It has been estimated that women in the United States have a 12% lifetime risk of developing breast cancer. While overall cancer incidence rate remained stable for women in the past few decades, there was a 0.3% increase in the incidence of breast cancer since 2006 (1). This trend is seen in the developed countries and could at least in part be a consequence of the obesity epidemic, as well as declining parity.

Traditional risk factors such as gender, increasing age, family history of breast cancer, and reproductive history (early menarche and late menopause, fewer pregnancies, late childbearing, lack of breastfeeding) are considered as pillars of risk assessment (2). The true risk however is much broader (Fig. 5-1). This chapter will highlight new data that accumulated in the last decade in cancer risk.

Approximately 5% to 10% of breast cancer cases are inheritable and are driven by aberrant genes. Inherited breast cancer tends to occur at a younger age than breast cancer in women without a genetic predisposition. Recent advances in genotyping and next generation sequencing found that germline mutations and somatic mutations interact with each other to drive carcinogenesis. There is a dynamic interaction between the cancer genome and the host immune system which determines the tumor growth rate and metastatic potential.

Lifestyle is considered an increasingly important contributing factor to breast cancer etiology. Cohort studies link overweight and obesity, inactivity, metabolic syndrome, and alcohol use to breast cancer. The impact of obesity on breast cancer risk differs across menopausal status and disease subtypes. Current evidence suggests that a high BMI associates with a reduced risk of estrogen receptor (ER)–positive premenopausal breast cancer, but strongly correlates with an increased risk after menopause (3). Breast cancers occurring in obese premenopausal women tend to be ER-negative and triple-negative subtypes (4). Even in women with normal BMI, high body fat levels were associated with elevated risk of postmenopausal breast cancer (5).

Alcohol intake is a recognized risk factor in women for breast cancer. Each unit of alcohol consumption (284 mL of 4% beer, 80 mL of 12% wine, or 25 mL of 40% spirit) daily is estimated to increase the risk by 2% to 12%. The risk is thought to be related to acetaldehyde-induced DNA strand deletions, chromosomal aberrations, and increased estrogen and prolactin receptor activity (6).

How does composition of diet matter in breast cancer risk? Recent reviews linked high fiber intake with a lower risk of breast cancer, with a 5% reduction in every 10 g of fiber per day. Soluble fiber appears the most protective by reducing the reabsorption of estrogens and androgens in the bowel hence, their circulating level and effect on insulin sensitivity. Meat consumption confer a slightly increased risk: 4% increase with each additional 100 g of red meat per day and 3% increase with each additional 30 g of processed meat per day (7). Marine omega-3 fats are associated with reduced breast cancer risk; each
additional 0.7 g of marine omega-3 polyunsaturated fat per week reduces the risk by 5%. Many studies examined the link between soy and breast cancer. Soy foods contain isoflavones with weak estrogenic and antiestrogenic effect as well as antiproliferative effect on cell cultures. Natural soy food intake (but not over-the-counter isoflavone supplements) showed lowering breast cancer risk: intake of 5 g of soy protein per day (170 mL of soymilk) was associated with a 4% reduction in risk. Vitamin supplement use did not yield any beneficial effect (8).

Emerging data suggests that smoking during adolescence or early adulthood increases later risk of breast cancer because of heightened susceptibility to chemical carcinogens before full differentiation of the breast (7). The effect of smoking appears to be mainly linked to ER-positive breast cancers.

Breast density affects the risk of breast cancer. The ACR Breast Imaging Reporting and Data System (BI-RADS) differentiates four categories of breast composition: a) the breasts are almost entirely fatty; b) scattered fibroglandular tissue; c) heterogeneously dense; d) extremely dense tissue. Women with breast composition category d (extreme breast density) have a four- to sixfold increased risk for breast cancer than those with BI-RADS breast composition category a (fatty tissue) (9).

Reproductive factors have long been recognized in breast cancer development. Studies of parity and breast cancer risk had variable results. Some have reported a protective effect of younger age at first childbirth and higher risk with first live birth at older ages. However, a recent pooled analysis evaluating the cancer risk after childbirth reported increased risk postpartum. Compared with women who had not given birth, parous women had a 1.8-fold elevated breast cancer risk that peaked around 5 years after childbirth and persisted for 20 years (10). The proposed underlying mechanism is tumor-promoting microenvironment during pregnancy-induced proliferation and the postpartum breast microenvironment (lactational involution) facilitating cancer cell migration and metastases.

