Mammographic density and ageing: A collaborative pooled analysis of cross-sectional data from 22 countries worldwide

Effect of a Randomized Trial of a Web-Based Intervention on Patient-Provider Communication About Breast Density

Background: Breast density increases breast cancer risk and decreases mammographic detection. We evaluated a personalized web-based intervention designed to improve breast cancer risk communication between women and their providers. Materials and Methods: This was a secondary outcome analysis of an online randomized trial. Women aged 40-69 years were randomized, February 2017-May 2018, to a control (n = 503) versus intervention website (n = 492). The intervention website included information about breast density, personalized breast cancer risk, chemoprevention, and magnetic resonance imaging. Participants self-reported communication about density with providers (yes/no) at 6 weeks and 12 months. We used logistic regression with generalized estimating equations to evaluate the association of study arm with density communication. In secondary analyses, we tested if the intervention was associated with indicators of patient activation (breast cancer worry, perceived risk, or health care use). Results: Women (mean age 62 years) in the intervention versus control arm were 2.39 times (95% confidence interval [CI] = 1.37-4.18) more likely to report density communication at 6 weeks; this effect persisted at 12 months (odds ratio [OR] = 1.71, 95% CI = 1.25-2.35). At 6 weeks, this effect was only significant among women who reported (OR = 3.23, 95% CI = 1.24-8.40) versus did not report any previous density discussions (OR = 1.64, 95% CI = 0.83-3.26). A quarter of women in each arm never had a density conversation at any time during the study. Conclusions: Despite providing personalized density and risk information, the intervention did not promote density discussions between women and their providers who had not had them previously. This intervention is unlikely to be used clinically to motivate density conversations in women who have not had them before. Clinical trial registration number NCT03029286.

68Ga-FAPI-PET/CT in patients with various gynecological malignancies

PURPOSE

68Ga-FAPI (fibroblast activation protein inhibitor) is a novel and highly promising radiotracer for PET/CT imaging. The aim of this retrospective analysis is to explore the potential of FAPI-PET/CT in gynecological malignancies. We assessed biodistribution, tumor uptake, and the influence of pre- or postmenopausal status on tracer accumulation in hormone-sensitive organs. Furthermore, a comparison with the current standard oncological tracer 18F-FDG was performed in selected cases.

PATIENTS AND METHODS

A total of 31 patients (median age 59.5) from two centers with several gynecological tumors (breast cancer; ovarian cancer; cervical cancer; endometrial cancer; leiomyosarcoma of the uterus; tubal cancer) underwent 68Ga-FAPI-PET/CT. Out of 31 patients, 10 received an additional 18F-FDG scan within a median time interval of 12.5 days (range 1-76). Tracer uptake was quantified by standardized uptake values (SUV)max and (SUV)mean, and tumor-to-background ratio (TBR) was calculated (SUVmax tumor/ SUVmean organ). Moreover, a second cohort of 167 female patients with different malignancies was analyzed regarding their FAPI uptake in normal hormone-responsive organs: endometrium (n = 128), ovary (n = 64), and breast (n = 147). These patients were categorized by age as premenopausal (<35 years; n = 12), postmenopausal (>65 years; n = 68), and unknown menstrual status (35-65 years; n = 87), followed by an analysis of FAPI uptake of the pre- and postmenopausal group.

RESULTS

In 8 out of 31 patients, the primary tumor was present, and all 31 patients showed lesions suspicious for metastasis (n = 81) demonstrating a high mean SUVmax in both the primary (SUVmax 11.6) and metastatic lesions (SUVmax 9.7). TBR was significantly higher in 68Ga-FAPI compared to 18F-FDG for distant metastases (13.0 vs. 5.7; p = 0.047) and by trend for regional lymph node metastases (31.9 vs 27.3; p = 0.6). Biodistribution of 68Ga-FAPI-PET/CT presented significantly lower uptake or no significant differences in 15 out of 16 organs, compared to 18F-FDG-PET/CT. The highest uptake of all primary lesions was obtained in endometrial carcinomas (mean SUVmax 18.4), followed by cervical carcinomas (mean SUVmax 15.22). In the second cohort, uptake in premenopausal patients differed significantly from postmenopausal patients in endometrium (11.7 vs 3.9; p < 0.0001) and breast (1.8 vs 1.0; p = 0.004), whereas no significant difference concerning ovaries (2.8 vs 1.6; p = 0.141) was observed.

CONCLUSION

Due to high tracer uptake resulting in sharp contrasts in primary and metastatic lesions and higher TBRs than 18F-FDG-PET/CT, 68Ga-FAPI-PET/CT presents a promising imaging method for staging and follow-up of gynecological tumors. The presence or absence of the menstrual cycle seems to correlate with FAPI accumulation in the normal endometrium and breast. This first investigation of FAP ligands in gynecological tumor entities supports clinical application and further research in this field.

Biological Mechanisms and Therapeutic Opportunities in Mammographic Density and Breast Cancer Risk

Mammographic density is an important risk factor for breast cancer; women with extremely dense breasts have a four to six fold increased risk of breast cancer compared to women with mostly fatty breasts, when matched with age and body mass index. High mammographic density is characterised by high proportions of stroma, containing fibroblasts, collagen and immune cells that suggest a pro-tumour inflammatory microenvironment. However, the biological mechanisms that drive increased mammographic density and the associated increased risk of breast cancer are not yet understood. Inflammatory factors such as monocyte chemotactic protein 1, peroxidase enzymes, transforming growth factor beta, and tumour necrosis factor alpha have been implicated in breast development as well as breast cancer risk, and also influence functions of stromal fibroblasts. Here, the current knowledge and understanding of the underlying biological mechanisms that lead to high mammographic density and the associated increased risk of breast cancer are reviewed, with particular consideration to potential immune factors that may contribute to this process.

Prolonged Time from Diagnosis to Breast-Conserving Surgery is Associated with Upstaging in Hormone Receptor-Positive Invasive Ductal Breast Carcinoma

BACKGROUND

Time to surgery (TTS) has been suggested to have an association with mortality in early-stage breast cancer.

OBJECTIVE

This study aims to determine the association between TTS and preoperative disease progression in tumor size or nodal status among women diagnosed with clinical T1N0M0 ductal breast cancer.

METHODS

Women diagnosed with clinical T1N0M0 ductal breast cancer who had breast-conserving surgery as their first definitive treatment between 2010 and 2016 (n = 90,405) were analyzed using the National Cancer Database. Separate multivariable logistic regression models for hormone receptor (HR)-positive and HR-negative patients, adjusted for clinical and demographic variables, were used to assess the relationship between TTS and upstaging of tumor size (T-upstaging) or nodal status (N-upstaging).

RESULTS

T-upstaging occurred in 6.76% of HR-positive patients and 11.00% of HR-negative patients, while N-upstaging occurred in 12.69% and 10.75% of HR-positive and HR-negative patients, respectively. Among HR-positive patients, odds of T-upstaging were higher for 61-90 days TTS (odds ratio [OR] 1.18, 95% confidence interval [CI] 1.05-1.34) and ≥91 days TTS (OR 1.47, 95% CI 1.17-1.84) compared with ≤30 days TTS, and odds of N- upstaging were higher for ≥91 days TTS (OR 1.35, 95% CI 1.13-1.62). No association between TTS and either T- or N-upstaging was found among HR-negative patients. Other clinical and demographic variables, including grade, tumor location, and race/ethnicity, were associated with both T- and N-upstaging.

CONCLUSION

TTS ≥61 and ≥91 days was a significant predictor of T- and N-upstaging, respectively, in HR-positive patients; however, TTS was not associated with upstaging in HR-negative breast cancer. Delays in surgery may contribute to measurable disease progression in T1N0M0 ductal breast cancer.

Mammographic Density Changes over Time and Breast Cancer Risk: A Systematic Review and Meta-Analysis

Simple Summary

Although mammographic density is strongly linked to the risk of breast cancer, research on the relationship between changes in density over time and the risk of breast cancer has shown conflicting results. We found in the present meta-analysis that increased breast density over time was associated with higher breast cancer risk whereas decreased breast density might be associated with lower breast cancer risk. The results of the meta-analysis constitute a potential opportunity for more individualized screening strategies based on the evolution of breast density during mammography screening.

