Body size, mammographic density, and breast cancer risk

A comparative analysis of risk factor associations with interval and screen-detected breast cancers: A large UK prospective study

The associations of certain factors, such as age and menopausal hormone therapy, with breast cancer risk are known to differ for interval and screen-detected cancers. However, the extent to which associations of other established breast cancer risk factors differ by mode of detection is unclear. We investigated associations of a wide range of risk factors using data from a large UK cohort with linkage to the National Health Service Breast Screening Programme, cancer registration, and other health records. We used Cox regression to estimate adjusted relative risks (RRs) and 95% confidence intervals (CIs) for associations between risk factors and breast cancer risk. A total of 9421 screen-detected and 5166 interval cancers were diagnosed in 517,555 women who were followed for an average of 9.72 years. We observed the following differences in risk factor associations by mode of detection: greater body mass index (BMI) was associated with a smaller increased risk of interval (RR per 5 unit increase 1.07, 95% CI 1.03-1.11) than screen-detected cancer (RR 1.27, 1.23-1.30); having a first-degree family history was associated with a greater increased risk of interval (RR 1.81, 1.68-1.95) than screen-detected cancer (RR 1.52, 1.43-1.61); and having had previous breast surgery was associated with a greater increased risk of interval (RR 1.85, 1.72-1.99) than screen-detected cancer (RR 1.34, 1.26-1.42). As these differences in associations were relatively unchanged after adjustment for tumour grade, and are in line with the effects of these factors on mammographic density, they are likely to reflect the effects of these risk factors on screening sensitivity.

Mammographic features differ with body composition in women with breast cancer

OBJECTIVES

There are several breast cancer (BC) risk factors-many related to body composition, hormonal status, and fertility patterns. However, it is not known if risk factors in healthy women are associated with specific mammographic features at the time of BC diagnosis. Our aim was to assess the potential association between pre-diagnostic body composition and mammographic features in the diagnostic BC image.

MATERIALS AND METHODS

The prospective Malmö Diet and Cancer Study includes women with invasive BC from 1991 to 2014 (n = 1116). BC risk factors at baseline were registered (anthropometric measures, menopausal status, and parity) along with mammography data from BC diagnosis (breast density, mammographic tumor appearance, and mode of detection). We investigated associations between anthropometric measures and mammographic features via logistic regression analyses, yielding odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

There was an association between high body mass index (BMI) (≥ 30) at baseline and spiculated tumor appearance (OR 1.370 (95% CI: 0.941-2.010)), primarily in women with clinically detected cancers (OR 2.240 (95% CI: 1.280-3.940)), and in postmenopausal women (OR 1.580 (95% CI: 1.030-2.440)). Furthermore, an inverse association between high BMI (≥ 30) and high breast density (OR 0.270 (95% CI: 0.166-0.438)) was found.

CONCLUSION

This study demonstrated an association between obesity and a spiculated mass on mammography-especially in women with clinically detected cancers and in postmenopausal women. These findings offer insights on the relationship between risk factors in healthy women and related mammographic features in subsequent BC.

CLINICAL RELEVANCE STATEMENT

With increasing numbers of both BC incidence and women with obesity, it is important to highlight mammographic findings in women with an unhealthy weight.

KEY POINTS

Women with obesity and BC may present with certain mammographic features. Spiculated masses were more common in women with obesity, especially postmenopausal women, and those with clinically detected BCs. Insights on the relationship between obesity and related mammographic features will aid mammographic interpretation.

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.

Reproductive risk factors for breast cancer and association with novel breast density measurements among Hispanic, Black, and White women

PURPOSE

There are differences in the distributions of breast cancer incidence and risk factors by race and ethnicity. Given the strong association between breast density and breast cancer, it is of interest describe racial and ethnic variation in the determinants of breast density.

METHODS

We characterized racial and ethnic variation in reproductive history and several measures of breast density for Hispanic (n = 286), non-Hispanic Black (n = 255), and non-Hispanic White (n = 1694) women imaged at a single hospital. We quantified associations between reproductive factors and percent volumetric density (PVD), dense volume (DV), non-dense volume (NDV), and a novel measure of pixel intensity variation (V) using multivariable-adjusted linear regression, and tested for statistical heterogeneity by race and ethnicity.

RESULTS

Reproductive factors most strongly associated with breast density were age at menarche, parity, and oral contraceptive use. Variation by race and ethnicity was most evident for the associations between reproductive factors and NDV (minimum p-heterogeneity:0.008) and V (minimum p-heterogeneity:0.004) and least evident for PVD (minimum p-heterogeneity:0.042) and DV (minimum p-heterogeneity:0.041).

CONCLUSION

Reproductive choices, particularly those related to childbearing and oral contraceptive use, may contribute to racial and ethnic variation in breast density.

Breast composition during and after puberty: the Chilean Growth and Obesity Cohort Study

BACKGROUND

Breast density (BD) is a strong risk factor for breast cancer. Little is known about how BD develops during puberty. Understanding BD trajectories during puberty and its determinants could be crucial for promoting preventive actions against breast cancer (BC) at early ages. The objective of this research is to characterize % fibroglandular volume (%FGV), absolute fibroglandular volume (AFGV), and breast volume (BV) at different breast Tanner stages until 4-year post menarche in a Latino cohort and to assess determinants of high %FGV and AFGV during puberty and in a fully mature breast.

METHODS

This is a longitudinal follow-up of 509 girls from low-middle socioeconomic status of the Southeast area of Santiago, recruited at a mean age of 3.5 years. The inclusion criteria were singleton birth born, birthweight between 2500 and 4500 g with no medical or mental disorder. A trained dietitian measured weight and height since 3.5 years old and sexual maturation from 8 years old (breast Tanner stages and age at menarche onset). Using standardized methods, BD was measured using dual-energy X-ray absorptiometry (DXA) in various developmental periods (breast Tanner stage B1 until 4 years after menarche onset).

RESULTS

In the 509 girls, we collected 1,442 breast DXA scans; the mean age at Tanner B4 was 11.3 years. %FGV increased across breast Tanner stages and peaked 250 days after menarche. AFGV and BV peaked 2 years after menarche onset. Girls in the highest quartiles of %FGV, AFGV, and BV at Tanner B4 and B5 before menarche onset had the highest values thereafter until 4 years after menarche onset. The most important determinants of %FGV and AFGV variability were BMI z-score (R2 = 44%) and time since menarche (R2 = 42%), respectively.

CONCLUSION

We characterize the breast development during puberty, a critical window of susceptibility. Although the onset of menarche is a key milestone for breast development, we observed that girls in the highest quartiles of %FGV and AFGV tracked in that group afterwards. Following these participants in adulthood would be of interest to understand the changes in breast composition during this period and its potential link with BC risk.

Associations of Vitamins and Related Cofactor Metabolites with Mammographic Breast Density in Premenopausal Women

BACKGROUND

Identifying biological drivers of mammographic breast density (MBD), a strong risk factor for breast cancer, could provide insight into breast cancer etiology and prevention. Studies on dietary factors and MBD have yielded conflicting results. There are, however, very limited data on the associations of dietary biomarkers and MBD.

OBJECTIVE

We aimed to investigate the associations of vitamins and related cofactor metabolites with MBD in premenopausal women.

METHODS

We measured 37 vitamins and related cofactor metabolites in fasting plasma samples of 705 premenopausal women recruited during their annual screening mammogram at the Washington University School of Medicine, St. Louis, MO. Volpara was used to assess volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV). We estimated the least square means of VPD, DV, and NDV across quartiles of each metabolite, as well as the regression coefficient of a metabolite in continuous scale from multiple covariate-adjusted linear regression. We corrected for multiple testing using the Benjamini-Hochberg procedure to control the false discover rate (FDR) at a 5% level.

RESULTS

Participants' mean VPD was 10.5%. Two vitamin A metabolites (β-cryptoxanthin and carotene diol 2) were positively associated, and one vitamin E metabolite (γ-tocopherol) was inversely associated with VPD. The mean VPD increased across quartiles of β-cryptoxanthin (Q1 = 7.2%, Q2 = 7.7%, Q3 = 8.4%%, Q4 = 9.2%; P-trend = 1.77E-05, FDR P value = 1.18E-03). There was a decrease in the mean VPD across quartiles of γ-tocopherol (Q1 = 9.4%, Q2 = 8.1%, Q3 = 8.0%, Q4 = 7.8%; P -trend = 4.01E-03, FDR P value = 0.04). Seven metabolites were associated with NDV: 3 vitamin E (γ-CEHC glucuronide, δ-CEHC, and γ-tocopherol) and 1 vitamin C (gulonate) were positively associated, whereas 2 vitamin A (carotene diol 2 and β-cryptoxanthin) and 1 vitamin C (threonate) were inversely associated with NDV. No metabolite was significantly associated with DV.

CONCLUSION

We report novel associations of vitamins and related cofactor metabolites with MBD in premenopausal women.

