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

Association of area- and volumetric-mammographic density and breast cancer risk in women of Asian descent: a case control study

BACKGROUND

Mammographic density (MD) has been shown to be a strong and independent risk factor for breast cancer in women of European and Asian descent. However, the majority of Asian studies to date have used BI-RADS as the scoring method and none have evaluated area and volumetric densities in the same cohort of women. This study aims to compare the association of MD measured by two automated methods with the risk of breast cancer in Asian women, and to investigate if the association is different for premenopausal and postmenopausal women.

METHODS

In this case-control study of 531 cases and 2297 controls, we evaluated the association of area-based MD measures and volumetric-based MD measures with breast cancer risk in Asian women using conditional logistic regression analysis, adjusting for relevant confounders. The corresponding association by menopausal status were assessed using unconditional logistic regression.

RESULTS

We found that both area and volume-based MD measures were associated with breast cancer risk. Strongest associations were observed for percent densities (OR (95% CI) was 2.06 (1.42-2.99) for percent dense area and 2.21 (1.44-3.39) for percent dense volume, comparing women in highest density quartile with those in the lowest quartile). The corresponding associations were significant in postmenopausal but not premenopausal women (premenopausal versus postmenopausal were 1.59 (0.95-2.67) and 1.89 (1.22-2.96) for percent dense area and 1.24 (0.70-2.22) and 1.96 (1.19-3.27) for percent dense volume). However, the odds ratios were not statistically different by menopausal status [p difference = 0.782 for percent dense area and 0.486 for percent dense volume].

CONCLUSIONS

This study confirms the associations of mammographic density measured by both area and volumetric methods and breast cancer risk in Asian women. Stronger associations were observed for percent dense area and percent dense volume, and strongest effects were seen in postmenopausal individuals.

Adiposity, Body Composition Measures, and Breast Cancer Risk in Korean Premenopausal Women

Objective

To investigate the association between body composition parameters and breast cancer (BC) risk in premenopausal women.

Design, Setting, and Participants

Prospective cohort study using data from the Kangbuk Samsung Cohort Study. Participants were women aged 20 to 54 years who were enrolled from 2011 to 2019 and followed up for BC development until December 31, 2020. Data were analyzed from June to August 2023.

Exposures

Trained nurses conducted anthropometric measurements and assessed body composition using segmental bioelectric impedance analysis. The analysis encompassed adiposity measures such as body mass index (BMI), waist circumference, and body composition parameters, including muscle mass, fat mass, ratio of muscle mass to weight, ratio of fat mass to weight, and fat mass index.

Main outcomes and measures

Adjusted hazard ratios (aHR) for BC during the follow-up period.

Results

Among 125 188 premenopausal women, the mean (SD) age was 34.9 (6.3) years. During a mean (range) follow-up of 6.7 (0.5-9.9) years, 1110 incident BC cases were identified. The mean (SD) BMI and waist circumference were 21.6 (3.1) and 75.3 (8.2) cm, respectively. Higher BMI and waist circumference were associated with decreased risk, with an aHR of 0.89 (95% CI, 0.84-0.95) per SD increase in BMI and 0.92 (95% CI, 0.86-0.98) per SD increase in waist circumference. A higher ratio of fat mass to weight was associated with decreased BC risk (aHR, 0.92; 95% CI, 0.86-0.99 per SD increase), whereas the opposite trend was observed for the ratio of muscle mass to weight, with an aHR of 1.08 (95% CI, 1.02-1.15) per SD increase. The results remained consistent even after additional adjustments for height in the model. The fat mass index was also inversely associated with BC risk, with an HR of 0.90 (95% CI, 0.85-0.97) per SD increase.

Conclusions and Relevance

In this cohort study of premenopausal women, a higher level of adiposity, represented by increased BMI, waist circumference, and fat mass, was consistently associated with decreased breast cancer risk. Conversely, muscle mass and its ratio to weight displayed opposite or inconsistent patterns. These findings suggest an inverse association between excess adiposity and the risk of BC in premenopausal women, confirming earlier findings that BMI is an indirect measure of adiposity.