Abstract

The aim of this meta-analysis was to evaluate the association between mammographic density changes over time and the risk of breast cancer. We performed a systematic literature review based on the PubMed and ISI Web of Knowledge databases. A meta-analysis was conducted by computing extracted hazard ratios (HRs) and 95% confidence intervals (CIs) for cohort studies or odds ratios (ORs) and 95% confidence interval using inverse variance method. Of the nine studies included, five were cohort studies that used HR as a measurement type for their statistical analysis and four were case–control or cohort studies that used OR as a measurement type. Increased breast density over time in cohort studies was associated with higher breast cancer risk (HR: 1.61; 95% CI: 1.33–1.96) whereas decreased breast density over time was associated with lower breast cancer risk (HR: 0.78; 95% CI: 0.71–0.87). Similarly, increased breast density over time was associated with higher breast cancer risk in studies presented ORs (pooled OR: 1.85; 95% CI: 1.29–2.65). Our findings imply that an increase in breast density over time seems to be linked to an increased risk of breast cancer, whereas a decrease in breast density over time seems to be linked to a lower risk of breast cancer.

Association between skeletal muscle mass and mammographic breast density

Mammographic density (MD) of the breast and body mass index (BMI) are inversely associated with each other, but have inconsistent associations with respect to the risk of breast cancer. Skeletal muscle mass index (SMI) has been considered to reflect a relatively accurate fat and muscle percentage in the body. So, we evaluated the relation between SMI and MD. A cross-sectional study was performed in 143,456 women who underwent comprehensive examinations from 2012 to 2016. BMI was adjusted to analyze whether SMI is an independent factor predicting dense breast. After adjustment for confounding factors including BMI, the odds ratios for MD for the dense breasts was between the highest and lowest quartiles of SMI at 2.65 for premenopausal women and at 2.39 for postmenopausal women. SMI was a significant predictor for MD, which could be due to the similar growth mechanism of the skeletal muscle and breast parenchymal tissue. Further studies are needed to understand the causal link between muscularity, MD and breast cancer risk.

Breast Density Awareness and Knowledge in a Mammography Screening Cohort of Predominantly Hispanic Women: Does Breast Density Notification Matter?

BACKGROUND

New York State law mandates that women with dense breasts receive a written notification of their breast density (BD) and its implications, but data on the impact of dense breast notification (DBN) on BD awareness and knowledge in diverse populations remain limited.

METHODS

Between 2016 and 2018, we collected survey and mammographic data from 666 women undergoing screening mammography in New York City (ages 40-60, 80% Hispanic, 69% Spanish-speaking) to examine the impact of prior DBN on BD awareness by sociodemographic and breast cancer risk factors, and describe BD knowledge by sources of information.

RESULTS

Only 24.8% of the overall sample and 34.9% of women receiving DBN had BD awareness. In multivariable models adjusting for DBN, awareness was significantly lower in women who were Spanish-speaking [OR, 0.16; 95% confidence interval (CI), 0.09-0.30 vs. English speakers], were foreign-born (OR, 0.31; 95% CI, 0.16-0.58 vs. U.S.-born), and had lower educational attainment (e.g., high school degree or less; OR, 0.14; 95% CI, 0.08-0.26 vs. college or higher degree). Women receiving DBN were more likely to be aware of BD (OR, 2.61; 95% CI, 1.59-4.27) but not more knowledgeable about the impact of BD on breast cancer risk and detection. However, women reporting additional communication about their BD showed greater knowledge in these areas.

CONCLUSIONS

DBN increases BD awareness disproportionately across sociodemographic groups.

IMPACT

Efforts to improve communication of DBN must focus on addressing barriers in lower socioeconomic and racially and ethnically diverse women, including educational and language barriers.

Association of Breast Density With Breast Cancer Risk Among Women Aged 65 Years or Older by Age Group and Body Mass Index

IMPORTANCE

Breast density is associated with breast cancer risk in women aged 40 to 65 years, but there is limited evidence of its association with risk of breast cancer among women aged 65 years or older.

OBJECTIVE

To compare the association between breast density and risk of invasive breast cancer among women aged 65 to 74 years vs women aged 75 years or older and to evaluate whether the association is modified by body mass index (BMI).

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study used data from the Breast Cancer Surveillance Consortium from January 1, 1996, to December 31, 2012, for US women aged 65 years or older who underwent screening mammography. Data were analyzed from January 1, 2018, to December 31, 2020.

EXPOSURES

Breast Imaging Reporting and Data System breast density category, age, and BMI.

MAIN OUTCOMES AND MEASURES

The 5-year cumulative incidence of invasive breast cancer by level of breast density (almost entirely fat, scattered fibroglandular densities, or heterogeneous or extreme density) and age (65-74 vs ≥75 years) was calculated using weighted means. Cox proportional hazards models were fit to estimate the association of breast density with invasive breast cancer risk. The likelihood ratio test was used to test the interaction between BMI and breast density.

RESULTS

A total of 221 714 screening mammograms from 193 787 women were included in the study; a total of 38% of the study population was aged 75 years or older. Of the mammograms, most were from women aged 65 to 74 years (64.6%) and non-Hispanic White individuals (81.4%). The 5-year cumulative incidence of invasive breast cancer increased in association with increasing breast density among women aged 65 to 74 years (almost entirely fatty breasts: 11.3 per 1000 women [95% CI, 10.4-12.5 per 1000 women]; scattered fibroglandular densities: 17.2 per 1000 women [95% CI, 16.1-17.9 per 1000 women]; extremely or heterogeneously dense breasts: 23.7 per 1000 women [95% CI, 22.4-25.3 per 1000 women]) and among those aged 75 years or older (fatty breasts: 13.5 per 1000 women [95% CI, 11.6-15.5]; scattered fibroglandular densities: 18.4 per 1000 women [95% CI, 17.0-19.5 per 1000 women]; extremely or heterogeneously dense breasts: 22.5 per 1000 women [95% CI, 20.2-24.2 per 1000 women]). Extreme or heterogeneous breast density was associated with increased risk of breast cancer compared with scattered fibroglandular breast density in both age categories (65-74 years: hazard ratio [HR], 1.39 [95% CI, 1.28-1.50]; ≥75 years: HR, 1.23 [95% CI, 1.10-1.37]). Women with almost entirely fatty breasts had a decrease of approximately 30% (range, 27%-34%) in the risk of invasive breast cancer compared with women with scattered fibroglandular breast density (65-74 years: HR, 0.66 [95% CI, 0.58-0.75]; ≥75 years: HR, 0.73; 95% CI, 0.62-0.86). Associations between breast density and breast cancer risk were not significantly modified by BMI (for age 65-74 years: likelihood ratio test, 2.67; df, 2; P = .26; for age ≥75 years, 2.06; df, 2; P = .36).

CONCLUSIONS AND RELEVANCE

The findings suggest that breast density is associated with increased risk of invasive breast cancer among women aged 65 years or older. Breast density and life expectancy should be considered together when discussing the potential benefits vs harms of continued screening mammography in this population.

Biomarkers of mammographic density in premenopausal women

BACKGROUND

While mammographic density is one of the strongest risk factors for breast cancer, little is known about its determinants, especially in young women. We applied targeted metabolomics to identify circulating metabolites specifically associated with mammographic density in premenopausal women. Then, we aimed to identify potential correlates of these biomarkers to guide future research on potential modifiable determinants of mammographic density.

METHODS

A total of 132 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids, hexose) were measured by tandem liquid chromatography/mass spectrometry in plasma samples from 573 premenopausal participants in the Mexican Teachers' Cohort. Associations between metabolites and percent mammographic density were assessed using linear regression models, adjusting for breast cancer risk factors and accounting for multiple tests. Mean concentrations of metabolites associated with percent mammographic density were estimated across levels of several lifestyle and metabolic factors.

RESULTS

Sphingomyelin (SM) C16:1 and phosphatidylcholine (PC) ae C30:2 were inversely associated with percent mammographic density after correction for multiple tests. Linear trends with percent mammographic density were observed for SM C16:1 only in women with body mass index (BMI) below the median (27.4) and for PC ae C30:2 in women with a BMI over the median. SM C16:1 and PC ae C30:2 concentrations were positively associated with cholesterol (total and HDL) and inversely associated with number of metabolic syndrome components.

CONCLUSIONS

We identified new biomarkers associated with mammographic density in young women. The association of these biomarkers with mammographic density and metabolic parameters may provide new perspectives to support future preventive actions for breast cancer.