Breast cancer risk factors and mammographic density among 12518 average-risk women in rural China

BACKGROUND

Mammographic density (MD) is a strong risk factor for breast cancer. We aimed to evaluate the association between MD and breast cancer related risk factors among average-risk women in rural China.

METHODS

This is a population-based screening study. 12518 women aged 45-64 years with complete MD data from three maternal and childcare hospitals in China were included in the final analysis. ORs and 95%CIs were estimated using generalized logit model by comparing each higher MD (BI-RADS b, c, d) to the lowest group (BI-RADS a). The cumulative logistic regression model was used to estimate the ORtrend (95%CI) and Ptrend by treating MD as an ordinal variable.

RESULTS

Older age (ORtrend = 0.81, 95%CI: 0.79-0.81, per 2-year increase), higher BMI (ORtrend = 0.73, 95%CI: 0.71-0.75, per 2 kg/m2), more births (ORtrend = 0.47, 95%CI: 0.41-0.54, 3 + vs. 0-1), postmenopausal status (ORtrend = 0.42, 95%CI: 0.38-0.46) were associated with lower MD. For parous women, longer duration of breastfeeding was found to be associated with higher MD when adjusting for study site, age, BMI, and age of first full-term birth (ORtrend = 1.53, 95%CI: 1.27-1.85, 25 + months vs. no breastfeeding; ORtrend = 1.45, 95%CI: 1.20-1.75, 19-24 months vs. no breastfeeding), however, the association became non-significant when adjusting all covariates. Associations between examined risk factors and MD were similar in premenopausal and postmenopausal women except for level of education and oral hormone drug usage. Higher education was only found to be associated with an increased proportion of dense breasts in postmenopausal women (ORtrend = 1.08, 95%CI: 1.02-1.15). Premenopausal women who ever used oral hormone drug were less likely to have dense breasts, though the difference was marginally significant (OR = 0.54, P = 0.045). In postmenopausal women, we also found the proportion of dense breasts increased with age at menopause (ORtrend = 1.31, 95%CI: 1.21-1.43).

CONCLUSIONS

In Chinese women with average risk for breast cancer, we found MD was associated with age, BMI, menopausal status, lactation, and age at menopausal. This finding may help to understand the etiology of breast cancer and have implications for breast cancer prevention in China.

Dose response relationship between breast cancer and somatotypes during childhood: a systematic review and meta-analysis

OBJECTIVES

This study aims to evaluate the relationship between breast cancer and somatotypes during early life by meta-analysis and give the corresponding advice.

METHODS

Observational studies till April 5, 2021, which explore women with/without breast cancer who used the Stunkard Figure Rating Scale/Sørensen Somatotypes to evaluate their somatotype before 18 years of age and distant breast cancer risk were included. Using random/fixed-effect models, the pooled relative risks (RRs) and 95% confidence intervals (CIs) were estimated. Then a nonlinear dose-response meta-analysis was conducted using restricted cubic spline analysis.

RESULTS

Six articles involving 15,211 breast cancer patients from 341,905 individuals were included for performing a meta-analysis of early somatotype and breast cancer risk. The pooled results showed that the protection became stronger with the increase of somatotype until it reached 6. The restricted cubic spline model indicated a linear relationship between somatotypes and breast cancer (P-nonlinearity = 0.533). Subgroup analysis of menopausal status showed that increasing somatotype during childhood was increasingly protective against postmenopausal breast cancer from somatotype 3 to somatotype 6, with a 0.887-fold (RR = 0.887, 95% CI: 0.842, 0.934) to 0.759-fold (RR = 0.759, 95% CI: 0.631, 0.913) decreased risk of breast cancer (P-nonlinearity = 0.880), but this association was not found in the population with premenopausal breast cancer (P-nonlinearity = 0.757). When stratified by age, among people younger than 10 years of age, an increase in somatotype was associated with a statistically significant reduction in breast cancer risk. From somatotype 3 to somatotype 6, the risk of breast cancer was reduced by 9.7-27.7% (P-nonlinearity = 0.175).

CONCLUSIONS

With early-life adiposity, our data support an inverse association with breast cancer risk, especially age less than 10 years and in postmenopausal women. Since girls with overweight likely remain overweight or even develop obesity in adulthood. While adults with overweight and obese are at increased risk of breast cancer and other types of cancer and various chronic diseases. Hence, we recommend that children should maintain a normal or slightly fat somatotype throughout all periods of life.

Predicting mammographic density with linear ultrasound transducers

BACKGROUND

High mammographic density (MD) is a risk factor for the development of breast cancer (BC). Changes in MD are influenced by multiple factors such as age, BMI, number of full-term pregnancies and lactating periods. To learn more about MD, it is important to establish non-radiation-based, alternative examination methods to mammography such as ultrasound assessments.

METHODS

We analyzed data from 168 patients who underwent standard-of-care mammography and performed additional ultrasound assessment of the breast using a high-frequency (12 MHz) linear probe of the VOLUSON® 730 Expert system (GE Medical Systems Kretztechnik GmbH & Co OHG, Austria). Gray level bins were calculated from ultrasound images to characterize mammographic density. Percentage mammographic density (PMD) was predicted by gray level bins using various regression models.

RESULTS

Gray level bins and PMD correlated to a certain extent. Spearman's ρ ranged from - 0.18 to 0.32. The random forest model turned out to be the most accurate prediction model (cross-validated R2, 0.255). Overall, ultrasound images from the VOLUSON® 730 Expert device in this study showed limited predictive power for PMD when correlated with the corresponding mammograms.

CONCLUSIONS

In our present work, no reliable prediction of PMD using ultrasound imaging could be observed. As previous studies showed a reasonable correlation, predictive power seems to be highly dependent on the device used. Identifying feasible non-radiation imaging methods of the breast and their predictive power remains an important topic and warrants further evaluation. Trial registration 325-19 B (Ethics Committee of the medical faculty at Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany).

Combining Molecular and Radiomic Features for Risk Assessment in Breast Cancer

Breast cancer risk is highly variable within the population and current research is leading the shift toward personalized medicine. By accurately assessing an individual woman's risk, we can reduce the risk of over/undertreatment by preventing unnecessary procedures or by elevating screening procedures. Breast density measured from conventional mammography has been established as one of the most dominant risk factors for breast cancer; however, it is currently limited by its ability to characterize more complex breast parenchymal patterns that have been shown to provide additional information to strengthen cancer risk models. Molecular factors ranging from high penetrance, or high likelihood that a mutation will show signs and symptoms of the disease, to combinations of gene mutations with low penetrance have shown promise for augmenting risk assessment. Although imaging biomarkers and molecular biomarkers have both individually demonstrated improved performance in risk assessment, few studies have evaluated them together. This review aims to highlight the current state of the art in breast cancer risk assessment using imaging and genetic biomarkers.

Changes in Automated Mammographic Breast Density Can Predict Pathological Response After Neoadjuvant Chemotherapy in Breast Cancer

OBJECTIVE

Mammographic density is an independent risk factor for breast cancer that can change after neoadjuvant chemotherapy (NCT). This study aimed to evaluate percent changes in volumetric breast density (ΔVbd%) before and after NCT measured automatically and determine its value as a predictive marker of pathological response to NCT.

MATERIALS AND METHODS

A total of 357 patients with breast cancer treated between January 2014 and December 2016 were included. An automated volumetric breast density (Vbd) measurement method was used to calculate Vbd on mammography before and after NCT. Patients were divided into three groups according to ΔVbd%, calculated as follows: Vbd (post-NCT - pre-NCT)/pre-NCT Vbd × 100 (%). The stable, decreased, and increased groups were defined as -20% ≤ ΔVbd% ≤ 20%, ΔVbd% < -20%, and ΔVbd% > 20%, respectively. Pathological complete response (pCR) was considered to be achieved after NCT if there was no evidence of invasive carcinoma in the breast or metastatic tumors in the axillary and regional lymph nodes on surgical pathology. The association between ΔVbd% grouping and pCR was analyzed using univariable and multivariable logistic regression analyses.

RESULTS

The interval between the pre-NCT and post-NCT mammograms ranged from 79 to 250 days (median, 170 days). In the multivariable analysis, ΔVbd% grouping (odds ratio for pCR of 0.420 [95% confidence interval, 0.195-0.905; P = 0.027] for the decreased group compared with the stable group), N stage at diagnosis, histologic grade, and breast cancer subtype were significantly associated with pCR. This tendency was more evident in the luminal B-like and triple-negative subtypes.

CONCLUSION

ΔVbd% was associated with pCR in breast cancer after NCT, with the decreased group showing a lower rate of pCR than the stable group. Automated measurement of ΔVbd% may help predict the NCT response and prognosis in breast cancer.

