The distribution of breast density in women aged 18 years and older.

PURPOSE: Age and body mass index (BMI) are critical considerations when assessing individual breast cancer risk, particularly for women with dense breasts. However, age- and BMI-standardized estimates of breast density are not available for screen-aged women, and little is known about the distribution of breast density in women aged < 40. This cross-sectional study uses three different modalities: optical breast spectroscopy (OBS), dual-energy X-ray absorptiometry (DXA), and mammography, to describe the distributions of breast density across categories of age and BMI. METHODS: Breast density measures were estimated for 1,961 Australian women aged 18-97 years using OBS (%water and %water + %collagen). Of these, 935 women had DXA measures (percent and absolute fibroglandular dense volume, %FGV and FGV, respectively) and 354 had conventional mammographic measures (percent and absolute dense area). The distributions for each breast density measure were described across categories of age and BMI. RESULTS: The mean age was 38 years (standard deviation = 15). Median breast density measures decreased with age and BMI for all three modalities, except for DXA-FGV, which increased with BMI and decreased after age 30. The variation in breast density measures was largest for younger women and decreased with increasing age and BMI. CONCLUSION: This unique study describes the distribution of breast density measures for women aged 18-97 using alternative and conventional modalities of measurement. While this study is the largest of its kind, larger sample sizes are needed to provide clinically useful age-standardized measures to identify women with high breast density for their age or BMI.

Alternative methods to measure breast density in younger women.

BACKGROUND: Breast density is a strong and potentially modifiable breast cancer risk factor. Almost everything we know about breast density has been derived from mammography, and therefore, very little is known about breast density in younger women aged <40. This study examines the acceptability and performance of two alternative breast density measures, Optical Breast Spectroscopy (OBS) and Dual X-ray Absorptiometry (DXA), in women aged 18-40. METHODS: Breast tissue composition (percent water, collagen, and lipid content) was measured in 539 women aged 18-40 using OBS. For a subset of 169 women, breast density was also measured via DXA (percent fibroglandular dense volume (%FGV), absolute dense volume (FGV), and non-dense volume (NFGV)). Acceptability of the measurement procedures was assessed using an adapted validated questionnaire. Performance was assessed by examining the correlation and agreement between the measures and their associations with known determinants of mammographic breast density. RESULTS: Over 93% of participants deemed OBS and DXA to be acceptable. The correlation between OBS-%water + collagen and %FGV was 0.48. Age and BMI were inversely associated with OBS-%water + collagen and %FGV and positively associated with OBS-%lipid and NFGV. CONCLUSIONS: OBS and DXA provide acceptable and viable alternative methods to measure breast density in younger women aged 18-40 years.

The association between breast arterial calcification and atherosclerotic cardiovascular disease in an Australian population-based breast cancer case-control study.

PURPOSE: Atherosclerotic cardiovascular disease (ASCVD) is a major cause of morbidity and mortality. Breast arterial calcification (BAC) on mammograms is not associated with breast cancer risk. However, there is increasing evidence supporting its association with cardiovascular disease (CVD). This study examines the association between BAC and ASCVD and their risk factors within an Australian population-based breast cancer study. MATERIALS AND METHODS: Data from the controls who participated in the breast cancer environment and employment study (BCEES) were linked with the Western Australian Department of Health Hospital Morbidity database and Mortality Registry to obtain ASCVD outcomes and related risk factor data. Mammograms from participants with no prior history of ASCVD were assessed for BAC by a radiologist. Cox proportional hazards regression was used to examine the association between BAC and later occurrence of an ASCVD event. Logistic regression was used to investigate the factors associated with BAC. RESULTS: A total of 1020 women with a mean age of 60 (sd = 7.0 years) were included and BAC found in 184 (18.0%). Eighty (7.8%) of the 1020 participants developed ASCVD, with an average time to event of 6.2 years (sd = 4.6) from baseline. In univariate analysis, participants with BAC were more likely to have an ASCVD event (HR = 1.96 95% CI 1.29-2.99). However, after adjusting for other risk factors, this association attenuated (HR = 1.37 95% CI 0.88-2.14). Increasing age (OR = 1.15, 95% CI 1.12-1.19) and parity (pLRT < 0.001) were associated with BAC. CONCLUSION: BAC is associated with increased ASCVD risk, but this is not independent of cardiovascular risk factors.

The impact of breast density notification on rescreening rates within a population-based mammographic screening program.

BACKGROUND: High participation in mammographic screening is essential for its effectiveness to detect breast cancers early and thereby, improve breast cancer outcomes. Breast density is a strong predictor of breast cancer risk and significantly reduces the sensitivity of mammography to detect the disease. There are increasing mandates for routine breast density notification within mammographic screening programs. It is unknown if breast density notification impacts the likelihood of women returning to screening when next due (i.e. rescreening rates). This study investigates the association between breast density notification and rescreening rates using individual-level data from BreastScreen Western Australia (WA), a population-based mammographic screening program. METHODS: We examined 981,705 screening events from 311,656 women aged 40+ who attended BreastScreen WA between 2008 and 2017. Mixed effect logistic regression was used to investigate the association between rescreening and breast density notification status. RESULTS: Results were stratified by age (younger, targeted, older) and screening round (first, second, third+). Targeted women screening for the first time were more likely to return to screening if notified as having dense breasts (Percentunadjusted notified vs. not-notified: 57.8% vs. 56.1%; Padjusted = 0.016). Younger women were less likely to rescreen if notified, regardless of screening round (all P < 0.001). There was no association between notification and rescreening in older women (all P > 0.72). CONCLUSIONS: Breast density notification does not deter women in the targeted age range from rescreening but could potentially deter younger women from rescreening. These results suggest that all breast density notification messaging should include information regarding the importance of regular mammographic screening to manage breast cancer risk, particularly for younger women. These results will directly inform BreastScreen programs in Australia as well as other population-based screening providers outside Australia who notify women about breast density or are considering implementing breast density notification.