The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study

We evaluated the association between short-term change in body mass index (BMI) and breast density during a 1 year weight-loss intervention (Manchester, UK). We included 65 premenopausal women (35-45 years, ≥7 kg adult weight gain, family history of breast cancer). BMI and breast density (semi-automated area-based, automated volume-based) were measured at baseline, 1 year, and 2 years after study entry (1 year post intervention). Cross-sectional (between-women) and short-term change (within-women) associations between BMI and breast density were measured using repeated-measures correlation coefficients and multivariable linear mixed models. BMI was positively correlated with dense volume between-women (r = 0.41, 95%CI: 0.17, 0.61), but less so within-women (r = 0.08, 95%CI: -0.16, 0.28). There was little association with dense area (between-women r = -0.12, 95%CI: -0.38, 0.16; within-women r = 0.01, 95%CI: -0.24, 0.25). BMI and breast fat were positively correlated (volume: between r = 0.77, 95%CI: 0.69, 0.84, within r = 0.58, 95%CI: 0.36, 0.75; area: between r = 0.74, 95%CI: 0.63, 0.82, within r = 0.45, 95%CI: 0.23, 0.63). Multivariable models reported similar associations. Exploratory analysis suggested associations between BMI gain from 20 years and density measures (standard deviation change per +5 kg/m2 BMI: dense area: +0.61 (95%CI: 0.12, 1.09); fat volume: -0.31 (95%CI: -0.62, 0.00)). Short-term BMI change is likely to be positively associated with breast fat, but we found little association with dense tissue, although power was limited by small sample size.

Optimization of prediction methods for risk assessment of pathogenic germline variants in the Japanese population

Predicting pathogenic germline variants (PGVs) in breast cancer patients is important for selecting optimal therapeutics and implementing risk reduction strategies. However, PGV risk factors and the performance of prediction methods in the Japanese population remain unclear. We investigated clinicopathological risk factors using the Tyrer‐Cuzick (TC) breast cancer risk evaluation tool to predict BRCA PGVs in unselected Japanese breast cancer patients (n = 1,995). Eleven breast cancer susceptibility genes were analyzed using target‐capture sequencing in a previous study; the PGV prevalence in BRCA1, BRCA2, and PALB2 was 0.75%, 3.1%, and 0.45%, respectively. Significant associations were found between the presence of BRCA PGVs and early disease onset, number of familial cancer cases (up to third‐degree relatives), triple‐negative breast cancer patients under the age of 60, and ovarian cancer history (all P < .0001). In total, 816 patients (40.9%) satisfied the National Comprehensive Cancer Network (NCCN) guidelines for recommending multigene testing. The sensitivity and specificity of the NCCN criteria for discriminating PGV carriers from noncarriers were 71.3% and 60.7%, respectively. The TC model showed good discrimination for predicting BRCA PGVs (area under the curve, 0.75; 95% confidence interval, 0.69‐0.81). Furthermore, use of the TC model with an optimized cutoff of TC score ≥0.16% in addition to the NCCN guidelines improved the predictive efficiency for high‐risk groups (sensitivity, 77.2%; specificity, 54.8%; about 11 genes). Given the influence of ethnic differences on prediction, we consider that further studies are warranted to elucidate the role of environmental and genetic factors for realizing precise prediction.

Association between changes in mammographic density category and the risk of breast cancer: A nationwide cohort study in East-Asian women

Breast density is strongly associated with breast cancer risk; however, studies on the association between density changes and breast cancer risk have controversial results. The aim of our study was to determine the association between breast density changes and breast cancer risk in East-Asian women. We included 3 301 279 women aged ≥40 years screened for breast cancer twice during 2009 to 2010 and 2011 to 2012. Data were obtained from the National Health Insurance Service (NHIS) database. Breast density was evaluated using the Breast Imaging-Reporting and Data System (BI-RADS). Relative risk (RR) and 5-year risk of developing breast cancer according to density category changes were calculated. Overall, 23.0% of the women had a higher breast density and 22.2% of the women had a lower breast density in second screening compared to the first. An increase in the BI-RADS density category between two subsequent mammographic screenings was associated with an increase in breast cancer risk and vice versa in terms of RR. The 5-year breast cancer risk was affected by the initial BI-RADS density category, changes in density category and patients' characteristics such as age, menopausal status and family history of breast cancer. In patients with breast cancer family history, the 5-year breast cancer risk was prominent, at a maximum of 2.39% (95% CI = 1.23-3.55) in women with breast density category of 2 to 4. Changes in the BI-RADS density category were associated with breast cancer risk. Longitudinal measures of BI-RADS density may be helpful in identifying high-risk women, especially those with a breast cancer family history.

Association of Interactions Between Mammographic Density Phenotypes and Established Risk Factors With Breast Cancer Risk, by Tumor Subtype and Menopausal Status

Previous studies suggest that the association between mammographic density (MD) and breast cancer risk might be modified by other breast cancer risk factors. In this study, we assessed multiplicative interactions between MD measures and established risk factors on the risk of invasive breast cancer overall and according to menopausal and estrogen receptor status. We used data on 2,137 cases and 4,346 controls from a nested case-control study within the Nurses' Health Study (1976-2004) and Nurses' Health Study II (1989-2007), whose data on percent mammographic density (PMD) and absolute area of dense tissue and nondense tissue (NDA) were available. No interaction remained statistically significant after adjusting for number of comparisons. For breast cancer overall, we observed nominally significant interactions (P < 0.05) between nulliparity and PMD/NDA, age at menarche and area of dense tissue, and body mass index and NDA. Individual nominally significant interactions across MD measures and risk factors were also observed in analyses stratified by either menopausal or estrogen receptor status. Our findings help provide further insights into potential mechanisms underlying the association between MD and breast cancer.

Simplified Breast Risk Tool Integrating Questionnaire Risk Factors, Mammographic Density, and Polygenic Risk Score: Development and Validation

BACKGROUND

Clinical use of breast cancer risk prediction requires simplified models. We evaluate a simplified version of the validated Rosner-Colditz model and add percent mammographic density (MD) and polygenic risk score (PRS), to assess performance from ages 45-74. We validate using the Mayo Mammography Health Study (MMHS).

METHODS

We derived the model in the Nurses' Health Study (NHS) based on: MD, 77 SNP PRS and a questionnaire score (QS; lifestyle and reproductive factors). A total of 2,799 invasive breast cancer cases were diagnosed from 1990-2000. MD (using Cumulus software) and PRS were assessed in a nested case-control study. We assess model performance using this case-control dataset and evaluate 10-year absolute breast cancer risk. The prospective MMHS validation dataset includes 21.8% of women age <50, and 434 incident cases identified over 10 years of follow-up.

RESULTS

In the NHS, MD has the highest odds ratio (OR) for 10-year risk prediction: OR_{per SD} = 1.48 [95% confidence interval (CI): 1.31-1.68], followed by PRS, OR_{per SD} = 1.37 (95% CI: 1.21-1.55) and QS, OR_{per SD} = 1.25 (95% CI: 1.11-1.41). In MMHS, the AUC adjusted for age + MD + QS 0.650; for age + MD + QS + PRS 0.687, and the NRI was 6% in cases and 16% in controls.

CONCLUSION

A simplified assessment of QS, MD, and PRS performs consistently to discriminate those at high 10-year breast cancer risk.

IMPACT

This simplified model provides accurate estimation of 10-year risk of invasive breast cancer that can be used in a clinical setting to identify women who may benefit from chemopreventive intervention.See related commentary by Tehranifar et al., p. 587.

Pre-Menopausal Breast Fat Density Might Predict MACE During 10 Years of Follow-Up: The BRECARD Study

OBJECTIVES

This study sought to determine whether the breast gland adipose tissue is associated with different rates of major adverse cardiac events (MACEs) in pre-menopausal women.

BACKGROUND

To our knowledge, no study investigated the impact of breast adipose tissue infiltration on MACEs in pre-menopausal women.

METHODS

Prospective multicenter cohort study conducted on pre-menopausal women >40 years of age without cardiovascular disease and breast cancer at enrollment. The study started in January 2000 and ended in January 2009, and the end of the follow-up for the evaluation of MACEs was in January 2019. Participants underwent mammography to evaluate breast density and were divided into 4 groups according to their breast density. The primary endpoint was the probability of a MACE at 10 years of follow-up in patients staged for different breast deposition/adipose tissue deposition.

RESULTS

The propensity score matching divided the baseline population of 16,763 pre-menopausal women, leaving 3,272 women according to the category of breast density from A to D. These women were assigned to 4 groups of the study according to baseline breast density. At 10 years of follow-up, we had 160 MACEs in group 1, 62 MACEs in group 2, 27 MACEs in group 3, and 16 MACEs in group 4. MACEs were predicted by the initial diagnosis of lowest breast density (hazard ratio: 3.483; 95% confidence interval: 1.476 to 8.257). Further randomized clinical trials are needed to translate the results of the present study into clinical practice. The loss of ex vivo breast density models to study the cellular/molecular pathways implied in MACE is another study limitation.

CONCLUSIONS

Among pre-menopausal women, a higher evidence of adipose tissue at the level of breast gland (lowest breast density, category A) versus higher breast density shows higher rates of MACEs. Therefore, the screening mammography could be proposed in overweight women to stage breast density and to predict MACEs. (Breast Density in Pre-menopausal Women Is Predictive of Cardiovascular Outcomes at 10 Years of Follow-Up [BRECARD]; NCT03779217).