Lifetime changes in body fatness and breast density in postmenopausal women: the FEDRA study

BACKGROUND

High mammographic breast density (MBD) is an established risk factor for breast cancer (BC). Body fatness conveys an increased BC risk in postmenopause but is associated with less dense breasts. Here, we studied the relationship between body fatness and breast composition within the FEDRA (Florence-EPIC Digital mammographic density and breast cancer Risk Assessment) longitudinal study.

METHODS

Repeated anthropometric data and MBD parameters (obtained through an automated software on BC screening digital mammograms) were available for all participants, as well as information on other BC risk factors. Multivariate linear regression and functional data analysis were used to longitudinally evaluate the association of body fatness, and changes thereof over time, with dense (DV) and non-dense (NDV) breast volumes and volumetric percent density (VPD).

RESULTS

A total of 5,262 women were included, with anthropometric data available at 20 and 40 years of age, at EPIC baseline (mean 49.0 years), and an average of 9.4 years thereafter. The mean number of mammograms per woman was 3.3 (SD 1.6). Body fatness (and increases thereof) at any age was positively associated with DV and NDV (the association being consistently stronger for the latter), and inversely associated with VPD. For instance, an increase by 1 kg/year between the age of 40 years and EPIC baseline was significantly associated with 1.97% higher DV, 8.85% higher NDV, and 5.82% lower VPD.

CONCLUSION

Body fatness and its increase from young adulthood until midlife are inversely associated with volumetric percent density, but positively associated with dense and non-dense breast volumes in postmenopausal women.

Beyond Breast Density: Risk Measures for Breast Cancer in Multiple Imaging Modalities

Breast density is an independent risk factor for breast cancer. In digital mammography and digital breast tomosynthesis, breast density is assessed visually using the four-category scale developed by the American College of Radiology Breast Imaging Reporting and Data System (5th edition as of November 2022). Epidemiologically based risk models, such as the Tyrer-Cuzick model (version 8), demonstrate superior modeling performance when mammographic density is incorporated. Beyond just density, a separate mammographic measure of breast cancer risk is parenchymal textural complexity. With advancements in radiomics and deep learning, mammographic textural patterns can be assessed quantitatively and incorporated into risk models. Other supplemental screening modalities, such as breast US and MRI, offer independent risk measures complementary to those derived from mammography. Breast US allows the two components of fibroglandular tissue (stromal and glandular) to be visualized separately in a manner that is not possible with mammography. A higher glandular component at screening breast US is associated with higher risk. With MRI, a higher background parenchymal enhancement of the fibroglandular tissue has also emerged as an imaging marker for risk assessment. Imaging markers observed at mammography, US, and MRI are powerful tools in refining breast cancer risk prediction, beyond mammographic density alone.

Association of body composition fat parameters and breast density in mammography by menopausal status

We investigated the relationship between body fat-driven obesity and breast fat density in mammography according to menopausal status. We retrospectively analyzed 8537 women (premenopausal, n = 4351; postmenopausal, n = 4186). Body fat parameters included BMI (body mass index), waist circumference (WC), waist-hip ratio (WHR), fat mass index (FMI), Percentage of body fat (PBF), and visceral fat area (VFA). Body fat-driven obesity was defined as follows: overall obesity, BMI ≥ 25 kg/m²; central obesity, WC > 85 cm; abdominal obesity, WHR > 0.85; excessive FMI, the highest quartile (Q4) of FMI; excessive PBF, the highest quartile (Q4) of VFA; visceral obesity, and the highest quartile (Q4) of VFA). Breast density was classified according to BI-RADS (grade a, b, c, and d), which defined as an ordinal scale (grade a = 1, grade b = 2, grade c = 3, and grade d = 4). All body fat-driven obesity parameters were negatively associated with the grade of breast density in both groups of women (p < 0.001): The more fatty parameters are, the less dense breast is. In multivariable binary logistic regression, all body fat-driven obesity parameters also showed a negative association with grade d density (vs. grade a, b, or c). In premenopausal women, BMI was a more associated parameter with grade d density than those of the other fat-driven parameters (OR 0.265, CI 0.204-0.344). In postmenopausal women, WC was more associated with grade d density than the others (OR 0.315, CI 0.239-0.416). We found that BMI, WC, WHR, FMI, PBF and VFA were negatively correlated with dense breast, and the association degree pattern between body fat-driven obesity and dense breast differs according to menopausal status.

Preventive Health Screening in Veterans Undergoing Bariatric Surgery

INTRODUCTION

Individuals with obesity are vulnerable to low rates of preventive health screening. Veterans with obesity seeking bariatric surgery are also hypothesized to have gaps in preventive health screening. Evaluation in a multidisciplinary bariatric surgery clinic is a point of interaction with the healthcare system that could facilitate improvements in screening.

METHODS

This is a retrospective cohort study of 381 consecutive patients undergoing bariatric surgery at a Veterans Affairs Hospital from January 2010 to October 2021. Age- and sex-appropriate health screening rates were determined at initial referral to a multidisciplinary bariatric surgery clinic and at the time of surgery. Rates of guideline concordance at both time points were compared using McNemar's test. Univariate and multivariate analyses were performed to identify the risk factors for nonconcordance.

RESULTS

Concordance with all recommended screening was low at initial referral and significantly improved by time of surgery (39.1%‒63.8%; p<0.001). Screening rates significantly improved for HIV (p<0.001), cervical cancer (p=0.03), and colon cancer (p<0.001). Increases in BMI (p=0.005) and the number of indicated screening tests (p=0.029) were associated with reduced odds of concordance at initial referral. Smoking history (p=0.012) and increasing distance to the nearest Veterans Affairs Medical Center (p=0.039) were associated with reduced odds of change from nonconcordance at initial referral to concordance at the time of surgery.

CONCLUSIONS

Rates of preventive health screening in Veterans with obesity are low. A multidisciplinary bariatric surgery clinic is an opportunity to improve preventive health screening in Veterans referred for bariatric surgery.

Rat Mammary carcinoma susceptibility 3 (Mcs3) pleiotropy, socioenvironmental interaction, and comparative genomics with orthologous human 15q25.1-25.2

Genome-wide association studies of breast cancer susceptibility have revealed risk-associated genetic variants and nominated candidate genes; however, the identification of causal variants and genes is often undetermined by genome-wide association studies. Comparative genomics, utilizing Rattus norvegicus strains differing in susceptibility to mammary tumor development, is a complimentary approach to identify breast cancer susceptibility genes. Mammary carcinoma susceptibility 3 (Mcs3) is a Copenhagen (COP/NHsd) allele that confers resistance to mammary carcinomas when introgressed into a mammary carcinoma susceptible Wistar Furth (WF/NHsd) genome. Here, Mcs3 was positionally mapped to a 7.2-Mb region of RNO1 spanning rs8149408 to rs107402736 (chr1:143700228-150929594, build 6.0/rn6) using WF.COP congenic strains and 7,12-dimethylbenz(a)anthracene-induced mammary carcinogenesis. Male and female WF.COP-Mcs3 rats had significantly lower body mass compared to the Wistar Furth strain. The effect on female body mass was observed only when females were raised in the absence of males indicating a socioenvironmental interaction. Furthermore, female WF.COP-Mcs3 rats, raised in the absence of males, did not develop enhanced lobuloalveolar morphologies compared to those observed in the Wistar Furth strain. Human 15q25.1-25.2 was determined to be orthologous to rat Mcs3 (chr15:80005820-82285404 and chr15:83134545-84130720, build GRCh38/hg38). A public database search of 15q25.1-25.2 revealed genome-wide significant and nominally significant associations for body mass traits and breast cancer risk. These results support the existence of a breast cancer risk-associated allele at human 15q25.1-25.2 and warrant ultrafine mapping of rat Mcs3 and human 15q25.1-25.2 to discover novel causal genes and variants.

The association of age at menarche and adult height with mammographic density in the International Consortium of Mammographic Density

BACKGROUND

Early age at menarche and tall stature are associated with increased breast cancer risk. We examined whether these associations were also positively associated with mammographic density, a strong marker of breast cancer risk.

METHODS

Participants were 10,681 breast-cancer-free women from 22 countries in the International Consortium of Mammographic Density, each with centrally assessed mammographic density and a common set of epidemiologic data. Study periods for the 27 studies ranged from 1987 to 2014. Multi-level linear regression models estimated changes in square-root per cent density (√PD) and dense area (√DA) associated with age at menarche and adult height in pooled analyses and population-specific meta-analyses. Models were adjusted for age at mammogram, body mass index, menopausal status, hormone therapy use, mammography view and type, mammographic density assessor, parity and height/age at menarche.

RESULTS

In pooled analyses, later age at menarche was associated with higher per cent density (β√PD = 0.023 SE = 0.008, P = 0.003) and larger dense area (β√DA = 0.032 SE = 0.010, P = 0.002). Taller women had larger dense area (β√DA = 0.069 SE = 0.028, P = 0.012) and higher per cent density (β√PD = 0.044, SE = 0.023, P = 0.054), although the observed effect on per cent density depended upon the adjustment used for body size. Similar overall effect estimates were observed in meta-analyses across population groups.

