Mammographic breast density and breast cancer risk by menopausal status, postmenopausal hormone use and a family history of breast cancer

Abstract Background Well-tolerated and commonly used medications are increasingly assessed for reducing breast cancer risk. These include metformin and statins, both linked to reduced hormone availability and cell proliferation or growth and sometimes prescribed concurrently. We investigated independent and joint associations of these medications with mammographic breast density (MBD), a useful biomarker for the effect of chemopreventive agents on breast cancer risk. Methods Using data from a cross-sectional study of 770 women (78% Hispanic, aged 40–61 years, in a mammography cohort with high cardiometabolic burden), we examined the association of self-reported “ever” use of statins and metformin with MBD measured via clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications (relative risk regression) and continuous semi-automated percent and size of dense area (Cumulus) (linear regression), adjusted for age, body mass index, education, race, menopausal status, age at first birth, and insulin use. Results We observed high statin (27%), metformin (13%), and combination (9%) use, and most participants were overweight/obese (83%) and parous (87%). Statin use was associated with a lower likelihood of high density BI-RADS (RR = 0.60, 95% CI = 0.45 to 0.80), percent dense area (PD) (β = − 6.56, 95% CI = − 9.05 to − 4.06), and dense area (DA) (β = − 9.05, 95% CI = − 14.89 to − 3.22). Metformin use was associated with lower PD and higher non-dense area (NDA), but associations were attenuated by co-medication with statins. Compared to non-use of either medication, statin use alone or with metformin were associated with lower PD and DA (e.g., β = − 6.86, 95% CI: − 9.67, − 4.05 and β = − 7.07, 95% CI: − 10.97, − 3.17, respectively, for PD) and higher NDA (β = 25.05, 95% CI: 14.06, 36.03; β = 29.76, 95% CI: 14.55, 44.96, respectively). Conclusions Statin use was consistently associated with lower MBD, measured both through clinical radiologist assessment and continuous relative and absolute measures, including dense area. Metformin use was associated with lower PD and higher NDA, but this may be driven by co-medication with statins. These results support that statins may lower MBD but need confirmation with prospective and clinical data to distinguish the results of medication use from that of disease.

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Gene methylation in random FNA samples as biomarkers for breast cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.15_suppl.518 ◽

2012 ◽

Vol 30 (15_suppl) ◽

pp. 518-518

Author(s):

Vered Stearns ◽

Seema Ahsan Khan ◽

Mary Jo Fackler ◽

Robert T. Chatterton ◽

Lisa K. Jacobs ◽

...

Keyword(s):

Breast Cancer ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Breast Density ◽

Menopausal Status ◽

Life Time ◽

Wilcoxon Test ◽

Mammographic Breast Density ◽

Gene Methylation ◽

Cytologic Atypia

518 Background: Current methods to determine breast cancer risk are insufficiently sensitive to select women most likely to benefit from preventive strategies. We hypothesized that candidate gene promoter hypermethylation may provide an individualized risk profile. We performed a prospective study to determine whether DNA cumulative methylation index (CMI) varies by menstrual phase or menopausal status, and to correlate CMI with established risk factors. Methods: We obtained random fine needle aspiration (rFNA) samples from healthy women age 35-60 and determined their menopausal and menstrual status, lifetime Gail risk, mammographic breast density, and cytologic atypia assessed as the Masood score. We evaluated CMI of 11 candidate genes in rFNA cells using the Quantitative Multiplex Methylation-Specific PCR (QM-MSP) technique. We used Wilcoxon test and ANOVA model to compare CMI across menopausal and menstrual (follicular, mid-cycle, luteal) categories, respectively. We used linear regression model to adjust for age and BMI. Methylation scores were log-transformed in the analysis. Results: We enrolled 390 women at the Avon Breast Centers at Johns Hopkins and Northwestern, the majority through the Love/Avon Army of Women, and 380 completed study procedures. Median age 50 (36-60), mean BMI 28 (18.7-50.8), 52% were postmenopausal. Mean life-time Gail risk 14.6 (5.6-54.1), mean percent mammographic density 19.6 (2.5-72.8), and mean Masood score (N=354) 13.6 (7-18). QM-MSP analysis was completed on 229 samples. We did not observe differences in CMI among menopausal (P=0.4895) or menstrual categories (P=0.2333). There was no association between CMI and life-time Gail risk (P=0.706) or breast density (P=0.4116). We observed a significant correlation between CMI and Masood score (P=0.0167). Conclusions: CMI correlates with degree of cytologic atypia and is potentially a robust indicator of breast cancer risk since it does not vary with menstrual or menopausal status. Next, we will select genes that best reflect changes in the clinical parameters to create a gene methylation signature that will be validated in other studies and correlated with breast cancer risk.