Mammographic breast density, its changes, and breast cancer risk in premenopausal and postmenopausal women

BACKGROUND

The risk of breast cancer related to changes in breast density over time, including its regression and persistence, remains controversial. The authors investigated the relationship between breast density and its changes over time with the development of breast cancer in premenopausal and postmenopausal women.

METHODS

The current cohort study included 74,249 middle-aged Korean women (aged ≥35 years) who were free of breast cancer at baseline and who underwent repeated screening mammograms. Mammographic breast density was categorized according to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS). A dense breast was defined as heterogeneously dense or extremely dense, and changes in dense breasts between baseline and subsequent follow-up were classified as none, developed, regressed, or persistent dense breast.

RESULTS

During a median follow-up of 6.1 years (interquartile range, 4.1-8.8 years), a total of 803 incident breast cancers were identified. Baseline breast density was found to be positively associated with incident breast cancer in a dose-response manner, and this association did not significantly differ by menopausal status. The multivariable-adjusted hazard ratios (HRs) for breast cancer comparing "heterogeneously dense" and "extremely dense" categories with the nondense category were 1.96 (95% confidence interval [95% CI], 1.40-2.75) and 2.86 (95% CI, 2.04-4.01), respectively. With respect to changes in dense breasts over time, multivariable-adjusted HRs for breast cancer comparing persistent dense breast with none were 2.37 (95% CI, 1.34-4.21) in premenopausal women and 3.61 (95% CI, 1.78-7.30) in postmenopausal women.

CONCLUSIONS

Both baseline dense breasts and their persistence over time were found to be strongly associated with an increased risk of incident breast cancer in premenopausal and postmenopausal women.

LAY SUMMARY

Both baseline breast density and its changes over time were found to be independently associated with the risk of breast cancer in both premenopausal and postmenopausal women. The risk of incident breast cancer increased in women with persistent dense breasts, whereas the breast cancer risk decreased as dense breasts regressed. The findings of the current study support that both dense breasts at baseline and their persistence over time are independent risk factors for developing breast cancer.

Menopausal Transition, Body Mass Index, and Prevalence of Mammographic Dense Breasts in Middle-Aged Women

The interrelationship between menopausal stage, excessive adiposity and dense breasts remains unclear. We aimed to investigate the relationship between menopausal stage and dense-breast prevalence in midlife women while considering a possible effect modification of being overweight. The present cross-sectional study comprised 82,677 Korean women, aged 35–65 years, who attended a screening exam. Menopausal stages were categorized based on the Stages of Reproductive Aging Workshop (STRAW + 10) criteria. Mammographic breast density was categorized according to Breast Imaging Reporting and Data System (BI-RADS). Dense breasts were defined as BI-RADS Breast Density category D (extremely dense). The prevalence of dense breasts decreased as menopausal stage increased (p-trend < 0.001), and this pattern was pronounced in overweight women than non-overweight women (p-interaction = 0.016). Compared with pre-menopause, the multivariable-adjusted prevalence ratios (and 95% confidence intervals) for dense breasts were 0.98 (0.96–1.00) in early transition, 0.89 (0.86–0.92) in late transition, and 0.55 (0.52–0.59) in post-menopause, among non-overweight women, while corresponding prevalence ratios were 0.92 (0.87–0.98), 0.83 (0.77–0.90) and 0.36 (0.31–0.41) among overweight women. The prevalence of dense breasts was inversely associated with increasing menopausal stages and significantly decreased from the late menopausal transition, with stronger declines among overweight women.

The Relationship Between Breast Density, Bone Mineral Density, and Metabolic Syndrome Among Postmenopausal Turkish Women

The relationship between metabolic syndrome (MetS) and menopause remains unclear. The effects of MetS on breast and bone density in this group of women are also not fully elucidated. Herein, we aimed to investigate the relationship between components of the MetS, mammographic breast density (MBD), and vertebral/femoral bone mineral density (BMD) in postmenopausal Turkish women. The study group consisted of postmenopausal women with MetS whereas controls postmenopausal women without MetS. All consecutive women who applied to our center for routine postmenopausal follow up and met the inclusion criteria, between July 2013 and October 2015 were included in the study. Menopause was defined as the cessation of menstruation for at least 1 year, and we used the definition of the MetS suggested by a joint interim statement. BMD of the spine and femur was measured by dual energy X-ray absorptiometry. The medical records of 390 postmenopausal were retrospectively reviewed. No significant differences were observed between the groups in terms of age, menopause type, and menopause duration (p > 0.05). Decreased MBD (for grade 1-2 and 3-4 densities) was associated with increased MetS risk (p = 0.017). Total femoral BMD, total lumber BMD, femoral neck BMD were significantly higher in postmenopausal women with MetS (p < 0,005). This study is the first report focusing on the relationship between MetS and breast/bone density. According to the results of our study, the presence of MetS in postmenopausal periods has a positive effect on both MBD and BMD.

Mammographic density changes during neoadjuvant breast cancer treatment: NeoDense, a prospective study in Sweden

OBJECTIVES

To assess if mammographic density (MD) changes during neoadjuvant breast cancer treatment and is predictive of a pathological complete response (pCR).

METHODS

We prospectively included 200 breast cancer patients assigned to neoadjuvant chemotherapy (NACT) in the NeoDense study (2014-2019). Raw data mammograms were used to assess MD with a fully automated volumetric method and radiologists categorized MD using the Breast Imaging-Reporting and Data System (BI-RADS), 5th Edition. Logistic regression was used to calculate odds ratios (OR) for pCR comparing BI-RADS categories c vs. a, b, and d as well as with a 0.5% change in percent dense volume adjusting for baseline characteristics.

RESULTS

The overall median age was 53.1 years, and 48% of study participants were premenopausal pre-NACT. A total of 23% (N = 45) of the patients accomplished pCR following NACT. Patients with very dense breasts (BI-RADS d) were more likely to have a positive axillary lymph node status at diagnosis: 89% of the patients with very dense breasts compared to 72% in the entire cohort. A total of 74% of patients decreased their absolute dense volume during NACT. The likelihood of accomplishing pCR following NACT was independent of volumetric MD at diagnosis and change in volumetric MD during treatment. No trend was observed between decreasing density according to BI-RADS and the likelihood of accomplishing pCR following NACT.

CONCLUSIONS

The majority of patients decreased their MD during NACT. We found no evidence of MD as a predictive marker of pCR in the neoadjuvant setting.

Heterogenous Effect of Risk Factors on Breast Cancer across the Breast Density Categories in a Korean Screening Population

We evaluated the heterogeneity of the effect of known risk factors on breast cancer development based on breast density by using the Breast Imaging-Reporting and Data System (BI-RADS). In total, 4,898,880 women, aged 40-74 years, who participated in the national breast cancer screening program in 2009-2010 were followed up to December 2018. Increased age showed a heterogeneous association with breast cancer (1-year hazard ratio (HR) = 0.92, 1.00 (reference), 1.03, and 1.03 in women with BI-RADS density category 1, 2, 3, and 4, respectively; P-heterogeneity < 0.001). More advanced age at menopause increased breast cancer risk in all BI-RADS categories. This was more prominent in women with BI-RADS density category 1 but less prominent in women in other BI-RADS categories (P-heterogeneity = 0.009). In postmenopausal women, a family history of breast cancer, body mass index ≥ 25 kg/m², and smoking showed a heterogeneous association with breast cancer across all BI-RADS categories. Other risk factors including age at menarche, menopause, hormone replacement therapy after menopause, oral contraceptive use, and alcohol consumption did not show a heterogeneous association with breast cancer across the BI-RADS categories. Several known risk factors of breast cancer had a heterogeneous effect on breast cancer development across breast density categories, especially in postmenopausal women.

Alcohol and Tobacco Use in Relation to Mammographic Density in 23,456 Women

BACKGROUND

Percent density (PD) is a strong risk factor for breast cancer that is potentially modifiable by lifestyle factors. PD is a composite of the dense (DA) and nondense (NDA) areas of a mammogram, representing predominantly fibroglandular or fatty tissues, respectively. Alcohol and tobacco use have been associated with increased breast cancer risk. However, their effects on mammographic density (MD) phenotypes are poorly understood.

METHODS

We examined associations of alcohol and tobacco use with PD, DA, and NDA in a population-based cohort of 23,456 women screened using full-field digital mammography machines manufactured by Hologic or General Electric. MD was measured using Cumulus. Machine-specific effects were estimated using linear regression, and combined using random effects meta-analysis.