CONCLUSIONS

In one of the largest international studies to date, later age at menarche was positively associated with mammographic density. This is in contrast to its association with breast cancer risk, providing little evidence of mediation. Increased height was also positively associated with mammographic density, particularly dense area. These results suggest a complex relationship between growth and development, mammographic density and breast cancer risk. Future studies should evaluate the potential mediation of the breast cancer effects of taller stature through absolute breast density.

Black Women Are Less Likely to Be Classified as High-Risk for Breast Cancer Using the Tyrer-Cuzick 8 Model

BACKGROUND

Breast cancer risk assessment is a powerful tool that guides recommendations for supplemental breast cancer screening and genetic counseling. The Tyrer-Cuzick 8 (TC8) model is widely used for calculating breast cancer risk and thus helps determine if women qualify for supplemental screening or genetic counseling. However, the TC8 model may underestimate breast cancer risk in Black women. This study sought to assess this disparity.

METHODS

Data on race, breast density, body mass index (BMI), and TC8 scores were retrospectively extracted from the electronic medical record (EMR). Logistic regressions were run to evaluate racial differences in TC8 scores. Summary and correlation statistics determined relationships between BMI, breast density, and race. Rank biserial correlations were employed to explore the impact of breast density and BMI on TC8 scores.

RESULTS

Of 15,356 patients, 5796 were White and 5813 were Black. Black patients had higher rates of BMI ≥ 27 compared with White women (79.2% vs. 45.7%), lower rates of breast density (35.1% vs. 56.2%), and lower rates of high-risk TC8 scores (10.7% vs. 17.5%, OR = 1.6646). There was an inverse relationship between TC8 score and BMI (r_rb = - 0.04) and a direct relationship between TC8 score and breast density (r_rb = 0.37).

DISCUSSION

Black women are less likely to have high-risk TC8 scores despite having only marginally lower breast cancer incidence rates and higher breast cancer mortality rates than White women. This suggests that the TC8 model underestimates breast cancer risk in Black women, possibly due to lower rates of breast density and higher BMIs among Black women.

Body Mass Index and Mammographic Density in a Multiracial and Multiethnic Population-Based Study

BACKGROUND

Mammographic density (MD) is strongly associated with breast cancer risk. We examined whether body mass index (BMI) partially explains racial and ethnic variation in MD.

METHODS

We used multivariable Poisson regression to estimate associations between BMI and binary MD [Breast Imaging Reporting and Database System (BI-RADS) A&B versus BI-RADS C&D] among 160,804 women in the Utah mammography cohort. We estimated associations overall and within racial and ethnic subgroups and calculated population attributable risk percents (PAR%).

RESULTS

We observed the lowest BMI and highest MD among Asian women, the highest BMI among Native Hawaiian and Pacific Islander women, and the lowest MD among American Indian and Alaska Native (AIAN) and Black women. BMI was inversely associated with MD [RRBMI≥30 vs. BMI<25 = 0.43; 95% confidence interval (CI), 0.42-0.44] in the full cohort, and estimates in all racial and ethnic subgroups were consistent with this strong inverse association. For women less than 45 years of age, although there was statistical evidence of heterogeneity in associations between BMI and MD by race and ethnicity (P = 0.009), magnitudes of association were similar across groups. PAR%s for BMI and MD among women less than 45 years were considerably higher in White women (PAR% = 29.2, 95% CI = 28.4-29.9) compared with all other groups with estimates ranging from PAR%Asain = 17.2%; 95% CI, 8.5 to 25.8 to PAR%Hispanic = 21.5%; 95% CI, 19.4 to 23.6. For women ≥55 years, PAR%s for BMI and MD were highest among AIAN women (PAR% = 37.5; 95% CI, 28.1-46.9).

CONCLUSIONS

While we observed substantial differences in the distributions of BMI and MD by race and ethnicity, associations between BMI and MD were generally similar across groups.

IMPACT

Distributions of BMI and MD may be important contributors to breast cancer disparities.

Targeted Intraoperative Radiotherapy (TARGIT-IORT) for Early-Stage Invasive Breast Cancer: A Single Institution Experience

Purpose/Objective

We present our single-institution experience in the management of invasive breast cancer with targeted intraoperative radiotherapy (TARGIT-IORT), focusing on patient suitability for IORT determined by the American Society for Radiation Oncology (ASTRO) Accelerated Partial Breast Irradiation (APBI) consensus guidelines.

Materials/Methods

We identified 237 patients treated for biopsy-proven early-stage invasive breast cancer using low energy x-ray TARGIT-IORT at the time of lumpectomy between September 2013 and April 2020 who were prospectively enrolled in an institutional review board (IRB) approved database. We retrospectively reviewed preoperative and postoperative clinicopathologic factors to determine each patient’s ASTRO APBI suitability (suitable, cautionary or unsuitable) according to the 2017 consensus guidelines (CG). Change in suitability group was determined based on final pathology. Kaplan-Meier methods were used to estimate the survival probability and recurrence probability across time.

Results

237 patients were included in this analysis, based on preoperative clinicopathologic characteristics, 191 (80.6%) patients were suitable, 46 (19.4%) were cautionary and none were deemed unsuitable. Suitability classification changed in 95 (40%) patients based on final pathology from lumpectomy. Increasing preoperative lesion size or a body mass index (BMI) ≥ 30 kg/m² were significant predictors for suitability group change. Forty-one (17.3%) patients received additional adjuvant whole breast radiotherapy after TARGIT-IORT. At a median follow up of 38.2 months (range 0.4 – 74.5), five (2.1%) patients had ipsilateral breast tumor recurrences (IBTR), including two (0.8%) true local recurrences defined as a recurrence in the same quadrant as the initial lumpectomy bed with the same histology as the initial tumor. IBTR occurred in 1/103 (0.09%) patient in the post-op suitable group, 4/98 (4.08%) patients in the post-op cautionary group, and no patients in the post-op unsuitable group. At 3-years, the overall survival rate was 98.4% and the local recurrence free survival rate was 97.1%.

Conclusion

There is a low rate of IBTR after TARGIT-IORT when used in appropriately selected patients. Change in suitability classification pre to postoperatively is common, highlighting a need for further investigation to optimize preoperative patient risk stratification in this setting. Patients who become cautionary or unsuitable based on final pathology should be considered for additional adjuvant therapy.

Metabolic Links to Socioeconomic Stresses Uniquely Affecting Ancestry in Normal Breast Tissue at Risk for Breast Cancer

A primary difference between black women (BW) and white women (WW) diagnosed with breast cancer is aggressiveness of the tumor. Black women have higher mortalities with similar incidence of breast cancer compared to other race/ethnicities, and they are diagnosed at a younger age with more advanced tumors with double the rate of lethal, triple negative breast cancers. One hypothesis is that chronic social and economic stressors result in ancestry-dependent molecular responses that create a tumor permissive tissue microenvironment in normal breast tissue. Altered regulation of N-glycosylation of proteins, a glucose metabolism-linked post-translational modification attached to an asparagine (N) residue, has been associated with two strong independent risk factors for breast cancer: increased breast density and body mass index (BMI). Interestingly, high body mass index (BMI) levels have been reported to associate with increases of cancer-associated N-glycan signatures. In this study, we used matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) to investigate molecular pattern changes of N-glycosylation in ancestry defined normal breast tissue from BW and WW with significant 5-year risk of breast cancer by Gail score. N-glycosylation was tested against social stressors including marital status, single, education, economic status (income), personal reproductive history, the risk factors BMI and age. Normal breast tissue microarrays from the Susan G. Komen tissue bank (BW=43; WW= 43) were used to evaluate glycosylation against socioeconomic stress and risk factors. One specific N-glycan (2158 m/z) appeared dependent on ancestry with high sensitivity and specificity (AUC 0.77, Brown/Wilson p-value<0.0001). Application of a linear regression model with ancestry as group variable and socioeconomic covariates as predictors identified a specific N-glycan signature associated with different socioeconomic stresses. For WW, household income was strongly associated to certain N-glycans, while for BW, marital status (married and single) was strongly associated with the same N-glycan signature. Current work focuses on understanding if combined N-glycan biosignatures can further help understand normal breast tissue at risk. This study lays the foundation for understanding the complexities linking socioeconomic stresses and molecular factors to their role in ancestry dependent breast cancer risk.

Body mass index, breast density, and the risk of breast cancer development in relation to the menopausal status; results from a population-based screening program in a native African-Arab country

Background

Risk factors are traits or behaviors that have an influence on the development of breast cancer (BC). Awareness of the prevalent risk factors can guide in developing prevention interventions.

Purpose

To evaluate the correlation between the breast density, body mass index, and the risk of breast cancer development in relation to the menopausal status in a native African-Arab population.