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The relationship of breast density, BMI, and menopausal status in mammography and MRI.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.27_suppl.36 ◽

2012 ◽

Vol 30 (27_suppl) ◽

pp. 36-36 ◽

Cited By ~ 1

Author(s):

Jennifer Chun ◽

Ana Paula Refinetti ◽

Ana Klautau Leite ◽

Freya Ruth Schnabel ◽

Tsivia Hochman ◽

...

Keyword(s):

Breast Cancer ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Breast Density ◽

Menopausal Status ◽

Mammographic Breast Density ◽

Strong Positive Correlation ◽

Background Parenchymal Enhancement ◽

Increased Risk ◽

The Relationship

36 Background: Mammographic breast density (BD) is associated with a 4- to 6-fold increased risk for developing breast cancer. A previous study has shown that background parenchymal enhancement (BPE) as measured on MRI can be correlated with breast cancer risk. Being overweight or obese is also an established risk factor for breast cancer. The purpose of this study was to evaluate the relationship between BD, BPE, FGT (assessment of fibroglandular tissue with contiguous MR images), and BMI in pre- and post-menopausal women. Methods: The Breast Cancer Database at NYU Langone Medical Center was queried and a total of 187 women had completed both screening mammograms and MRIs. Variables of interest included BD, BPE, FGT, BMI, and menopausal status. BD was defined by ACR classifications 1-4. FGT was assessed on a similar scale 1-4. BPE was categorized as minimal, mild, moderate, or marked. BMI (kg/m2) was grouped as underweight (≤18), normal (19-24), overweight (25-29), and obese (≥30). Statistical analyses were performed using Spearman Correlation Coefficients and Cochran Mantel Haenszel tests. Results: The median age in our cohort was 51 years (range 22-87 years). The majority were Caucasian (71%) with early stage breast cancers (75%). There was no correlation between BD and BPE (r=0.132) and a weak correlation between BPE and FGT (r=0.312). However, there was a strong positive correlation between BD and FGT (r=0.733). After adjusting for menopausal status, these correlations remained the same. When we stratified by BMI, we found the strongest positive association between BD and FGT among women with BMI≥25 (r=0.715). Conclusions: In our cohort of newly diagnosed breast cancer patients, BD and BPE were not correlated, even after adjusting for menopausal status. This implies that BD and BPE may represent different characteristics of breast tissue and may have different implications. We found a strong correlation between FGT and BD. This association was strongest in women who were overweight and obese. FGT is a more objective and quantitative measurement of breast density and may be more useful in quantitative breast cancer risk assessment.Further studies are necessary to determine if BPE and FGT are independent risk factors for breast cancer.

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Breast Cancer Risk by Breast Density, Menopause, and Postmenopausal Hormone Therapy Use

Journal of Clinical Oncology ◽

10.1200/jco.2009.26.4770 ◽

2010 ◽

Vol 28 (24) ◽

pp. 3830-3837 ◽

Cited By ~ 134

Author(s):

Karla Kerlikowske ◽

Andrea J. Cook ◽

Diana S.M. Buist ◽

Steve R. Cummings ◽

Celine Vachon ◽

...

Keyword(s):

Breast Cancer ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Hormone Therapy ◽

Breast Density ◽

Menopausal Status ◽

Postmenopausal Hormone Therapy ◽

Postmenopausal Hormone ◽

Estrogen Plus Progestin ◽

Very High

Purpose We determined whether the association between breast density and breast cancer risk and cancer severity differs according to menopausal status and postmenopausal hormone therapy (HT) use. Methods We collected data on 587,369 women who underwent 1,349,027 screening mammography examinations; 14,090 women were diagnosed with breast cancer. We calculated 5-year breast cancer risk from a survival model for subgroups of women classified by their Breast Imaging Reporting and Data System (BIRADS) breast density, age, menopausal status, and current HT use, assuming a body mass index of 25 kg/m2. Odds of advanced (ie, IIb, III, IV) versus early (ie, I, IIa) stage invasive cancer was calculated according to BIRADS density. Results Breast cancer risk was low among women with low density (BIRADS-1): women age 55 to 59 years, 5-year risk was 0.8% (95% CI, 0.6 to 0.9%) for non-HT users and 0.9% (95% CI, 0.7% to 1.1%) for estrogen and estrogen plus progestin users. Breast cancer risk was high among women with very high density (BIRADS-4), particularly estrogen plus progestin users: women age 55 to 59 years, 5-year risk was 2.4% (95% CI, 2.0% to 2.8%) for non-HT users, 3.0% (95% CI, 2.6% to 3.5%) for estrogen users, and 4.2% (95% CI, 3.7% to 4.6%) for estrogen plus progestin users. Advanced-stage breast cancer risk was increased 1.7-fold for postmenopausal HT users who had very high density (BIRADS-4) compared to those with average density (BIRADS-2). Conclusion Postmenopausal women with high breast density are at increased risk of breast cancer and should be aware of the added risk of taking HT, especially estrogen plus progestin.

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