RESULTS

Alcohol use was positively associated with PD (P trend = 0.01), unassociated with DA (P trend = 0.23), and inversely associated with NDA (P trend = 0.02) adjusting for age, body mass index, reproductive factors, physical activity, and family history of breast cancer. In contrast, tobacco use was inversely associated with PD (P trend = 0.0008), unassociated with DA (P trend = 0.93), and positively associated with NDA (P trend<0.0001). These trends were stronger in normal and overweight women than in obese women.

CONCLUSIONS

These findings suggest that associations of alcohol and tobacco use with PD result more from their associations with NDA than DA.

IMPACT

PD and NDA may mediate the association of alcohol drinking, but not tobacco smoking, with increased breast cancer risk. Further studies are needed to elucidate the modifiable lifestyle factors that influence breast tissue composition, and the important role of the fatty tissues on breast health.

Comparison of Qualitative and Volumetric Assessments of Breast Density and Analyses of Breast Compression Parameters and Breast Volume of Women in Bahcesehir Mammography Screening Project

Objective

We aimed to compare visual and quantitative measurements of breast density and to reveal the density profile with compression characteristics.

Materials and Methods

Screening mammograms of 1399 women between May 2014 and May 2015 were evaluated by using Volpara 4^th and 5^th version. First 379 mammograms were assessed according to ACR BI-RADS 4^th edition and compared to Volpara. We categorized the breast density in two subgroups as dens or non-dens. Two radiologists reviewed the images in consensus. Agreement level between visual and volumetric methods and volumetric methods between themselves assessed using weighted kappa statistics. Volpara data such as fibroglandular volume (FGV), breast volume (BV), compression thickness (CT), compression force (CF), compression pressure (CP) were also analyzed with relation to the age.

Results

1399 mammograms were distributed as follows: 12.7% VDG1, 39.3% VDG2, 34.1% VDG3, 13.9% VDG4 according to the 4th edition of Volpara; 1.2% VDG1, 46% VDG2, 36.8% VDG3, 15.9% VDG4 according to the 5^th edition of Volpara. The difference between two editions was 4.7% increase in dense category. 379 mammograms, according to ACR BI-RADS 4^th edition, were distributed as follows: 25.9% category A, 50.9% category B, 19.8% category C, 3.4% category D. The strength of agreement between the Volpara 4^th and 5^th editions was found substantial (k=0.726). The agreements between visual assessment and both Volpara editions were poor (k=-0.413, k=-0.399 respectively). There was a 142% increase in dense group with the VDG 4^th edition and 162% with the VDG 5^th edition when compared to visual assessment. Compression force decreased while compression pressure increased with increasing Volpara Density Grade (VDG) (p for trend <0.001 for both). Compression thickness and breast volume decreased with increasing VDG (p for trend <0.001 for both). The FGV decreases with age and the breast volume increases with increasing age (p<0.001).

Conclusion

Visual assessment of breast density doesn't correlate well with volumetric assessments. Obtaining additional information about physical parameters and breast profile by the results of quantified methods is important for breast cancer risk assessments and prevention strategies.

Immigration history, lifestyle characteristics, and breast density in the Vietnamese American Women's Health Study: a cross-sectional analysis

PURPOSE

Breast density is an important risk factor for breast cancer and varies substantially across racial-ethnic groups. However, determinants of breast density in Vietnamese immigrants in the United States (US) have not been studied. We investigated whether reproductive factors, immigration history, and other demographic and lifestyle factors were associated with breast density in Vietnamese Americans.

METHODS

We collected information on demographics, immigration history, and other lifestyle factors and mammogram reports from a convenience sample of 380 Vietnamese American women in California aged 40 to 70 years. Breast Imaging Reporting and Data System (BI-RADS) breast density was abstracted from mammogram reports. Multivariable logistic regression was used to investigate the association between lifestyle factors and having dense breasts (BI-RADS 3 or 4).

RESULTS

All participants were born in Viet Nam and 82% had lived in the US for 10 years or longer. Younger age, lower body mass index, nulliparity/lower number of deliveries, and longer US residence (or younger age at migration) were associated with having dense breasts. Compared to women who migrated at age 40 or later, the odds ratios and 95% confidence intervals for having dense breasts among women who migrated between the ages of 30 and 39 and before age 30 were 1.72 (0.96-3.07) and 2.48 (1.43-4.32), respectively.

CONCLUSIONS

Longer US residence and younger age at migration were associated with greater breast density in Vietnamese American women. Identifying modifiable mediating factors to reduce lifestyle changes that adversely impact breast density in this traditionally low-risk population for breast cancer is warranted.

The relationship between breast size and aspects of health and psychological wellbeing in mature-aged women

OBJECTIVES

Increases in breast size with age are common but have not been widely examined as a factor that could affect the health and psychological wellbeing of mature-aged women. The purpose of this study was to examine the relationships between breast size and aspects of health and psychological wellbeing in mature-aged women.

METHODS

This was a cross-sectional study of mature-aged women (⩾40 years). Breast size (breast size score) was determined from self-reported bra size and was examined against health-related quality of life (Medical Outcomes Study Short-Form 36 and BREAST-Q), body satisfaction (numerical rating scale), breast satisfaction (BREAST-Q), physical activity levels (Human Activity Profile), the presence of upper back pain and breast and bra fit perceptions.

RESULTS

Two hundred sixty-nine women (40-85 years) with bra band sizes ranging from 8 to 26 and bra cup sizes from A to HH participated. The mean (standard deviation) breast size score of 7.7 (2.7) was equivalent to a bra size of 14DD. Increasing breast size was associated with significantly lower breast-related physical wellbeing (p < 0.001, R2 = 0.043) and lower ratings of body (p = 0.002, R2 = 0.024) and breast satisfaction (p < 0.001, R2 = 0.065). Women with larger breasts were more likely to be embarrassed by their breasts (odds ratio: 1.49, 95% confidence interval: 1.31 to 1.70); more likely to desire a change in their breasts (odds ratio: 1.55, 95% confidence interval: 1.37 to 1.75) and less likely to be satisfied with their bra fit (odds ratio: 0.84, 95% confidence interval: 0.76 to 0.92). Breast size in addition to age contributed to explaining upper back pain. For each one-size increase in breast size score, women were 13% more likely to report the presence of upper back pain.

CONCLUSION

Larger breast sizes have a small but significant negative relationship with breast-related physical wellbeing, body and breast satisfaction. Larger breasts are associated with a greater likelihood of upper back pain. Clinicians considering ways to improve the health and psychological wellbeing of mature-aged women should be aware of these relationships.

Mammographic Breast Density Assessed with Fully Automated Method and its Risk for Breast Cancer

Objectives:

We evaluated the association between breast cancer and breast density (BD) measured using fully automated software. We also evaluated the performance of cancer risk models such as only clinical risk factors, density related measures, and both clinical risk factors and density-related measures for determining cancer risk.

Materials and Methods:

This is a retrospective case–control study. The data were collected from August 2015 to December 2018. Two hundred fifty women with breast cancer and 400 control subjects were included in this study. We evaluated the BD qualitatively using breast imaging-reporting and data system density and quantitatively using 3D slicer. We also collected clinical factors such as age, familial history of breast cancer, menopausal status, number of births, body mass index, and hormonal replacement therapy use. We calculated the odds ratio (OR) for BD to determine the risk of breast cancer. We performed receiver operating characteristic (ROC) curve to assess the performance of cancer risk models.

Results:

The OR for the percentage BD for second, third, and fourth quartiles was 1.632 (95% confidence intervals [CI]: 1.102–2.416), 2.756 (95% CI: 1.704–4.458), and 3.163 (95% CI: 1.356–5.61). The area under ROC curve for clinical risk factors only, mammographic density measures, combined mammographic, and clinical risk factors was 0.578 (95% CI: 0.45, 0.64), 0.684 (95% CI: 0.58, 0.75), and 0.724 (95% CI: 0.64, 0.80), respectively.

Conclusion:

Mammographic BD was found to be positively associated with breast cancer. The density related measures combined clinical risk factors, and density model had good discriminatory power in identifying the cancer risk.

Global parenchymal texture features based on histograms of oriented gradients improve cancer development risk estimation from healthy breasts

BACKGROUND

The breast dense tissue percentage on digital mammograms is one of the most commonly used markers for breast cancer risk estimation. Geometric features of dense tissue over the breast and the presence of texture structures contained in sliding windows that scan the mammograms may improve the predictive ability when combined with the breast dense tissue percentage.

METHODS

A case/control study nested within a screening program covering 1563 women with craniocaudal and mediolateral-oblique mammograms (755 controls and the contralateral breast mammograms at the closest screening visit before cancer diagnostic for 808 cases) aging 45 to 70 from Comunitat Valenciana (Spain) was used to extract geometric and texture features. The dense tissue segmentation was performed using DMScan and validated by two experienced radiologists. A model based on Random Forests was trained several times varying the set of variables. A training dataset of 1172 patients was evaluated with a 10-stratified-fold cross-validation scheme. The area under the Receiver Operating Characteristic curve (AUC) was the metric for the predictive ability. The results were assessed by only considering the output after applying the model to the test set, which was composed of the remaining 391 patients.