Material and methods

The study included 30,443 screened females who were classified into cancer and non-cancer groups and each group was further sub-classified into pre- and postmenopausal groups. The breast density (BD) was reported and subjectively classified according to the 2013 ACR BI-RADS breast density classification. The weight and height were measured, and the body mass index (BMI) was calculated and classified according to the WHO BMI classification.

Results

A statistically significant difference was calculated between the mean BMI in the cancer and non-cancer groups (p: .027) as well as between the pre- and postmenopausal groups (p < .001). A positive statistically insignificant correlation was calculated between the breast density and the risk of breast cancer in the premenopausal group (OR: 1.062, p: .919) and a negative highly significant correlation was calculated in the postmenopausal group (OR: 0.234, p < .001).

Conclusion

BMI and BD are inversely associated with each other. The current studied population presented unique ethnic characteristics, where a decreased BD and an increased BMI were found to be independent risk factors for developing breast cancer.

A Case Study in Breast Density Evaluation Using Bioimpedance Measurements

(1) Background: As breast cancer studies suggest, a high percentage of breast density (PBD) may be related to breast cancer incidence. Although PBD screening is one of the strongest predictors of breast cancer risk, X-ray-based mammography evaluation is subjective. Therefore, new objective PBD measuring techniques are of interest. A case study analyzing the PBD of thirteen female participants using a bioimpedance-based method, the anomalies tracking circle (ATC), is described in this paper. (2) Methods: In the first stage, the breast bioimpedance of each participant was measured. Then, the participant breast density was determined by applying a mammogram just after the breast bioimpedance measurement stage. In the third stage, the ATC algorithm was applied to the measured bioimpedance data for each participant, and a results analysis was done. (3) Results: An ATC variation according to the breast density was observed from the obtained data, this allowed the use of classification techniques to determine the PBD. (4) Conclusions: The described breast density method is a promising approach that might be applied as an auxiliary tool to the mammography in order to obtain precise and objective results for evaluation of breast density and with that determine potential breast cancer risk.

Applied Machine Learning in Spiral Breast-CT: Can We Train a Deep Convolutional Neural Network for Automatic, Standardized and Observer Independent Classification of Breast Density?

The aim of this study was to investigate the potential of a machine learning algorithm to accurately classify parenchymal density in spiral breast-CT (BCT), using a deep convolutional neural network (dCNN). In this retrospectively designed study, 634 examinations of 317 patients were included. After image selection and preparation, 5589 images from 634 different BCT examinations were sorted by a four-level density scale, ranging from A to D, using ACR BI-RADS-like criteria. Subsequently four different dCNN models (differences in optimizer and spatial resolution) were trained (70% of data), validated (20%) and tested on a “real-world” dataset (10%). Moreover, dCNN accuracy was compared to a human readout. The overall performance of the model with lowest resolution of input data was highest, reaching an accuracy on the “real-world” dataset of 85.8%. The intra-class correlation of the dCNN and the two readers was almost perfect (0.92) and kappa values between both readers and the dCNN were substantial (0.71–0.76). Moreover, the diagnostic performance between the readers and the dCNN showed very good correspondence with an AUC of 0.89. Artificial Intelligence in the form of a dCNN can be used for standardized, observer-independent and reliable classification of parenchymal density in a BCT examination.

OUP accepted manuscript

In screening for breast cancer (BC), mammographic breast density (MBD) is a powerful risk factor that increases breast carcinogenesis and synergistically reduces the sensitivity of mammography. It also reduces specificity of lesion identification, leading to recalls, additional testing, and delayed and later-stage diagnoses, which result in increased health care costs. These findings provide the foundation for dense breast notification laws and lead to the increase in patient and provider interest in MBD. However, unlike other risk factors for BC, MBD is dynamic through a woman’s lifetime and is modifiable. Although MBD is known to change as a result of factors such as reproductive history and hormonal status, few conclusions have been reached for lifestyle factors such as alcohol, diet, physical activity, smoking, body mass index (BMI), and some commonly used medications. Our review examines the emerging evidence for the association of modifiable factors on MBD and the influence of MBD on BC risk. There are clear associations between alcohol use and menopausal hormone therapy and increased MBD. Physical activity and the Mediterranean diet lower the risk of BC without significant effect on MBD. Although high BMI and smoking are known risk factors for BC, they have been found to decrease MBD. The influence of several other factors, including caffeine intake, nonhormonal medications, and vitamins, on MBD is unclear. We recommend counseling patients on these modifiable risk factors and using this knowledge to help with informed decision making for tailored BC prevention strategies.

Factors associated with mammographic breast density among women in Karachi Pakistan

Background

There are no studies done to evaluate the distribution of mammographic breast density and factors associated with it among Pakistani women.

Methods

Participants included 477 women, who had received either diagnostic or screening mammography at two hospitals in Karachi Pakistan. Mammographic breast density was assessed using the Breast Imaging Reporting and Data System. In person interviews were conducted using a detailed questionnaire, to assess risk factors of interest, and venous blood was collected to measure serum vitamin D level at the end of the interview. To determine the association of potential factors with mammographic breast density, multivariable polytomous logistic regression was used.

Results

High-density mammographic breast density (heterogeneously and dense categories) was high and found in 62.4% of women. There was a significant association of both heterogeneously dense and dense breasts with women of a younger age group < 45 years (OR 2.68, 95% CI 1.60–4.49) and (OR 4.83, 95% CI 2.54–9.16) respectively. Women with heterogeneously dense and dense breasts versus fatty and fibroglandular breasts had a higher history of benign breast disease (OR 1.90, 95% CI 1.14–3.17) and (OR 3.61, 95% CI 1.90–6.86) respectively. There was an inverse relationship between breast density and body mass index. Women with dense breasts and heterogeneously dense breasts had lower body mass index (OR 0.94 95% CI 0.90–0.99) and (OR 0.81, 95% CI 0.76–0.87) respectively. There was no association of mammographic breast density with serum vitamin D levels, diet, and breast cancer.

Conclusions

The findings of a positive association of higher mammographic density with younger age and benign breast disease and a negative association between body mass index and breast density are important findings that need to be considered in developing screening guidelines for the Pakistani population.

Association of the Interaction Between Mammographic Breast Density, Body Mass Index, and Menopausal Status With Breast Cancer Risk Among Korean Women

IMPORTANCE

Evidence suggests that breast density and body mass index (BMI) are strong breast cancer risk factors; however, their interactive associations are unknown. Elucidation of these interactive associations may help to increase understanding of the causes of breast cancer and find effective interventions for susceptible subgroups.

OBJECTIVE

To explore the association of the interaction of mammographic breast density and BMI with breast cancer risks among premenopausal and postmenopausal women.

DESIGN, SETTING, AND PARTICIPANTS

This prospective observational cohort study used population-based data of the Korean National Cancer Screening Program embedded in the National Health Insurance Service database to evaluate the breast cancer risk of 3 248 941 premenopausal cancer-free women and 4 373 473 postmenopausal cancer-free women aged 40 years or older who underwent mammographic screening between January 1, 2009, and December 31, 2013, and were followed up until December 31, 2018. Statistical analysis was performed from June 1 to July 15, 2021.

EXPOSURES

Breast Imaging Reporting and Data System (BI-RADS)-defined breast density (with a scale from 1 to 4, where 1 indicates almost entirely fat, 2 indicates scattered fibroglandular densities, 3 indicates heterogeneously dense tissue, and 4 indicates extremely dense tissue) and BMI levels classified according to the World Health Organization Asia-Pacific Region classification.

MAIN OUTCOMES AND MEASURES

Adjusted relative risk (aRR) of breast cancer during the follow-up period and interactions in additive and multiplicative scales. The study end point was the development of breast cancer.

RESULTS

Of 3 248 941 premenopausal women (mean [SD] age, 44.6 [4.3] years) and 4 373 473 postmenopausal women (mean [SD] age, 59.6 [8.4] years) aged 40 years or older, 34 466 cases of breast cancer were identified among the premenopausal women, and 30 816 cases of breast cancer were identified among the postmenopausal women. Increased breast density was associated with an increased risk of breast cancer in both premenopausal and postmenopausal women across the BMI categories. Among premenopausal women, those in BI-RADS category 4 had an approximately 2-fold higher risk of breast cancer irrespective of BMI (all women: aRR, 2.36 [95% CI, 2.24-2.49]; underweight: aRR, 1.80 [95% CI, 1.25-2.59]; normal weight: aRR, 2.10 [95% CI, 1.93-2.28]; overweight: aRR, 2.47 [95% CI, 2.27-2.68]; obese: aRR, 2.87 [95% CI, 2.49-3.32]) than those with underweight status and in BI-RADS category 1. However, an association between BMI and the risk of breast cancer was found only in the postmenopausal women in all breast density categories compared with underweight women with BI-RADS category 1 (BI-RADS category 4, all women: aRR, 2.91 [95% CI, 2.78-3.04]; underweight: aRR, 2.74 [95% CI, 1.89-3.98]; normal weight: aRR, 3.05 [95% CI, 2.82-3.30]; overweight: aRR, 2.85 [95% CI, 2.67-3.04]; obese: aRR, 2.52 [95% CI, 2.22-2.88]). When the combined associations of breast density and BMI with the risk of breast cancer were considered, a high breast density and high BMI had a significant positive interaction on the additive scale for both premenopausal and postmenopausal women, especially the latter (premenopausal women: adjusted relative excess risk due to interaction, 0.53 [95% CI, 0.35-0.71]; postmenopausal women: adjusted relative excess risk due to interaction, 1.68 [95% CI, 1.26-2.10]).