Identifying factors that indicate the possibility of non-visible cases on mammograms using mammary gland content ratio estimated by artificial intelligence

Background

Mammography is the modality of choice for breast cancer screening. However, some cases of breast cancer have been diagnosed through ultrasonography alone with no or benign findings on mammography (hereby referred to as non-visibles). Therefore, this study aimed to identify factors that indicate the possibility of non-visibles based on the mammary gland content ratio estimated using artificial intelligence (AI) by patient age and compressed breast thickness (CBT).

Methods

We used AI previously developed by us to estimate the mammary gland content ratio and quantitatively analyze 26,232 controls and 150 non-visibles. First, we evaluated divergence trends between controls and non-visibles based on the average estimated mammary gland content ratio to ensure the importance of analysis by age and CBT. Next, we evaluated the possibility that mammary gland content ratio ≥50% groups affect the divergence between controls and non-visibles to specifically identify factors that indicate the possibility of non-visibles. The images were classified into two groups for the estimated mammary gland content ratios with a threshold of 50%, and logistic regression analysis was performed between controls and non-visibles.

Results

The average estimated mammary gland content ratio was significantly higher in non-visibles than in controls when the overall sample, the patient age was ≥40 years and the CBT was ≥40 mm (p < 0.05). The differences in the average estimated mammary gland content ratios in the controls and non-visibles for the overall sample was 7.54%, the differences in patients aged 40-49, 50-59, and ≥60 years were 6.20%, 7.48%, and 4.78%, respectively, and the differences in those with a CBT of 40-49, 50-59, and ≥60 mm were 6.67%, 9.71%, and 16.13%, respectively. In evaluating mammary gland content ratio ≥50% groups, we also found positive correlations for non-visibles when controls were used as the baseline for the overall sample, in patients aged 40-59 years, and in those with a CBT ≥40 mm (p < 0.05). The corresponding odds ratios were ≥2.20, with a maximum value of 4.36.

Conclusion

The study findings highlight an estimated mammary gland content ratio of ≥50% in patients aged 40-59 years or in those with ≥40 mm CBT could be indicative factors for non-visibles.

Lifestyle and host determinants of antitumor immunity and cancer health disparities

Lifestyle factors exert profound effects on host physiology and immunology. Disparities in cancer outcomes persist as a complex and multifaceted challenge, necessitating a comprehensive understanding of the interplay between host environment and antitumor immune responses. Determinants of health - such as obesity, diet, exercise, stress, or sleep disruption - have the potential for modification, yet some exert long-lasting effects and may challenge the notion of complete reversibility. Herein we review intersectional considerations of lifestyle immunity and the impact on tumor immunology and disparities in cancer outcomes, with a focus on obesity.

Mammographic Breast Density and Risk of Ovarian Cancer in Korean Women

BACKGROUND

This study aimed to investigate the potential association between mammographic breast density and ovarian cancer risk.

METHODS

This retrospective cohort study included women ≥40 years of age who underwent a mammography screening from 2009 to 2014. Breast density was assessed using the Breast Imaging-Reporting and Data System. The primary outcome was ovarian cancer development, and the cases were recorded until 2020. Cox proportional hazards regression was used to assess the association between breast density and ovarian cancer development. Subgroup analyses stratified by age, menopausal status, and body mass index (BMI) were conducted.

RESULTS

Of the 8,556,914 women included in this study, 9,246 ovarian cancer events were recorded during a median follow-up period of 10 years (interquartile range, 8.1-11.0 years). Compared with women with almost entirely fat density, those with scattered fibroglandular density, heterogeneous density, and extreme density had an increased risk of ovarian cancer with adjusted HRs of 1.08 [95% confidence interval (CI), 1.02-1.15], 1.16 (95% CI, 1.09-1.24), and 1.24 (95% CI, 1.15-1.34), respectively. The strongest association was observed in the ≥60 years age group; subgroup analysis indicated a significant increase in association between the higher-density category and ovarian cancer risk, regardless of BMI or menopausal status.