RESULTS

The AUC score obtained by the dense tissue percentage (0.55) was compared to a machine learning-based classifier results. The classifier, apart from the percentage of dense tissue of both views, firstly included global geometric features such as the distance of dense tissue to the pectoral muscle, dense tissue eccentricity or the dense tissue perimeter, obtaining an accuracy of 0.56. By the inclusion of a global feature based on local histograms of oriented gradients, the accuracy of the classifier was significantly improved (0.61). The number of well-classified patients was improved up to 236 when it was 208.

CONCLUSION

Relative geometric features of dense tissue over the breast and histograms of standardized local texture features based on sliding windows scanning the whole breast improve risk prediction beyond the dense tissue percentage adjusted by geometrical variables. Other classifiers could improve the results obtained by the conventional Random Forests used in this study.

Long-term excess risk of breast cancer after a single breast density measurement

AIM

Breast density is a risk factor for breast cancer. As density changes across a woman's life span, we studied for how long a single density measurement taken in (post-)menopausal women remains informative.

METHODS

We used data from Singaporean women who underwent a single mammography screen at age 50-64 years. For each case with breast cancer diagnosed at screening or in the subsequent 10 years, whether screen detected or diagnosed following symptoms, two age-matched controls were selected. We studied the excess risk of breast cancer, calculated as an odds ratio (OR) with conditional logistic regression and adjusted for body mass index, associated with 26-50% and with 51-100% density compared with ≤25% density by time since screening.

RESULTS

In total, 490 women had breast cancer, of which 361 were diagnosed because of symptoms after screening. Women with 51-100% breast density had an excess risk of breast cancer that did not seem to attenuate with time. In 1-3 years after screening, the OR was 2.22 (95% confidence interval [CI]: 1.07-4.61); in 4-6 years after screening, the OR was 4.09 (95% CI: 2.21-7.58), and in 7-10 years after screening, the OR was 5.35 (95% CI: 2.57-11.15). Excess risk with a stable OR of about 2 was also observed for women with 26-50% breast density. These patterns were robust when the analyses were limited to post-menopausal women, non-users of hormonal replacement therapy and after stratification by age at density measurement.

CONCLUSION

A single breast density measurement identifies women with an excess risk of breast cancer during at least the subsequent 10 years.

Longitudinal Changes in Volumetric Breast Density in Healthy Women across the Menopausal Transition

BACKGROUND

Mammographic breast density declines during menopause. We assessed changes in volumetric breast density across the menopausal transition and factors that influence these changes.

METHODS

Women without a history of breast cancer, who had full field digital mammograms during both pre- and postmenopausal periods, at least 2 years apart, were sampled from four facilities within the San Francisco Mammography Registry from 2007 to 2013. Dense breast volume (DV) was assessed using Volpara on mammograms across the time period. Annualized change in DV from pre- to postmenopause was estimated using linear mixed models adjusted for covariates and per-woman random effects. Multiplicative interactions were evaluated between premenopausal risk factors and time to determine whether these covariates modified the annualized changes.

RESULTS

Among the 2,586 eligible women, 1,802 had one premenopausal and one postmenopausal mammogram, 628 had an additional perimenopausal mammogram, and 156 had two perimenopausal mammograms. Women experienced an annualized decrease in DV [-2.2 cm³ (95% confidence interval, -2.7 to -1.7)] over the menopausal transition. Declines were greater among women with a premenopausal DV above the median (54 cm³) versus below (DV, -3.5 cm³ vs. -1.0 cm³; P < 0.0001). Other breast cancer risk factors, including race, body mass index, family history, alcohol, and postmenopausal hormone therapy, had no effect on change in DV over the menopausal transition.

CONCLUSIONS

High premenopausal DV was a strong predictor of greater reductions in DV across the menopausal transition.

IMPACT

We found that few factors other than premenopausal density influence changes in DV across the menopausal transition, limiting targeted prevention efforts.

Reproductive Factors and Mammographic Density: Associations Among 24,840 Women and Comparison of Studies Using Digitized Film-Screen Mammography and Full-Field Digital Mammography

Breast density is a modifiable factor that is strongly associated with breast cancer risk. We sought to understand the influence of newer technologies of full-field digital mammography (FFDM) on breast density research and to determine whether results are comparable across studies using FFDM and previous studies using traditional film-screen mammography. We studied 24,840 screening-age (40-74 years) non-Hispanic white women who were participants in the Research Program on Genes, Environment and Health of Kaiser Permanente Northern California and underwent screening mammography with either Hologic (Hologic, Inc., Marlborough, Massachusetts) or General Electric (General Electric Company, Boston, Massachusetts) FFDM machines between 2003 and 2013. We estimated the associations of parity, age at first birth, age at menarche, and menopausal status with percent density and dense area as measured by a single radiological technologist using Cumulus software (Canto Software, Inc., San Francisco, California). We found that associations between reproductive factors and mammographic density measured using processed FFDM images were generally similar in magnitude and direction to those from prior studies using film mammography. Estimated associations for both types of FFDM machines were in the same direction. There was some evidence of heterogeneity in the magnitude of the effect sizes by machine type, which we accounted for using random-effects meta-analysis when combining results. Our findings demonstrate the robustness of quantitative mammographic density measurements across FFDM and film mammography platforms.

The association between mammographic density and breast cancer risk in Western Australian Aboriginal women

PURPOSE

Mammographic density is an established breast cancer risk factor within many ethnically different populations. The distribution of mammographic density has been shown to be significantly lower in Western Australian Aboriginal women compared to age- and screening location-matched non-Aboriginal women. Whether mammographic density is a predictor of breast cancer risk in Aboriginal women is unknown.

METHODS

We measured mammographic density from 103 Aboriginal breast cancer cases and 327 Aboriginal controls, 341 non-Aboriginal cases, and 333 non-Aboriginal controls selected from the BreastScreen Western Australia database using the Cumulus software program. Logistic regression was used to examine the associations of percentage dense area and absolute dense area with breast cancer risk for Aboriginal and non-Aboriginal women separately, adjusting for covariates.

RESULTS

Both percentage density and absolute dense area were strongly predictive of risk in Aboriginal women with odds per adjusted standard deviation (OPERAS) of 1.36 (95% CI 1.09, 1.69) and 1.36 (95% CI 1.08, 1.71), respectively. For non-Aboriginal women, the OPERAS were 1.22 (95% CI 1.03, 1.46) and 1.26 (95% CI 1.05, 1.50), respectively.

CONCLUSIONS

Whilst mean mammographic density for Aboriginal women is lower than non-Aboriginal women, density measures are still higher in Aboriginal women with breast cancer compared to Aboriginal women without breast cancer. Thus, mammographic density strongly predicts breast cancer risk in Aboriginal women. Future efforts to predict breast cancer risk using mammographic density or standardize risk-associated mammographic density measures should take into account Aboriginal status when applicable.

Mammographic densities of Aboriginal and non-Aboriginal women living in Australia's Northern Territory

OBJECTIVES

To compare the mammographic densities and other characteristics of Aboriginal and non-Aboriginal women screened in Australia.

METHODS

Population screening programme data of Aboriginal (n = 857) and non-Aboriginal women (n = 3236) were used. Mann-Whitney U test compared ages at screening and Chi-square tests compared personal and clinical information. Logistic regression analysis was used for density groupings. OR and 95% CI were calculated for multivariate association for density.

RESULTS

Mammographic density was lower amongst Aboriginal women (P < 0.001). For non-Aboriginal women, higher density was associated with younger age (OR 2.4, 95% CI 2.1-2.8), recall to assessment (OR 2.2, 95% CI 1.6-3.0), family history of breast cancer (OR 1.4, 95% CI 1.2-1.6), English-speaking background (OR 1.4, 95% CI 1.2-1.6), and residence in remote areas (OR 1.2, 95% CI 1.1-1.4). For Aboriginal women, density was associated with younger age (OR 2.7, 95% CI 2.0-3.5; P < 0.001), and recall to assessment (OR 2.3, 95% CI 1.4-3.9; P < 0.05).

CONCLUSIONS

Significant differences between Aboriginal and non-Aboriginal women were found. There were more significant associations for dense breasts for non-Aboriginal women than for Aboriginal women.

Characteristics of Mammographic Breast Density and Associated Factors for Chinese Women: Results from an Automated Measurement

Background

Characteristics of mammographic density for Chinese women are understudied. This study aims to identify factors associated with mammographic density in China using a quantitative method.