CONCLUSIONS AND RELEVANCE

This study suggests that breast density and BMI interact synergistically to augment breast cancer risk, with a stronger association found among postmenopausal women. Both factors should be incorporated into risk stratification in a population-based screening for public health significance. Women with overweight or obesity and dense breast tissue might benefit from tailored early screening strategies to detect breast cancer.

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.

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.

Adolescent and early adulthood inflammation-associated dietary patterns in relation to premenopausal mammographic density

BACKGROUND

Adolescence and early adulthood has been identified as a critical time window for establishing breast cancer risk. Mammographic density is an independent risk factor for breast cancer that may be influenced by diet, but there has been limited research conducted on the impact of diet on mammographic density. Thus, we sought to examine the association between adolescent and early adulthood inflammatory dietary patterns, which have previously been associated with breast cancer risk, and premenopausal mammographic density among women in the Nurses' Health Study II (NHSII).

METHODS

This study included control participants with premenopausal mammograms from an existing breast cancer case-control study nested within the NHSII who completed a Food Frequency Questionnaire in 1998 about their diet during high school (HS-FFQ) (n = 685) and/or a Food Frequency Questionnaire in 1991 (Adult-FFQ) when they were 27-44 years old (n = 1068). Digitized analog film mammograms were used to calculate the percent density, absolute dense, and non-dense areas. Generalized linear models were fit to evaluate the associations of a pro-inflammatory dietary pattern and the Alternative Healthy Eating Index (AHEI, an anti-inflammatory dietary pattern) with each breast density measure.

RESULTS

Significant associations were observed between an adolescent pro-inflammatory dietary pattern and mammographic density in some age-adjusted models; however, these associations did not remain after adjustment for BMI and other breast cancer risk factors. No associations were observed with the pro-inflammatory pattern or with the AHEI pattern in adolescence or early adulthood in fully adjusted models.

CONCLUSIONS

To our knowledge, this is the first study to evaluate the dietary patterns during adolescence and early adulthood in relation to mammographic density phenotypes. Our findings do not support an association between adolescent and early adulthood diet and breast density in mid-adulthood that is independent of BMI or other breast cancer risk factors.

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.

Identification of a Positive Association between Mammary Adipose Cholesterol Content and Indicators of Breast Cancer Aggressiveness in a French Population

BACKGROUND

Several studies have recently highlighted important roles for adipose tissue in cancer. However, few have examined adipose tissue cholesterol, and no study has been performed in breast adipose tissue associated with breast tumors.

OBJECTIVES

The present work was designed to determine if breast adipose tissue cholesterol from the tumor-surrounding area is associated with breast cancer aggressiveness.

METHODS

Between 2009 and 2011, 215 breast adipose tissue samples were collected at the Tours University Hospital (France) during surgery of women (aged 28-89 y) with invasive breast cancer. Associations of free cholesterol (FC), esterified cholesterol (EC), and total cholesterol (TC) amounts with clinical variables (age, BMI, and treated or untreated hypercholesterolemia) and tumor aggressiveness parameters [phenotype, grade, presence of inflammatory breast cancer (IBC), and multifocality] were tested using Student's t test and after ANOVA.

RESULTS

The predominant form of cholesterol in adipose tissue was FC, and 50% of patients had no detectable EC. The adipose tissue FC content (μg/mg total lipid) was 18% greater in patients >70 y old than in those 40-49 y old (P < 0.05) and the TC content tended to be 12% greater in untreated hypercholesterolemic patients than in normocholesterolemic patients (P = 0.06). Breast adipose cholesterol concentrations were increased in tissues obtained from patients with human-epidermal-growth-factor-receptor-2 (HER2) phenotype (+13% FC; P < 0.05 compared with luminal A), IBC (+15% FC; P = 0.06 compared with noninflammatory tumors), as well as with multifocal triple-negative tumors (+34% FC, P < 0.05; +30% TC, P < 0.05, compared with unifocal triple-negative tumors). Among patients with triple-negative tumors, hypercholesterolemia was significantly more common (P < 0.05) in patients with multifocal tumors (64%) than in patients with unifocal tumors (25%).

CONCLUSIONS

This study is the first of this magnitude that analyzes cholesterol concentrations in adipose tissue from female breast cancer patients. An increase in breast adipose tissue cholesterol content may contribute to breast cancer aggressiveness (HER2 phenotype, multifocality of triple-negative tumors, and IBC).

[Management of breast cancer in Abidjan: A single center experience]

AIM

To present the results of the personalized care of Ivorian women suffering from breast cancer since the advent of immunohistochemistry in Côte d'Ivoire.

METHODS

We carried out a single-center retrospective study at the Yopougon university hospital from January 2014 to December 2018. All women's breast cancer with complementary immunohistochemistry and treated at the Yopougon hospital center were selected. Standard descriptive statistical tests were used to describe patient and tumor characteristics, and univariate and multivariate analyzes were performed with a statistical significance set at a P-value of 0.05 using SPSS version 20.0.

RESULTS

The mean age of women is 48.27 years, SD (11.92). 50.88 % of the tumors were hormone-dependent. The triple negative subgroup was the most represented (43.28 %) followed by luminal A (35.42 %). Conservative treatment represented 18.51 % of cases. In the univariate analysis, the risk of developing a hormone-dependent cancer is statistically significant respectively in women with an education level removed OR=1.98 (P˂0.015) and with a wealthy salary OR=1.85 (P˂0.009). On the other hand, the high level of education (OR=0.44; P˂0.005), and the well-off salary condition (OR=0.59; P˂0.024) would be protective factors for the development of triple negative breast cancer. All these factors are not significant in multivariate analysis, whether for hormone-dependent or triple negative tumors.

CONCLUSION

The personalized care of breast cancer in our African context remains difficult and must take into account several medical and extra-medical parameters.

Predictors of mammographic microcalcifications

We examined the association between established risk factors for breast cancer and microcalcification clusters and their asymmetry. A cohort study of 53 273 Swedish women aged 30 to 80 years, with comprehensive information on breast cancer risk factors and mammograms, was conducted. Total number of microcalcification clusters and the average mammographic density area were measured using a Computer Aided Detection system and the STRATUS method, respectively. A polygenic risk score for breast cancer, including 313 single nucleotide polymorphisms, was calculated for those women genotyped (N = 7387). Odds ratios (ORs) and 95% confidence intervals (CIs), with adjustment for potential confounders, were estimated. Age was strongly associated with microcalcification clusters. Both high mammographic density (>40 cm2 ), and high polygenic risk score (80-100 percentile) were associated with microcalcification clusters, OR = 2.08 (95% CI = 1.93-2.25) and OR = 1.22 (95% CI = 1.06-1.48), respectively. Among reproductive risk factors, life-time breastfeeding duration >1 year was associated with microcalcification clusters OR = 1.22 (95% CI = 1.03-1.46). The association was confined to postmenopausal women. Among lifestyle risk factors, women with a body mass index ≥30 kg/m2 had the lowest risk of microcalcification clusters OR = 0.79 (95% CI = 0.73-0.85) and the association was stronger among premenopausal women. Our results suggest that age, mammographic density, genetic predictors of breast cancer, having more than two children, longer duration of breast-feeding are significantly associated with increased risk of microcalcification clusters. However, most lifestyle risk factors for breast cancer seem to protect against presence of microcalcification clusters. More research is needed to study biological mechanisms behind microcalcifications formation.

Effects of neoadjuvant chemotherapy on the contralateral non-tumor-bearing breast assessed by diffuse optical tomography

BACKGROUND

The purpose of this study is to evaluate whether the changes in optically derived parameters acquired with a diffuse optical tomography breast imager system (DOTBIS) in the contralateral non-tumor-bearing breast in patients administered neoadjuvant chemotherapy (NAC) for breast cancer are associated with pathologic complete response (pCR).

METHODS

In this retrospective evaluation of 105 patients with stage II-III breast cancer, oxy-hemoglobin (ctO₂Hb) from the contralateral non-tumor-bearing breast was collected and analyzed at different time points during NAC. The earliest monitoring imaging time point was after 2-3 weeks receiving taxane. Longitudinal data were analyzed using linear mixed-effects modeling to evaluate the contralateral breast ctO₂Hb changes across chemotherapy when corrected for pCR status, age, and BMI.