CONCLUSIONS

Higher levels of breast density are associated with an increased risk of ovarian cancer.

IMPACT

Breast density may have a relationship with ovarian cancer risk and could be used to assess future risk.

Mammographic breast density and cardiovascular disease risk in women

AIMS

We aimed to determine the predictive role of mammographic breast density in addition to the Framingham Risk Score (FRS) on subsequent CVD events in women.

METHODS AND RESULTS

This cohort study included 4,268,579 women aged ≥40 years who underwent mammography screening between 2009 and 2010 with follow-up until 2020. Breast density was reported following the Breast Imaging Reporting and Data System. Primary outcomes included coronary heart disease, cerebrovascular disease, peripheral arterial disease, and heart failure. The incremental predictive ability of breast density added to the FRS model was assessed using the ROC and net reclassification index (NRI) among all women and strata based on FRS risk categories (<5% as low-risk, 5%-10% as moderate-risk, and ≥10% as high-risk). In total, 135,475 CVD events were recorded after a median follow-up of 10.9 years. A lower category of breast density was associated with a higher risk of CVD. Compared to the extremely dense breast group, the hazard ratios (95% CI) for CVDs were 1.12 (1.09-1.14), 1.19 (1.17-1.22), and 1.29 (1.26-1.32) in women with heterogeneously dense, scattered fibroglandular densities, and almost entirely fat breast density, respectively. Adding breast density to the FRS showed a slight improvement in AUROC but a modest improvement in NRI; the C-statistic difference was 0.083% (95% CI 0.069-0.096) with a 7.15% (6.85-7.69) increase in NRI, with the strongest improvement observed in the low-risk group.

CONCLUSIONS

Mammographic breast density is an independent predictor of incident CVD among women. The addition of mammographic breast density to FRS improves the prediction of CVDs, especially in low-risk individuals.

Estimating the joint effect of household solid fuel use and social isolation on depression among middle-aged and older adults in China

BACKGROUND

Household solid fuel use and social isolation are reported to increase the risk of depressive symptoms, but their joint effect has not yet been examined. This study aimed to explore the separate and joint effects of household solid fuel use and social isolation on depression.

METHODS

We used data from the latest four waves (2011-2018) of the China Health and Retirement Longitudinal Study (CHARLS). Depression was defined as a score of ≥12 using the Center for Epidemiologic Studies Depression Scale (CES-D 10). Cox proportional hazards models were applied to explore the separate and joint associations of household solid fuel use and social isolation with incident depression.

RESULTS

During the seven-year follow-up, 2793 (30.25 %) out of the 9232 participants were identified with depressive symptoms. Solid fuel use for household heating or cooking was significantly associated with more hazards of depressive symptoms after adjusting for potential confounders (cooking: HR = 1.280, 95 % CI = 1.175-1.394; heating: HR = 1.142, 95 % CI = 1.054-1.238). High social isolation at baseline was also a significant predictor of incident depressive symptoms (HR = 1.139, 95 % CI = 1.053-1.231). Participants exposed to both solid fuel use and high social isolation were found to have higher hazards of experiencing depressive symptoms than those exposed to none or only one of these two risk factors (heating: HR for 'solid fuel use + high social isolation'=1.308 versus HR for other groups = 1-1.185; cooking: HR for 'solid fuel use + high social isolation' = 1.430 versus HR for other groups = 1-1.255).

CONCLUSION

Household solid fuel use and social isolation were separately and jointly associated with higher risks of incident depression. Appropriate interventions to reduce solid fuel use and social isolation are recommended to improve the psychological health among middle-aged and older adults in China.

Trajectories of body mass index in adulthood and risk of subtypes of postmenopausal breast cancer

BACKGROUND

Body fatness is a dynamic exposure throughout life. To provide more insight into the association between body mass index (BMI) and postmenopausal breast cancer, we aimed to examine the age at onset, duration, intensity, and trajectories of body fatness in adulthood in relation to risk of breast cancer subtypes.