Methods

Mammographic density was measured for a total of 1071 (84 with and 987 without breast cancer) women using an automatic algorithm AutoDensity. Pearson tests examined relationships between density and continuous variables and t-tests compared differences of mean density values between groupings of categorical variables. Linear models were built using multiple regression.

Results

Percentage density and dense area were positively associated with each other for cancer-free (r=0.487, p<0.001) and cancer groups (r=0.446, p<0.001), respectively. For women without breast cancer, weight and BMI (p<0.001) were found to be negatively associated (r=-0.237, r=-0.272) with percentage density whereas they were found to be positively associated (r=0.110, r=0.099) with dense area; age at mammography was found to be associated with percentage density (r=-0.202, p<0.001) and dense area (r=-0.086, p<0.001) but did not add any prediction within multivariate models; lower percentage density was found within women with secondary education background or below compared to women with tertiary education. For women with breast cancer, percentage density demonstrated similar relationships with that of cancer-free women whilst breast area was the only factor associated with dense area (r=0.739, p<0.001).

Conclusion

This is the first time that mammographic density was measured by a quantitative method for women in China and identified associations should be useful to health policy makers who are responsible for introducing effective models of breast cancer prevention and diagnosis.

The distribution and determinants of mammographic density measures in Western Australian aboriginal women

Background

Mammographic density (MD) is an established risk factor for breast cancer. There are significant ethnic differences in MD measures which are consistent with those for corresponding breast cancer risk. This is the first study investigating the distribution and determinants of MD measures within Aboriginal women of Western Australia (WA).

Methods

Epidemiological data and mammographic images were obtained from 628 Aboriginal women and 624 age-, year of screen-, and screening location-matched non-Aboriginal women randomly selected from the BreastScreen Western Australia database. Women were cancer free at the time of their mammogram between 1989 and 2014. MD was measured using the Cumulus software. Kolmogorov-Smirnov tests were used to compare distributions of absolute dense area (DA), precent dense area (PDA), non-dense area (NDA) and total breast area between Aboriginal and non-Aboriginal women. General linear regression was used to estimate the determinants of MD, adjusting for age, NDA, hormone therapy use, family history, measures of socio-economic status and remoteness of residence for Aboriginal and non-Aboriginal women separately.

Results

Aboriginal women were found to have lower DA and PDA and higher NDA than non-Aboriginal women. Age (p <  0.001) was negatively associated and several socio-economic indices (p <  0.001) were positively associated with DA and PDA in Aboriginal and non-Aboriginal women. Remoteness of residence was associated with both mammographic measures but for non-Aboriginal women only.

Conclusions

Aboriginal women have, on average, less MD than non-Aboriginal women but the factors associated with MD are similar for both sample populations. Since reduced MD is associated with improved sensitivity of mammography, this study suggests that mammographic screening is a particularly good test for Australian Indigenous women, a population that suffers from high breast cancer mortality.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1113-4) contains supplementary material, which is available to authorized users.

Change in mammographic density across birth cohorts of Dutch breast cancer screening participants

High mammographic density is a well‐known risk factor for breast cancer. This study aimed to search for a possible birth cohort effect on mammographic density, which might contribute to explain the increasing breast cancer incidence. We separately analyzed left and right breast density of Dutch women from a 13‐year period (2003–2016) in the breast cancer screening programme. First, we analyzed age‐specific changes in average percent dense volume (PDV) across birth cohorts. A linear regression analysis (PDV vs. year of birth) indicated a small but statistically significant increase in women of: 1) age 50 and born from 1952 to 1966 (left, slope = 0.04, p = 0.003; right, slope = 0.09, p < 0.0001); 2) age 55 and born from 1948 to 1961 (right, slope = 0.04, p = 0.01); and 3) age 70 and born from 1933 to 1946 (right, slope = 0.05, p = 0.002). A decrease of total breast volume seemed to explain the increase in PDV. Second, we compared proportion of women with dense breast in women born in 1946–1953 and 1959–1966, and observed a statistical significant increase of proportion of highly dense breast in later born women, in the 51 to 55 age‐groups for the left breast (around a 20% increase in each age‐group), and in the 50 to 56 age‐groups for the right breast (increase ranging from 27% to 48%). The study indicated a slight increase in mammography density across birth cohorts, most pronounced for women in their early 50s, and more marked for the right than for the left breast.

What's new?

Women with dense breast tissue are at increased risk of breast cancer. Here, changes in mammographic density were investigated across birth cohorts in women enrolled in a breast cancer screening program in the Netherlands. The findings reveal an increase in the average fraction of dense tissue in the breast across cohorts. In particular, greater breast density was observed in a higher proportion of women in later‐born than earlier‐born birth cohorts. The increase was most significant among women in their early 50s and may be linked to a reported shift toward older age at menopause among women in Europe.

Adjuvant Therapy and Mammographic Density Changes in Women With Breast Cancer

Background

Tamoxifen decreases mammographic density. Whether compliance affects this relationship is unclear as is the relationship between other types of adjuvant treatment and changes in mammographic density.

Methods

This prospective cohort study included 2490 women diagnosed with breast cancer during 2001-2015 in Sweden. Mammographic density was assessed within 3 months of diagnosis and 6-36 months post diagnosis. Logistic regression was performed to study the association between each respective adjuvant treatment and mammographic density reduction (annual dense area decrease >15%).

Results

Intention-to-treat analyses using treatment information from the regional cancer registries showed that tamoxifen-treated patients more frequently experienced mammographic density reductions compared with nontreated patients (odds ratio [OR] = 1.58, 95% confidence interval [CI] = 1.25 to 1.99), as did chemotherapy-treated patients (OR = 1.28, 95% CI = 1.06 to 1.54). For chemotherapy, the association was mainly seen in premenopausal women. Neither aromatase inhibitors nor radiotherapy was associated with density change. Tamoxifen use based on prescription and dispensation data from the Swedish Prescribed Drug Register showed that users were more likely to have density reductions compared with nonusers (adjusted OR = 2.24, 95% CI = 1.40 to 3.59). Moreover, among tamoxifen users, tamoxifen continuers were more likely than discontinuers to experience density reductions (adjusted OR = 1.50, 95% CI = 1.04 to 2.17).

Conclusions

Our results indicate that adherence influences the association between tamoxifen and mammographic density reduction. We further found that chemotherapy was associated with density reductions and propose that this is largely secondary to chemotherapy-induced ovarian failure.

Circulating Growth and Sex Hormone Levels and Breast Tissue Composition in Young Nulliparous Women

BACKGROUND

Endogenous hormones are associated with breast cancer risk, but little is known about their role on breast tissue composition, a strong risk predictor. This study aims to investigate the relationship between growth and sex hormone levels and breast tissue composition in young nulliparous women.

METHODS

A cross-sectional study of 415 young (age ∼21.5 years) nulliparous women from an English prebirth cohort underwent a MRI examination of their breasts to estimate percent-water (a proxy for mammographic percent density) and provided a blood sample to measure plasma levels of growth factors (insulin-like growth factor-I, insulin-like growth factor-II, insulin growth factor-binding protein-3, growth hormone) and, if not on hormonal contraception (n = 117) sex hormones (dehydroepiandrosterone, androstenedione, testosterone, estrone, estadiol, sex hormone-binding globulin, prolactin). Testosterone (n = 330) and sex hormone-binding globulin (n = 318) were also measured at age 15.5 years. Regression models were used to estimate the relative difference (RD) in percent-water associated with one SD increment in hormone levels.

RESULTS

Estradiol at age 21.5 and sex hormone-binding globulin at age 21.5 were positively associated with body mass index (BMI)-adjusted percent-water [RD (95% confidence interval (CI)): 3% (0%-7%) and 3% (1%-5%), respectively]. There was a positive nonlinear association between androstenedione at age 21.5 and percent-water. Insulin-like growth factor-I and growth hormone at age 21.5 were also positively associated with BMI-adjusted percent-water [RD (95% CI): 2% (0%-4%) and 4% (1%-7%), respectively].

CONCLUSIONS

The findings suggest that endogenous hormones affect breast tissue composition in young nulliparous women.

IMPACT

The well-established associations of childhood growth and development with breast cancer risk may be partly mediated by the role of endogenous hormones on breast tissue composition.

Growth factor genes and change in mammographic density after stopping combined hormone therapy in the California Teachers Study

Background

The contribution of genetic polymorphisms to the large inter-individual variation in mammographic density (MD) changes following starting and stopping use of estrogen and progestin combined therapy (EPT) has not been well-studied. Previous studies have shown that circulating levels of insulin-like growth factors are associated with MD and cross-talk between estrogen signaling and growth factors is necessary for cell proliferation in the breast. We evaluated single nucleotide polymorphisms (SNPs) in growth factor genes in association with MD changes after women stop EPT use.

