Prevention of Breast Cancer in Postmenopausal Women: Approaches to Estimating and Reducing Risk

San Francisco Coordinating Center, California Pacific Medical Center Research Institute, 94107, USA.
Journal of the National Cancer Institute (Impact Factor: 12.58). 03/2009; 101(6):384-98. DOI: 10.1093/jnci/djp018
Source: PubMed


It is uncertain whether evidence supports routinely estimating a postmenopausal woman's risk of breast cancer and intervening to reduce risk.
We systematically reviewed prospective studies about models and sex hormone levels to assess breast cancer risk and used meta-analysis with random effects models to summarize the predictive accuracy of breast density. We also reviewed prospective studies of the effects of exercise, weight management, healthy diet, moderate alcohol consumption, and fruit and vegetable intake on breast cancer risk, and used random effects models for a meta-analyses of tamoxifen and raloxifene for primary prevention of breast cancer. All studies reviewed were published before June 2008, and all statistical tests were two-sided.
Risk models that are based on demographic characteristics and medical history had modest discriminatory accuracy for estimating breast cancer risk (c-statistics range = 0.58-0.63). Breast density was strongly associated with breast cancer (relative risk [RR] = 4.03, 95% confidence interval [CI] = 3.10 to 5.26, for Breast Imaging Reporting and Data System category IV vs category I; RR = 4.20, 95% CI = 3.61 to 4.89, for >75% vs <5% of dense area), and adding breast density to models improved discriminatory accuracy (c-statistics range = 0.63-0.66). Estradiol was also associated with breast cancer (RR range = 2.0-2.9, comparing the highest vs lowest quintile of estradiol, P < .01). Most studies found that exercise, weight reduction, low-fat diet, and reduced alcohol intake were associated with a decreased risk of breast cancer. Tamoxifen and raloxifene reduced the risk of estrogen receptor-positive invasive breast cancer and invasive breast cancer overall.
Evidence from this study supports screening for breast cancer risk in all postmenopausal women by use of risk factors and breast density and considering chemoprevention for those found to be at high risk. Several lifestyle changes with the potential to prevent breast cancer should be recommended regardless of risk.

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Available from: Victor Vogel, Oct 01, 2015
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    • "Breast cancer is the leading diagnosed cancer and the most common cause of cancer-related death in women worldwide [1]-[3]. Several chemotherapeutic drugs are used in the treatment of breast cancer to reduce or suppress the growth of cancerous cells [1] [4]-[7]. "
    Journal of Biophysical Chemistry 01/2015; 06(01):1-13. DOI:10.4236/jbpc.2015.61001
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    • "It is estimated that women with an increased breast density have 4 to 6 times higher risk of breast cancer than women with less dense breasts [1,2,3]. The relative risk of cancer related to breast density is greater than most traditional risk factors such as nulliparity and early menarche [4,5]. Recently, mammographic density has also been investigated as a surrogate marker of breast cancer treatment outcomes [6,7,8]. "
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    ABSTRACT: Purpose The reliability of the quantitative measurement of breast density with a semi-automated thresholding method (Cumulus™) has mainly been investigated with film mammograms. This study aimed to evaluate the intrarater reproducibility of percent density (PD) by Cumulus™ with digital mammograms. Methods This study included 1,496 craniocaudal digital mammograms from the unaffected breast of breast cancer patients. One rater reviewed each mammogram and estimated the PD using the Cumulus™ method. All images were reassessed by the same rater 1 month later without reference to the previously assigned values. The repeatability of the PD was evaluated by an intraclass correlation coefficient (ICC). All patients were grouped based on their body mass index (BMI), age, family history of breast cancer, breastfeeding history and breast area (calculated with Cumulus™), and subgroup analysis for the ICC of each group was performed. All patients were categorized by their Breast Imaging Reporting and Data System (BI-RADS) density pattern, and the mean and standard deviation of the PD by each BI-RADS categories were compared. Results The ICC for the PD was 0.94, indicating excellent repeatability. The discrepancy between the paired PD values ranged from 0 to 23.93, with an average of 3.90 (standard deviation=3.39). The subgroup ICCs for the PD ranged from 0.88 to 0.96, indicating excellent reliability in all subgroups regardless of patient variables. The ICCs of the PD for the high-risk (BI-RADS 3 and 4) and low-risk (BI-RADS 1 and 2) groups were 0.90 and 0.88, respectively. Conclusion This study suggests that PD calculated with digital mammograms has an acceptable reliability regardless of patient age, BMI, family history of breast cancer, breastfeeding history, breast size, and BI-RADS density pattern.
    Journal of Breast Cancer 06/2014; 17(2):174-9. DOI:10.4048/jbc.2014.17.2.174 · 1.58 Impact Factor
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    • "Continuous and objective measures of breast density, such as percentage areal [16] and volumetric [17] mammographic density, were developed to improve on the semi-quantitative and subjective nature of scoring. Percent areal density has been shown to have a slightly stronger risk association with breast cancer than categorical scores [18], but does not represent the true volume of dense tissue, could have errors associated with its two-dimensional projection, and requires a trained reader [19]. "
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    ABSTRACT: Clinical scores of mammographic breast density are highly subjective. Automated technologies for mammography exist to quantify breast density objectively, but the technique that most accurately measures the quantity of breast fibroglandular tissue is not known. To compare the agreement of three automated mammographic techniques for measuring volumetric breast density with a quantitative volumetric MRI-based technique in a screening population. Women were selected from the UCSF Medical Center screening population that had received both a screening MRI and digital mammogram within one year of each other, had Breast Imaging Reporting and Data System (BI-RADS) assessments of normal or benign finding, and no history of breast cancer or surgery. Agreement was assessed of three mammographic techniques (Single-energy X-ray Absorptiometry [SXA], Quantra, and Volpara) with MRI for percent fibroglandular tissue volume, absolute fibroglandular tissue volume, and total breast volume. Among 99 women, the automated mammographic density techniques were correlated with MRI measures with R(2) values ranging from 0.40 (log fibroglandular volume) to 0.91 (total breast volume). Substantial agreement measured by kappa statistic was found between all percent fibroglandular tissue measures (0.72 to 0.63), but only moderate agreement for log fibroglandular volumes. The kappa statistics for all percent density measures were highest in the comparisons of the SXA and MRI results. The largest error source between MRI and the mammography techniques was found to be differences in measures of total breast volume. Automated volumetric fibroglandular tissue measures from screening digital mammograms were in substantial agreement with MRI and if associated with breast cancer could be used in clinical practice to enhance risk assessment and prevention.
    PLoS ONE 12/2013; 8(12):e81653. DOI:10.1371/journal.pone.0081653 · 3.23 Impact Factor
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