METHODS

Based on self-reported anthropometry in the prospective Norwegian Women and Cancer Study, we calculated the age at onset, duration, and intensity of overweight and obesity using linear mixed-effects models. BMI trajectories in adulthood were modeled using group-based trajectory modeling. We used Cox proportional hazards models to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for the associations between BMI exposures and breast cancer subtypes in 148,866 postmenopausal women.

RESULTS

A total of 7223 incident invasive postmenopausal breast cancer cases occurred during follow-up. Increased overweight duration and age at the onset of overweight or obesity were associated with luminal A-like breast cancer. Significant heterogeneity was observed in the association between age at overweight and overweight duration and the intrinsic-like subtypes (pheterogeneity 0.03). Compared with women who remained at normal weight throughout adulthood, women with a descending BMI trajectory had a reduced risk of luminal A-like breast cancer (HR 0.54, 95% CI 0.33-0.90), whereas women with ascending BMI trajectories were at increased risk (HR 1.09; 95% CI 1.01-1.17 for "Normal-overweight"; HR 1.20; 95% CI 1.07-1.33 for "Normal-obesity"). Overweight duration and weighted cumulative years of overweight and obesity were inversely associated with luminal B-like breast cancer.

CONCLUSIONS

In this exploratory analysis, decreasing body fatness from obesity in adulthood was inversely associated with overall, hormone receptor-positive and luminal A-like breast cancer in postmenopausal women. This study highlights the potential health benefits of reducing weight in adulthood and the health risks associated with increasing weight throughout adult life. Moreover, our data provide evidence of intrinsic-like tumor heterogeneity with regard to age at onset and duration of overweight.

Personalized Breast Cancer Screening: A Risk Prediction Model Based on Women Attending BreastScreen Norway

BACKGROUND

We aimed to develop and validate a model predicting breast cancer risk for women targeted by breast cancer screening.

METHOD

This retrospective cohort study included 57,411 women screened at least once in BreastScreen Norway during the period from 2007 to 2019. The prediction model included information about age, mammographic density, family history of breast cancer, body mass index, age at menarche, alcohol consumption, exercise, pregnancy, hormone replacement therapy, and benign breast disease. We calculated a 4-year absolute breast cancer risk estimates for women and in risk groups by quartiles. The Bootstrap resampling method was used for internal validation of the model (E/O ratio). The area under the curve (AUC) was estimated with a 95% confidence interval (CI).

RESULTS

The 4-year predicted risk of breast cancer ranged from 0.22-7.33%, while 95% of the population had a risk of 0.55-2.31%. The thresholds for the quartiles of the risk groups, with 25% of the population in each group, were 0.82%, 1.10%, and 1.47%. Overall, the model slightly overestimated the risk with an E/O ratio of 1.10 (95% CI: 1.09-1.11) and the AUC was 62.6% (95% CI: 60.5-65.0%).

CONCLUSIONS

This 4-year risk prediction model showed differences in the risk of breast cancer, supporting personalized screening for breast cancer in women aged 50-69 years.

Physiological and Environmental Factors Affecting Cancer Risk and Prognosis in Obesity

Obesity results from a chronic excessive accumulation of adipose tissue due to a long-term imbalance between energy intake and expenditure. Available epidemiological and clinical data strongly support the links between obesity and certain cancers. Emerging clinical and experimental findings have improved our understanding of the roles of key players in obesity-associated carcinogenesis such as age, sex (menopause), genetic and epigenetic factors, gut microbiota and metabolic factors, body shape trajectory over life, dietary habits, and general lifestyle. It is now widely accepted that the cancer-obesity relationship depends on the site of cancer, the systemic inflammatory status, and microenvironmental parameters such as levels of inflammation and oxidative stress in transforming tissues. We hereby review recent advances in our understanding of cancer risk and prognosis in obesity with respect to these players. We highlight how the lack of their consideration contributed to the controversy over the link between obesity and cancer in early epidemiological studies. Finally, the lessons and challenges of interventions for weight loss and better cancer prognosis, and the mechanisms of weight gain in survivors are also discussed.

