Prevention of breast cancer in postmenopausal women: approaches to estimating and reducing risk

Abstract

Background: It is uncertain whether evidence supports routinely estimating a postmenopausal woman's risk of breast cancer and intervening to reduce risk.

Methods: 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.

Results: 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.

Conclusions: 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.

Figure 1

Breast density patterns. A) BI-RADS I = fatty breast (<25% dense). B) BI-RADS II = scattered densities (25%–50% dense). C) BI-RADS III = heterogeneously dense (51%–75% dense). D) BI-RADS IV = extremely dense (>75% dense). BI-RADS = Breast Imaging Reporting Data System.

Figure 2

Illustration of the quantitative estimation of breast density from a digitized image of a mammogram. The image of the breast is outlined, and the areas that exceed any certain threshold value of density are also outlined. Percent density is calculated as [(dense area%total area) x 100]. Dense tissue in this breast area of this mammogram accounts for 48% of its area.

Figure 3

Forest plots of the risk of breast cancer from placebo-controlled trials of tamoxifen or raloxifene, with pooled estimates overall and for each treatment separately. A) All invasive breast cancer. B) Estrogen receptor–positive invasive breast cancer. The solid squares are centered on the point estimate from each study, and the horizontal line through each square represents the 95% CI for the study estimate. The size of each square represents the weight of the study in the meta-analysis. The center of each diamond represents the summary estimate of the effect size, and the horizontal tips represent the 95% CI. The solid vertical line corresponds to no effect, and the dashed vertical line corresponds to the summary estimate. CI = confidence interval.