RESULTS

Patients who achieved pCR to NAC had an overall decrease of 3.88 μM for ctO₂Hb (95% CI, 1.39 to 6.37 μM), p = .004, after 2-3 weeks. On the other hand, non-pCR subjects had a non-significant mean reduction of 0.14 μM (95% CI, - 1.30 to 1.58 μM), p > .05. Mixed-effect model results indicated a statistically significant negative relationship of ctO₂Hb levels with BMI and age.

CONCLUSIONS

This study demonstrates that the contralateral normal breast tissue assessed by DOTBIS is modifiable after NAC, with changes associated with pCR after only 2-3 weeks of chemotherapy.

Supplemental Screening for Patients at Intermediate and High Risk for Breast Cancer

The sensitivity of mammography is more limited in patients with dense breasts and some patients at higher risk for breast cancer. Patients with intermediate or high risk for breast cancer may begin screening earlier and benefit from supplemental screening techniques beyond standard 2-dimensional mammography. A patient's individual risk factors for developing breast cancer, their breast density, and the evidence supporting specific modalities for a given clinical scenario help to determine the need for supplemental screening and the modality chosen. Additional factors include the availability of supplemental screening techniques at an individual institution, cost, insurance coverage, and state-specific breast density legislation.

Causal mediation analysis in presence of multiple mediators uncausally related

Mediation analysis aims at disentangling the effects of a treatment on an outcome through alternative causal mechanisms and has become a popular practice in biomedical and social science applications. The causal framework based on counterfactuals is currently the standard approach to mediation, with important methodological advances introduced in the literature in the last decade, especially for simple mediation, that is with one mediator at the time. Among a variety of alternative approaches, Imai et al. showed theoretical results and developed an R package to deal with simple mediation as well as with multiple mediation involving multiple mediators conditionally independent given the treatment and baseline covariates. This approach does not allow to consider the often encountered situation in which an unobserved common cause induces a spurious correlation between the mediators. In this context, which we refer to as mediation with uncausally related mediators, we show that, under appropriate hypothesis, the natural direct and joint indirect effects are non-parametrically identifiable. Moreover, we adopt the quasi-Bayesian algorithm developed by Imai et al. and propose a procedure based on the simulation of counterfactual distributions to estimate not only the direct and joint indirect effects but also the indirect effects through individual mediators. We study the properties of the proposed estimators through simulations. As an illustration, we apply our method on a real data set from a large cohort to assess the effect of hormone replacement treatment on breast cancer risk through three mediators, namely dense mammographic area, nondense area and body mass index.

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 Breast Density and Urbanization: Interactions with BMI, Environmental, Lifestyle, and Other Patient Factors

Mammographic breast density (MBD) is an important imaging biomarker of breast cancer risk, but it has been suggested that increased MBD is not a genuine finding once corrected for age and body mass index (BMI). This study examined the association of various factors, including both residing in and working in the urban setting, with MBD. Questionnaires were completed by 1144 women attending for mammography at the London Breast Institute in 2012–2013. Breast density was assessed with an automated volumetric breast density measurement system (Volpara) and compared with subjective radiologist assessment. Multivariable linear regression was used to model the relationship between MBD and residence in the urban setting as well as working in the urban setting, adjusting for both age and BMI and other menstrual, reproductive, and lifestyle factors. Urban residence was significantly associated with an increasing percent of MBD, but this association became non-significant when adjusted for age and BMI. This was not the case for women who were both residents in the urban setting and still working. Our results suggest that the association between urban women and increased MBD can be partially explained by their lower BMI, but for women still working, there appear to be other contributing factors.

Empirically-derived synthetic populations to mitigate small sample sizes

Limited sample sizes can lead to spurious modeling findings in biomedical research. The objective of this work is to present a new method to generate synthetic populations (SPs) from limited samples using matched case-control data (n = 180 pairs), considered as two separate limited samples. SPs were generated with multivariate kernel density estimations (KDEs) with unconstrained bandwidth matrices. We included four continuous variables and one categorical variable for each individual. Bandwidth matrices were determined with Differential Evolution (DE) optimization by covariance comparisons. Four synthetic samples (n = 180) were derived from their respective SPs. Similarity between observed samples with synthetic samples was compared assuming their empirical probability density functions (EPDFs) were similar. EPDFs were compared with the maximum mean discrepancy (MMD) test statistic based on the Kernel Two-Sample Test. To evaluate similarity within a modeling context, EPDFs derived from the Principal Component Analysis (PCA) scores and residuals were summarized with the distance to the model in X-space (DModX) as additional comparisons. Four SPs were generated from each sample. The probability of selecting a replicate when randomly constructing synthetic samples (n = 180) was infinitesimally small. MMD tests indicated that the observed sample EPDFs were similar to the respective synthetic EPDFs. For the samples, PCA scores and residuals did not deviate significantly when compared with their respective synthetic samples. The feasibility of this approach was demonstrated by producing synthetic data at the individual level, statistically similar to the observed samples. The methodology coupled KDE with DE optimization and deployed novel similarity metrics derived from PCA. This approach could be used to generate larger-sized synthetic samples. To develop this approach into a research tool for data exploration purposes, additional evaluation with increased dimensionality is required. Moreover, given a fully specified population, the degree to which individuals can be discarded while synthesizing the respective population accurately will be investigated. When these objectives are addressed, comparisons with other techniques such as bootstrapping will be required for a complete evaluation.

Association of Imaging-Based Body Fat Distribution and Mammographic Density in the Multiethnic Cohort Adiposity Phenotype Study

BACKGROUND

As the stronger association of obesity with postmenopausal breast cancer in Asian than white women may be due to body fat distribution, we examined the relation of adiposity measures with percent mammographic density (PMD), a strong predictor of breast cancer incidence.

METHODS

A total of 938 women from five ethnic groups (69.1 ± 2.7 years) in the Adiposity Phenotype Study (APS) underwent DXA and MRI imaging. PMD was assessed in routine mammograms using a computer-assisted method. Spearman correlation coefficients were computed and general linear models were applied to estimate regression coefficients (β) for PMD per 0.5 SD units of adiposity measures while adjusting for known confounders, including DXA total body fat.

RESULTS

For 701 (75%) of the participants (69.1 ± 2.7 years), valid mammograms were obtained. Whereas total body fat, the trunk-to-periphery fat ratio (TPFR), visceral fat (VAT), and subcutaneous fat (SAT) were inversely correlated with PMD (P < 0.0001), the VAT/SAT ratio correlated positively (r spearman = 0.10; P = 0.01). In fully adjusted models, PMD remained inversely related to TPFR and SAT and disappeared for VAT, while it was strengthened for VAT/SAT (β = 0.51; P = 0.009). This relation was stronger in Japanese Americans than other ethnic groups.

CONCLUSIONS

This is the first study to show an association of a high VAT/SAT ratio with greater PMD, a marker of breast cancer risk after taking into account total body fat.

IMPACT

The results indicate a link between the propensity to accumulate VAT and the amount of fat in the breast (1-PMD), which may influence the relation of obesity with breast cancer incidence.

Obesity and breast cancer screening: Cross-sectional survey results from the behavioral risk factor surveillance system

BACKGROUND

Postmenopausal obese women demonstrate an elevated breast cancer risk and experience increased breast cancer morbidity and mortality compared with women with a normal body mass index (BMI). However, to the authors' knowledge, prior studies have yielded inconclusive results regarding the effects of obesity on mammography screening adherence. Using national cross-sectional survey data, the objective of the current study was to assess the current association between increasing BMI and use of mammography screening.

METHODS

Cross-sectional survey data from the 2016 Behavioral Risk Factor Surveillance System, a state-based national telephone survey of noninstitutionalized adults in the United States, was used to identify the association between mammography screening use and increasing incremental BMI categories, including normal (18.5-24.9 kg/m2 ), overweight (25-29.9 kg/m2 ), obese class I (30-34.9 kg/m2 ), obese class II (35-39.9 kg/m2 ), and obese class III (>40 kg/m2 ), with adjustments for potential confounders. A multivariable logistic regression model was used to evaluate the effect of each BMI category on self-reported mammography use, using unadjusted and adjusted odds ratios. Effect modification by race/ethnicity was determined by testing interaction terms using Wald tests.

RESULTS

Of 116,343 survey respondents, 33.5% (38,984 respondents) had a normal BMI, 32.6% (37,969 respondents) were overweight, 19.3% (22,416 respondents) were classified as obese class I, 8.4% (9791 respondents) were classified as obese class II, and 6.2% (7183 respondents) were classified as obese class III. There was no statistically significant difference (P < .05) observed with regard to mammography use between women with a normal BMI and obese women from each obese class (classes I-III) when compared individually. There also was no evidence of effect modification by race (P = .53).

CONCLUSIONS

In contrast to prior reports, the results of the current study demonstrated no association between obesity and adherence to screening mammography. These findings may relate to the increasing social acceptance of obesity among women from all racial/ethnic groups and the removal of weight-related facility-level barriers over time.