Automated Estimation of Mammary Gland Content Ratio Using Regression Deep Convolutional Neural Network and the Effectiveness in Clinical Practice as Explainable Artificial Intelligence

Recently, breast types were categorized into four types based on the Breast Imaging Reporting and Data System (BI-RADS) atlas, and evaluating them is vital in clinical practice. A Japanese guideline, called breast composition, was developed for the breast types based on BI-RADS. The guideline is characterized using a continuous value called the mammary gland content ratio calculated to determine the breast composition, therefore allowing a more objective and visual evaluation. Although a discriminative deep convolutional neural network (DCNN) has been developed conventionally to classify the breast composition, it could encounter two-step errors or more. Hence, we propose an alternative regression DCNN based on mammary gland content ratio. We used 1476 images, evaluated by an expert physician. Our regression DCNN contained four convolution layers and three fully connected layers. Consequently, we obtained a high correlation of 0.93 (p < 0.01). Furthermore, to scrutinize the effectiveness of the regression DCNN, we categorized breast composition using the estimated ratio obtained by the regression DCNN. The agreement rates are high at 84.8%, suggesting that the breast composition can be calculated using regression DCNN with high accuracy. Moreover, the occurrence of two-step errors or more is unlikely, and the proposed method can intuitively understand the estimated results.

Levonorgestrel intrauterine system and breast cancer risk: An updated systematic review and meta-analysis of observational studies

Objectives

Levonorgestrel intrauterine sustained release system (LNG-IUS) is an intrauterine hormonal contraceptive device. Breast cancer (BC) was the most common type of cancer in women in the world in 2020. The relationship between LNG-IUS and BC is controversial. We conducted an updated meta-analysis (larger sample capacity and including Asian data) to explore whether LNG-IUS can increase the risk of BC.

Study design

We performed a thorough review of peer-reviewed publications from January 2005 through November 2022 using combinations of search terms for BC risk and LNG-IUS in the PubMed, Cochrane, Embase, Science Direct, and Web of Science databases. Studies reporting BC risk estimates among users of LNG-IUS were included according to the PRISMA criteria. Two authors independently evaluated all studies identified from the databases using Endnote software, and a third author resolved disagreements. The quality of evidence was evaluated using the Newcastle‒Ottawa Scale (NOS). A funnel plot was generated to assess publication bias.

Results

We identified 3029 studies; 12 studies were included in our systematic review, and 6 studies involving 261,221 women were included in our meta-analysis. Two subgroup analyses were performed for different study designs. A total of 190,475 women were included in the meta-analysis of cohort studies, and the results were RR = 0.80 (95% CI 0.57-1.11, Z = 1.33, P = 0.18 > 0.05). The meta-analysis of the case‒control studies included 70,746 women, and the results were OR = 1.38 (95% CI 0.98-1.94, Z = 1.85, P = 0.06 > 0.05).

Conclusions

Evidence of an increased risk of BC was not observed among LNG-IUS users.

Implications

There are inconsistencies in existing studies that prevent us from confirming whether LNG-IUS can increase the risk of BC. Our updated meta-analysis preliminarily suggested that LNG-IUS did not increase the risk of BC, providing evidence for more clinically safe use and thus providing a better choice for contraception.

Association of Breast Cancer Family History With Breast Density Over Time in Korean Women

IMPORTANCE

Evidence suggests that women with a family history of breast cancer (FHBC) in first-degree relatives have a higher level of breast density; however, studies of premenopausal women remain limited.

OBJECTIVE

To investigate the association between FHBC and mammographic breast density and breast density changes among premenopausal women.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used population-based data obtained from the National Health Insurance Service-National Health Information Database of Korea. We included premenopausal women aged 40 to 55 years who underwent mammography for breast cancer screening once between January 1, 2015, and December 31, 2016 (n = 1 174 214), and women who underwent mammography twice (first in 2015-2016 and again between January 1, 2017 and December 31, 2018) (n = 838 855).

EXPOSURES

Family history of breast cancer was assessed using a self-reported questionnaire, which included information on FHBC in the mother and/or sister.

