act to Address Breast Cancer Disparities

PURPOSE: The Mammography Quality Standards Act requires that mammography facilities conduct audits, but there are no specifications on the metrics to be measured. In a previous mammography quality improvement project, the authors examined whether breast cancer screening facilities could collect the data necessary to show that they met certain quality benchmarks. Here the authors present trends from the first 5 years of data collection to examine whether continued participation in this quality improvement program was associated with an increase in the number of benchmarks met for breast cancer screening. METHODS: Participating facilities across the state of Illinois (n = 114) with at least two time points of data collected (2006, 2009, 2010, 2011, and/or 2013) were included. Facilities provided aggregate data on screening mammographic examinations and corresponding diagnostic follow-up information, which was used to estimate 13 measures and corresponding benchmarks for patient tracking, callback, cancer detection, loss to follow-up, and timeliness of care. RESULTS: The number of facilities able to show that they met specific benchmarks increased with length of participation for many but not all measures. Trends toward meeting more benchmarks were apparent for cancer detection, timely imaging, not lost at biopsy, known minimal status (P \u3c .01 for all), and proportion of screening-detected cancers that were minimal and early stage (P \u3c .001 for both). CONCLUSIONS: Participation in the quality improvement program seemed to lead to improvements in patient tracking, callback and detection, and timeliness benchmarks