Bayesian methods of confidence interval construction for the population attributable risk from cross-sectional studies.

Population attributable risk measures the public health impact of the removal of a risk factor. To apply this concept to epidemiological data, the calculation of a confidence interval to quantify the uncertainty in the estimate is desirable. However, because perhaps of the confusion surrounding the attributable risk measures, there is no standard confidence interval or variance formula given in the literature. In this paper, we implement a fully Bayesian approach to confidence interval construction of the population attributable risk for cross-sectional studies. We show that, in comparison with a number of standard Frequentist methods for constructing confidence intervals (i.e. delta, jackknife and bootstrap methods), the Bayesian approach is superior in terms of percent coverage in all except a few cases. This paper also explores the effect of the chosen prior on the coverage and provides alternatives for particular situations. Copyright © 2016 John Wiley & Sons, Ltd.

The impact of height and weight on rescreening rates within a population-based breast screening program.

INTRODUCTION: Women with obesity are at increased risk of post-menopausal breast cancer and less likely to participate in breast screening. This study investigates the impact of asking women their height and weight within a population-based screening program, and the association of BMI with rescreening status. METHODS: Data regarding 666,130 screening events from 318,198 women aged 50-74 attending BreastScreen Western Australia between 2016 and 2021 were used to compare crude and age-standardised rescreening rates over time. Mixed effects logistic regression was used to investigate associations of BMI with rescreening status. RESULTS: Rescreening rates for women screened since 2016 were within 1.8% points from the previous reporting period, stratified by screening round. Increasing BMI was associated with decreased likelihood of returning to breast screening (OR = 0.993, 95% CI: 0.988-0.998; OR = 0.989, 95% CI: 0.984-0.994; OR = 0.985, 95% CI: 0.982-0.987 for women screening for the first, second and third+ time, respectively). CONCLUSIONS: This large, prospective study supports implementation of routine height and weight collection within breast screening programs. It shows that asking women their height and weight does not deter them from returning to screening and that women with increased BMI are less likely to rescreen, highlighting a need for targeted interventions to improve screening barriers for women living with obesity.

The Prospective Association between Early Life Growth and Breast Density in Young Adult Women.

Breast density is a strong intermediate endpoint to investigate the association between early-life exposures and breast cancer risk. This study investigates the association between early-life growth and breast density in young adult women measured using Optical Breast Spectroscopy (OBS) and Dual X-ray Absorptiometry (DXA). OBS measurements were obtained for 536 female Raine Cohort Study participants at ages 27-28, with 268 completing DXA measurements. Participants with three or more height and weight measurements from ages 8 to 22 were used to generate linear growth curves for height, weight and body mass index (BMI) using SITAR modelling. Three growth parameters (size, velocity and timing) were examined for association with breast density measures, adjusting for potential confounders. Women who reached their peak height rapidly (velocity) and later in adolescence (timing) had lower OBS-breast density. Overall, women who were taller (size) had higher OBS-breast density. For weight, women who grew quickly (velocity) and later in adolescence (timing) had higher absolute DXA-breast density. Overall, weight (size) was also inversely associated with absolute DXA-breast density, as was BMI. These findings provide new evidence that adolescent growth is associated with breast density measures in young adult women, suggesting potential mediation pathways for breast cancer risk in later life.

Assessment of repeated reference measurements to inform the validity of optical breast spectroscopy.

Mammographic breast density is a strong breast cancer risk factor, and its routine clinical measurement could potentially be used to identify women at higher risk of breast cancer and/or monitor primary prevention strategies. Previous reports of optical breast spectroscopy (OBS), a novel approach to measuring breast density, demonstrated that it is safe (no ionizing radiation), portable, low-cost, and does not require image interpretation but have been limited to small, single-center studies. Reference measurements taken on a phantom breast prior to and after each woman's OBS assessment are required for the calibration of the system transfer function as a part of processing participant data. To inform the validity of participant data, a detailed description of the reference measurements and a repeatability analysis of these measurements taken before and after participant assessment is presented. Reference measurements for OBS from 539 women aged 18-40 years were obtained as a part of a high-throughput epidemiological pilot study. Of these, measurements from 20 women with no useable data due to device failure (3.7%) were excluded and from another 12 women due to user error. The intra-class correlation (ICC) within complete pairs of reference data (taken before and after assessment) was high (all ICC > 0.84). The analysis presented here confirms the OBS participant data as valid for use in ongoing epidemiological research, providing further supporting evidence of OBS as a measure of breast density. A novel method of measuring breast density is needed to bridge large gaps in the knowledge of breast density in younger women and its relation to later-life breast cancer risk.

Confusion and Anxiety Following Breast Density Notification: Fact or Fiction?

In the absence of evidence-based screening recommendations for women with dense breasts, it is important to know if breast density notification increases women's anxiety. This study describes psychological reactions and future screening intentions of women attending a public mammographic screening program in Western Australia. Two-thirds of notified women indicated that knowing their breast density made them feel informed, 21% described feeling anxious, and 23% confused. Of the notified women who reported anxiety, 96% intended to re-screen when due (compared to 91% of all notified women and 93% of controls; p = 0.007 and p < 0.001, respectively). In summary, reported anxiety (following breast density notification) appears to increase women's intentions for future screening, not the reverse.