The impact of bariatric surgery on qualitative and quantitative breast density

BACKGROUND

Obesity and breast density are associated with breast cancer in postmenopausal women. Bariatric surgery effectively treats morbid obesity, with sustainable weight loss and reductions in cancer incidence. We evaluated changes in qualitative and quantitative density; hypothesizing breast density would increase following bariatric surgery.

METHODS

Women undergoing bariatric surgery from 1990 to 2015 were identified, excluding patients without a mammogram performed both before and after surgery. Changes in body mass index (BMI), time between mammograms and surgery, and American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) scores were assessed. VolparaDensity™ automated software calculated volumetric breast density (VBD), fibroglandular volume (FGV), and total breast volume for the 82 women with digital data available. Differences between pre- and postsurgery values were assessed.

RESULTS

One hundred eighty women were included. Median age at surgery was 50.0 years, with 8.8 months between presurgery mammogram and surgery and 62.3 months between surgery and postsurgery mammogram. Median BMI significantly decreased over the study period (46.0 vs 35.4 kg/m² ; P < 0.001). No change in BI-RADS scores was seen between the pre- and postsurgery mammograms. Eighty-two women had VolparaDensity™ data available. While VBD increased in these patients, FGV and total breast volume both decreased following bariatric surgery.

CONCLUSIONS

Increased VBD, decreased FGV, and decreased total breast volume were seen following bariatric surgery-induced weight loss. There was no difference in qualitative breast density, highlighting the discrepancy between BI-RADS and VolparaDensity™ measurements. Further investigation will be required to determine how differential changes in components of breast density may affect breast cancer risk.

Measuring height and weight as part of routine mammographic screening for breast cancer

Objectives

Body mass index is a strong predictor of post-menopausal breast cancer risk and (negatively) confounds the association between mammographic breast density and breast cancer risk; however, height and weight are not typically measured as part of routine mammographic screening. This study piloted voluntary height and weight measurement within the BreastScreen Western Australia (WA) programme, and assessed trial participation.

Methods

From February 2016 to January 2018, 204,429 women attending BreastScreen WA were invited to have their height and weight measured and recorded as part of their routine screening mammogram. Descriptive data analysis was used to assess pilot participation rates by available screening data.

Results

Of the 204,429 patients who attended BreastScreen WA during the pilot, 76.35% (156,072) agreed to have their height and weight measured. Pilot participation rates were significantly lower in those patients with disabilities (RR: 0.626; 95% CI: 0.600, 0.653), those who spoke a language other than English at home (RR: 0.876; 95% CI: 0.867, 0.885), and those who identified as Aboriginal and Torres Strait Islander (RR: 0.829; 95% CI: 0.807, 0.852). Pilot participation decreased over time from 88.9% in the first three months to 55.5% in the last month, due to lessening of support from BreastScreen staff.

Conclusion

Measuring height and weight at the time of routine mammographic screening is feasible, although logistical issues, particularly the added time/effort required of support staff, should be considered. BreastScreen WA has since decided to collect voluntary self-reported height and weight data as routine screening policy.

Predictors of mammographic density among women with a strong family history of breast cancer

BACKGROUND

Mammographic density is one of the strongest risk factors for breast cancer. In the general population, mammographic density can be modified by various exposures; whether this is true for women a strong family history is not known. Thus, we evaluated the association between reproductive, hormonal, and lifestyle risk factors and mammographic density among women with a strong family history of breast cancer but no BRCA1 or BRCA2 mutation.

METHODS

We included 97 premenopausal and 59 postmenopausal women (age range: 27-68 years). Risk factor data was extracted from the research questionnaire closest in time to the mammogram performed nearest to enrollment. The Cumulus software was used to measure percent density, dense area, and non-dense area for each mammogram. Multivariate generalized linear models were used to evaluate the relationships between breast cancer risk factors and measures of mammographic density, adjusting for relevant covariates.

RESULTS

Among premenopausal women, those who had two live births had a mean percent density of 28.8% vs. 41.6% among women who had one live birth (P=0.04). Women with a high body weight had a lower mean percent density compared to women with a low body weight among premenopausal (17.6% vs. 33.2%; P=0.0006) and postmenopausal women (8.7% vs. 14.7%; P=0.04). Among premenopausal women, those who smoked for 14 years or longer had a lower mean dense area compared to women who smoked for a shorter duration (25.3cm² vs. 53.1cm²; P=0.002). Among postmenopausal women, former smokers had a higher mean percent density (19.5% vs. 10.8%; P=0.003) and dense area (26.9% vs. 16.4%; P=0.01) compared to never smokers. After applying the Bonferroni correction, the association between body weight and percent density among premenopausal women remained statistically significant.

CONCLUSIONS

In this cohort of women with a strong family history of breast cancer, body weight was associated with mammographic density. These findings suggest that mammographic density may explain the underlying relationship between some of these risk factors and breast cancer risk, and lend support for the inclusion of mammographic density into risk prediction models.

In utero and postnatal programing of dehydroepiandrosterone sulfate (DHEAS) in young adult women

Fetal adrenal-derived OH-DHEAS is the primary precursor for maternal estriol, an abundant, human, placental estrogen. We measured maternal pregnancy estriol as a marker of fetal adrenal function + placenta capacity to synthesize estriol. We hypothesized that maternal estriol is directly correlated with the adrenal hormone, DHEAS, in young adult women. We tested this hypothesis in a subset of women in the Child Health and Development Studies (351 of 470 eligible). 176 of these had serum samples collected at ages 27-30 for DHEAS assays, archived maternal pregnancy serum for estriol assays, and childhood growth data. In regression analyses, both maternal estriol and accelerated growth in middle childhood were independently, directly associated with DHEAS (+19% for quartile 4 versus quartile 1 of estriol, 95%CI=+ 2%, +36% and +12% for quartile 4 versus quartile 1 for middle childhood growth, 95%CI= +3%, +21%). Adrenal function may be programmed in utero and middle childhood with long-term consequences.

A Longitudinal Study of the Association between Mammographic Density and Gene Expression in Normal Breast Tissue

High mammographic density (MD) is associated with a 4-6 times increase in breast cancer risk. For post-menopausal women, MD often decreases over time, but little is known about the underlying biological mechanisms. MD reflects breast tissue composition, and may be associated with microenvironment subtypes previously identified in tumor-adjacent normal tissue. Currently, these subtypes have not been explored in normal breast tissue. We obtained biopsies from breasts of healthy women at two different time points several years apart and performed microarray gene expression analysis. At time point 1, 65 samples with both MD and gene expression were available. At time point 2, gene expression and MD data were available from 17 women, of which 11 also had gene expression data available from the first time point. We validated findings from our previous study; negative correlation between RBL1 and MD in post-menopausal women, indicating involvement of the TGFβ pathway. We also found that breast tissue samples from women with a large decrease in MD sustained higher expression of genes in the histone family H4. In addition, we explored the previously defined active and inactive microenvironment subtypes and demonstrated that normal breast samples of the active subtype had characteristics similar to the claudin-low breast cancer subtype. Breast biopsies from healthy women are challenging to obtain, but despite a limited sample size, we have identified possible mechanisms relevant for changes in breast biology and MD over time that may be of importance for breast cancer risk and tumor initiation.

Combined effect of volumetric breast density and body mass index on breast cancer risk

BACKGROUND

Breast density and body mass index (BMI) are used for breast cancer risk stratification. We evaluate whether the positive association between volumetric breast density and breast cancer risk is strengthened with increasing BMI.

METHODS

The San Francisco Mammography Registry and Mayo Clinic Rochester identified 781 premenopausal and 1850 postmenopausal women with breast cancer diagnosed between 2007 and 2015 that had a screening digital mammogram at least 6 months prior to diagnosis. Up to three controls (N = 3535) were matched per case on age, race, date, mammography machine, and state. Volumetric percent density (VPD) and dense volume (DV) were measured with Volpara™. Breast cancer risk was assessed with logistic regression stratified by menopause status. Multiplicative interaction tests assessed whether the association of density measures was differential by BMI categories.

RESULTS

The increased risk of breast cancer associated with VPD was strengthened with higher BMI for both premenopausal (p_interaction = 0.01) and postmenopausal (p_interaction = 0.0003) women. For BMI < 25, 25-30, and ≥ 30 kg/m², ORs for breast cancer for a 1 SD increase in VPD were 1.24, 1.65, and 1.97 for premenopausal, and 1.20, 1.55, and 2.25 for postmenopausal women, respectively. ORs for breast cancer for a 1 SD increase in DV were 1.39, 1.33, and 1.51 for premenopausal (p_interaction = 0.58), and 1.31, 1.34, and 1.65 (p_interaction = 0.03) for postmenopausal women for BMI < 25, 25-30 and ≥ 30 kg/m², respectively.

CONCLUSIONS

The effect of volumetric percent density on breast cancer risk is strongest in overweight and obese women. These associations have clinical relevance for informing prevention strategies.