MAIN OUTCOMES AND MEASURES

Breast density, based on the Breast Imaging Reporting and Data System, was categorized as dense (heterogeneously or extremely dense) and nondense (almost entirely fat or scattered fibroglandular areas). Multivariate logistic regression was used to assess the association among FHBC, breast density, and changes in breast density from the first to second screening. Data analysis was performed from June 1 to September 31, 2022.

RESULTS

Of the 1 174 214 premenopausal women, 34 003 (2.4%; mean [SD] age, 46.3 [3.2] years) reported having FHBC among their first-degree relatives, and 1 140 211 (97.1%; mean [SD] age, 46.3 [3.2] years) reported no FHBC. Odds of having dense breasts was 22% higher (adjusted odds ratio [aOR], 1.22; 95% CI, 1.19-1.26) in women with FHBC than in women without FHBC, and the association varied by affected relatives: mother alone (aOR, 1.15; 95% CI, 1.10-1.21), sister alone (aOR, 1.26; 95% CI, 1.22-1.31), and both mother and sister (aOR, 1.64; 95% CI, 1.20-2.25). Among women with fatty breasts at baseline, the odds of developing dense breasts was higher in women with FHBC than in those without FHBC (aOR, 1.19; 95% CI, 1.11-1.26), whereas among women with dense breasts, higher odds of having persistently dense breasts were observed in women with FHBC (aOR, 1.11; 95% CI, 1.05-1.16) than in those without FHBC.

CONCLUSIONS AND RELEVANCE

In this cohort study of premenopausal Korean women, FHBC was positively associated with an increased incidence of having increased or persistently dense breasts over time. These findings suggest the need for a tailored breast cancer risk assessment for women with FHBC.

Association of Longitudinal Mammographic Breast Density Changes with Subsequent Breast Cancer Risk

Background Although Breast Imaging Reporting and Data System (BI-RADS) density classification has been used to assess future breast cancer risk, its reliability and validity are still debated in literature. Purpose To determine the association between overall longitudinal changes in mammographic breast density and breast cancer risk stratified by menopausal status. Materials and Methods In a retrospective cohort study using the Korean National Health Insurance Service database, women aged at least 40 years without a history of cancer who underwent three consecutive biennial mammographic screenings in 2009-2014 were followed up through December 2020. Participants were divided according to baseline breast density: fatty (BI-RADS categories a, b) versus dense (BI-RADS categories c, d) and then into subgroups on the basis of changes from the first to second and from second to third screenings. Women without change in breast density were used as the reference group. Main outcomes were incident breast cancer events, both invasive breast cancer and ductal carcinoma in situ. Cox proportion hazard regression was used to calculate the hazard ratio (HR) with adjustment for other covariables. Results Among 2 253 963 women (mean age, 59 years ± 9) there were 22 439 detected breast cancers. Premenopausal women with fatty breasts at the first screening had a higher risk of breast cancer as density increased in the second and third screenings (fatty-to-dense HR, 1.45 [95% CI: 1.27, 1.65]; dense-to-fatty HR, 1.53 [95% CI: 1.34, 1.74]; dense-to-dense HR, 1.93 [95% CI: 1.75, 2.13]). In premenopausal women with dense breasts at baseline, those in whom density continuously decreased had a 0.62-fold lower risk (95% CI: 0.56, 0.69). Similar results were observed in postmenopausal women, remaining significant after adjustment for baseline breast density or changes in body mass index (fatty-to-dense HR, 1.50 [95% CI: 1.39, 1.62]; dense-to-fatty HR, 1.42 [95% CI: 1.31, 1.53]; dense-to-dense HR, 1.62 [95% CI: 1.51, 1.75]). Conclusion In both premenopausal and postmenopausal women undergoing three consecutive biennial mammographic screenings, a consecutive increase in breast density augmented the future breast cancer risk whereas a continuous decrease was associated with a lower risk. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Kataoka et al in this issue.

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.