Methods

We genotyped 191 SNPs in 13 growth factor pathway genes in 284 non-Hispanic white California Teachers Study participants who previously used EPT and collected their mammograms before and after quitting EPT. Percent MD was assessed using a computer-assisted method. Change in percent MD was calculated by subtracting percent MD of an ‘off-EPT’ mammogram from percent MD of an ‘on-EPT’ (i.e. baseline) mammogram. We used multivariable linear regression analysis to investigate the association between SNPs and change in percent MD. We calculated P-values corrected for multiple testing within a gene (P_adj).

Results

Rs1983210 in INHA and rs35539615 in IGFBP1/3 showed the strongest associations. Per minor allele of rs1983210, the absolute change in percent MD after stopping EPT use decreased by 1.80% (a difference in absolute change in percent MD) (P_adj= 0.021). For rs35539615, change in percent MD increased by 1.79% per minor allele (P_adj= 0.042). However, after applying a Bonferroni correction for the number of genes tested, these associations were no longer statistically significant.

Conclusions

Genetic variation in growth factor pathway genes INHA and IGFBP1/3 may predict longitudinal MD change after women quit EPT. The observed differences in EPT-associated changes in percent MD in association with these genetic polymorphisms are modest but may be clinically significant considering that the magnitude of absolute increase in percent MD reported from large clinical trials of EPT ranged from 3% to 7%.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4981-6) contains supplementary material, which is available to authorized users.

Mammographic Density Distribution of Healthy Taiwanese Women and its Naturally Decreasing Trend with Age

We analysed typical mammographic density (MD) distributions of healthy Taiwanese women to augment existing knowledge, clarify cancer risks, and focus public health efforts. From January 2011 to December 2015, 88,193 digital mammograms were obtained from 69,330 healthy Taiwanese women (average, 1.27 mammograms each). MD measurements included dense volume (DV) and volumetric density percentage (VPD) and were quantified by fully automated volumetric density estimation and Box-Cox normalization. Prediction of the declining MD trend was estimated using curve fitting and a rational model. Normalized DV and VPD Lowess curves demonstrated similar but non-identical distributions. In high-density grade participants, the VPD increased from 12.45% in the 35-39-year group to 13.29% in the 65-69-year group but only from 5.21% to 8.47% in low-density participants. Regarding the decreased cumulative VPD percentage, the mean MD declined from 12.79% to 19.31% in the 45-50-year group versus the 50-55-year group. The large MD decrease in the fifth decade in this present study was similar to previous observations of Western women. Obtaining an MD distribution model with age improves the understanding of breast density trends and age variations and provides a reference for future studies on associations between MD and cancer risk.

Determination of mammographic breast density using a deep convolutional neural network

OBJECTIVE

High breast density is a risk factor for breast cancer. The aim of this study was to develop a deep convolutional neural network (dCNN) for the automatic classification of breast density based on the mammographic appearance of the tissue according to the American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) Atlas.

METHODS

In this study, 20,578 mammography single views from 5221 different patients (58.3 ± 11.5 years) were downloaded from the picture archiving and communications system of our institution and automatically sorted according to the ACR density (a-d) provided by the corresponding radiological reports. A dCNN with 11 convolutional layers and 3 fully connected layers was trained and validated on an augmented dataset. The model was finally tested on two different datasets against: i) the radiological reports and ii) the consensus decision of two human readers. None of the test datasets was part of the dataset used for the training and validation of the algorithm.

RESULTS

The optimal number of epochs was 91 for medio-lateral oblique (MLO) projections and 94 for cranio-caudal projections (CC), respectively. Accuracy for MLO projections obtained on the validation dataset was 90.9% (CC: 90.1%). Tested on the first test dataset of mammographies (850 MLO and 880 CC), the algorithm showed an accordance with the corresponding radiological reports of 71.7% for MLO and of 71.0% for CC. The agreement with the radiological reports improved in the differentiation between dense and fatty breast for both projections (MLO = 88.6% and CC = 89.9%). In the second test dataset of 200 mammographies, a good accordance was found between the consensus decision of the two readers on both, the MLO-model (92.2%) and the right craniocaudal-model (87.4%). In the differentiation between fatty (ACR A/B) and dense breasts (ACR C/D), the agreement reached 99% for the MLO and 96% for the CC projections, respectively.

CONCLUSIONS

The dCNN allows for accurate classification of breast density based on the ACR BI-RADS system. The proposed technique may allow accurate, standardized, and observer independent breast density evaluation of mammographies.

ADVANCES IN KNOWLEDGE

Standardized classification of mammographies by a dCNN could lead to a reduction of falsely classified breast densities, thereby allowing for a more accurate breast cancer risk assessment for the individual patient and a more reliable decision, whether additional ultrasound is recommended.

Childhood body size and midlife mammographic breast density in foreign-born and U.S.-born women in New York City

PURPOSE

We investigated whether childhood body size is associated with midlife mammographic density, a strong risk factor for breast cancer.

METHODS

We collected interview data, including body size at age 10 years using a pictogram, and measured height and weight from 518 women, recruited at the time of screening mammography in New York City (ages 40-64 years, 71% Hispanic, 68% foreign-born). We used linear regression models to examine childhood body size in relation to percent density and areas of dense and nondense tissue, measured using a computer-assisted method from digital mammograms.

RESULTS

In models that adjusted for race/ethnicity, and age and body mass index at mammogram, the heaviest relative to leanest childhood body size was associated with 5.94% lower percent density (95% confidence interval [CI]: -9.20, -2.29), 7.69 cm² smaller dense area (95% CI: -13.94, -0.63), and 26.17 cm² larger nondense area (95% CI: 9.42, 43.58). In stratified analysis by menopausal status and nativity, the observed associations were stronger for postmenopausal and U.S.-born women although these differences did not reach statistical significance.

CONCLUSIONS

Heavy childhood body size is associated with lower mammographic density, consistent with its associations with breast cancer risk. Suggestive findings by nativity require confirmation in larger samples.

Molecular mechanisms of the preventable causes of cancer in the United States

Annually, there are 1.6 million new cases of cancer and nearly 600,000 cancer deaths in the United States alone. The public health burden associated with these numbers has motivated enormous research efforts into understanding the root causes of cancer. These efforts have led to the recognition that between 40% and 45% of cancers are associated with preventable risk factors and, importantly, have identified specific molecular mechanisms by which these exposures modify human physiology to induce or promote cancer. The increasingly refined knowledge of these mechanisms, which we summarize here, emphasizes the need for greater efforts toward primary cancer prevention through mitigation of modifiable risk factors. It also suggests exploitable avenues for improved secondary prevention (which includes the development of therapeutics designed for cancer interception and enhanced techniques for noninvasive screening and early detection) based on detailed knowledge of early neoplastic pathobiology. Such efforts would complement the current emphasis on the development of therapeutic approaches to treat established cancers and are likely to result in far greater gains in reducing morbidity and mortality.

PAM50 and Risk of Recurrence Scores for Interval Breast Cancers

Breast cancers detected after a negative breast screening examination and prior to the next screening are referred to as interval cancers. These cancers generally have poor clinical characteristics compared with screen-detected cancers, but associations between interval cancer and genomic cancer characteristics are not well understood. Mammographically screened women diagnosed with primary invasive breast cancer from 1993 to 2013 (n = 370) were identified by linking the Carolina Breast Cancer Study and the Carolina Mammography Registry. Among women with a registry-identified screening mammogram 0 to 24 months before diagnosis, cancers were classified as screen-detected (N = 165) or interval-detected (N = 205). Using logistic regression, we examined the association of mode of detection with cancer characteristics (clinical, IHC, and genomic), overall, and in analyses stratified on mammographic density and race. Interval cancer was associated with large tumors [>2 cm; OR, 2.3; 95% confidence interval (CI), 1.5-3.7], positive nodal status (OR, 1.8; 95% CI, 1.1-2.8), and triple-negative subtype (OR, 2.5; 95% CI, 1.1-5.5). Interval cancers were more likely to have non-Luminal A subtype (OR, 2.9; 95% CI, 1.5-5.7), whereas screen-detected cancers tended to be more indolent (96% had low risk of recurrence genomic scores; 71% were PAM50 Luminal A). When stratifying by mammographic density and race, associations between interval detection and poor prognostic features were similar by race and density status. Strong associations between interval cancers and poor-prognosis genomic features (non-Luminal A subtype and high risk of recurrence score) suggest that aggressive tumor biology is an important contributor to interval cancer rates. Cancer Prev Res; 11(6); 327-36. ©2018 AACR.