Body Mass Index Is Inversely Associated with Risk of Postmenopausal Interval Breast Cancer: Results from the Women’s Health Initiative

Interval breast cancer refers to cancer diagnosed after a negative screening mammogram and before the next scheduled screening mammogram. Interval breast cancer has worse prognosis than screening-detected cancer. Body mass index (BMI) influences the accuracy of mammography and overall postmenopausal breast cancer risk, yet how is obesity associated with postmenopausal interval breast cancer incidence is unclear. The current study included cancer-free postmenopausal women aged 50–79 years at enrollment in the Women’s Health Initiative who were diagnosed with breast cancer during follow-up. Analyses include 324 interval breast cancer cases diagnosed within one year after the participant’s last negative screening mammogram and 1969 screening-detected breast cancer patients. Obesity (BMI ≥ 30 kg/m2) was measured at baseline. Associations between obesity and incidence of interval cancer were determined by sequential logistic regression analyses. In multivariable-adjusted models, obesity was inversely associated with interval breast cancer risk [OR (95% CI) = 0.65 (0.46, 0.92)]. The inverse association persisted after excluding women diagnosed within 2 years [OR (95% CI) = 0.60 (0.42, 0.87)] or 4 years [OR (95% CI) = 0.56 (0.37, 0.86)] of enrollment, suggesting consistency of the association regardless of screening practices prior to trial entry. These findings warrant confirmation in studies with body composition measures.

Mammographic breast density, body mass index and risk of breast cancer in Korean women aged 75 years and older

Mammographic breast density and body mass index (BMI) are strong risk factors of breast cancer, but few studies have investigated these factors in older women. Our study assessed the association between breast density, BMI and the breast cancer risk among women aged ≥75 years. We included women who underwent breast cancer screening between 2009 and 2014 and were followed up until 2020. Breast density was measured using Breast Imaging Reporting and Data System. BMI was classified into three groups: <23, 23 to <25 and ≥25. Cox proportional hazards models were used to estimate the association of breast density and BMI with breast cancer risk. In 483 564 women, 1885 developed breast cancer. The 5-year incidence increased with an increase in breast density and BMI. Increase in breast density was associated with an increased breast cancer risk in all BMI categories: among women with BMI <23, those with heterogeneous/extreme density had a 2.98-fold (95% CI: 2.23-3.80) increased risk of breast cancer compared to those with entirely fatty breasts. An increase in BMI was associated with increased breast cancer risk in women with the same breast density in all density categories. When the combined associations of breast density and BMI on the risk of breast cancer were considered, women with a BMI ≥25 and heterogeneous/extreme breast density had a 5.35-fold (95% CI: 4.26-6.72) increased risk of breast cancer compared to women with a BMI <23 and fatty breasts. Women aged ≥75 years, with dense breasts, regardless of BMI status, might benefit from a tailored screening strategy for early detection of breast cancer.

The role of obesity and bariatric surgery-induced weight loss in breast cancer

Obesity is a complex metabolic condition considered a worldwide public health crisis, and a deeper mechanistic understanding of obesity-associated diseases is urgently needed. Obesity comorbidities include many associated cancers and are estimated to account for 20% of female cancer deaths in the USA. Breast cancer, in particular, is associated with obesity and is the focus of this review. The exact causal links between obesity and breast cancer remain unclear. Still, interactions have emerged between body mass index, tumor molecular subtype, genetic background, and environmental factors that strongly suggest obesity influences the risk and progression of certain breast cancers. Supportive preclinical research uses various diet-induced obesity models to demonstrate that weight loss, via dietary interventions or changes in energy expenditure, reduces the onset or progression of breast cancers. Ongoing and future studies are now aimed at elucidating the underpinning mechanisms behind weight-loss-driven observations to improve therapy and outcomes in patients with breast cancer and reduce risk. This review aims to summarize the rapidly emerging literature on obesity and weight loss strategies with a focused discussion of bariatric surgery in both clinical and preclinical studies detailing the complex interactions between metabolism, immune response, and immunotherapy in the setting of obesity and breast cancer.