In the general population, oral contraceptive (OCP) use has been associated with a slightly higher breast cancer risk that appears to decrease after cessation of OCPs. A recent prospective cohort study using contemporary hormonal contraception found a 1.2-fold increased relative risk (RR) of breast cancer (1.09 with less than 1 year of OCP use to 1.38 with more than 10 years of use). Progesterone-only intrauterine system posed similar risk (RR = 1.21). The absolute increase in risk, however, was small: 13 per 100,000 person-years or 1 extra breast cancer for every 7,690 women using hormonal contraception for 1 year (11). The addition of progestin appears to increase the risk of breast cancer among postmenopausal women who receive hormone therapy (12).

Breastfeeding has been associated with an estimated 12% to 25% lower risk for premenopausal breast cancer overall and is thought to be particularly beneficial in reducing risk for ER-negative breast cancer, which is relatively more common at young ages than older ages. Although higher parity is associated with an overall increase in risk for ER-negative breast cancer, parous women who breastfeed have comparable risk to nulliparous women, suggesting that breastfeeding may mitigate parity-related increases in risk for ER-negative cancer (10).

Social factors, such as race/ethnicity, socioeconomic position (SEP), access to care matter in assessing cancer risk. While all-cause mortality rates had been steadily declined in the United States between 1999 and 2013, when mortality rates were stratified by race and SEP, it became apparent that midlife mortality was increased among one particular social group, non-Hispanic Whites with low education. Recent findings suggest an increased risk of breast cancer incidence among women born in states with Jim Crow laws (postslavery laws in place in the United States from the 1870s to 1964 that limited Black advancements and freedoms). Poverty, insurance coverage, and access to screening are modifiable risk factors that can influence cancer risk (13).

Physical activity is emerging as a modifiable risk factor for breast cancer, especially for premenopausal breast cancer. The World Cancer Research Fund and American Cancer Society (ACS) cancer prevention guidelines recommend maintaining a healthy weight, undertaking at least 150 minutes of moderate-intensity exercise per week, limiting alcohol consumption, and eating a plant-based diet. Recent expert reports estimate that successful lifestyle changes could prevent 25% to 30% of cases of breast cancer (14). It has been debated whether the reduction of the risk of breast cancer with physical activity is attributable, in part, to its positive effect on weight and body composition. Studies showed that the relationship between physical activity and breast cancer is independent of BMI, ER status, weight gain, and hormone replacement therapy (HRT) (15). A concerted effort of primary care physicians, surgeons, and oncologists is needed to increase compliance with the physical activity guidelines.

The paradigm has recently shifted from a uniform method of breast cancer screening to an individualized approach that incorporates multiple risk factors (16). Genetic cancer risk assessment is an interdisciplinary specialty practice that uses genetic and genomic information to identify individuals with inherited cancer risk and advise on high-risk screening, preventive care, and targeted treatment.

Breast cancer risk assessment models are various mathematical models that estimate a woman’s risk of breast cancer over defined time periods (Table 5-1). The models are used to identify women who can benefit from interventions, such as more intense screening with breast
magnetic resonance imaging (MRI) in addition to mammograms and chemoprevention. Most models are not applicable to patients with a hereditary cancer syndrome. A comprehensive breast cancer risk assessment includes calculation of risk via multiple models, as they vary in their estimates and applicability to patients. Additionally, clinical factors, such as history of mantle field radiation between 10 and 30 years of age will automatically place a woman in a high-risk category. The important features of each model are highlighted in Table 5-1.

The Gail model primarily focuses on nongenetic risk factors and includes limited information on family history (17). The model combines the patient’s reproductive history and limited family history, including age, age at menarche, age at first live birth, number of first-degree female relatives with breast cancer, number of previous breast biopsies, and results of those biopsies. The Gail model was validated for white women as well as for those of African American, Asian, and Pacific Islander descent. Limiting factors that the Gail model is only applicable for women aged 35 or older, excludes personal history of breast cancer or ductal carcinoma in situ (DCIS) and only accounts for first-degree relatives with breast cancer independent of the age of onset. It is not recognized by the ACS as a model to identify candidates for breast MRI screening or as an adjunct to mammography and it is used for identifying candidates for chemoprevention when the 5-year risk is 1.67% or greater.

The Claus model gathers input on family history of female breast cancer as well as ovarian cancer. The model assumes that breast cancer risk is transmitted as an autosomal-dominant trait, and its risk estimates are based on the patients’ relation to their affected relatives (18). This model includes age and a comprehensive family history with paternal relatives as well but excludes high-risk breast cancer genes and does not account for male relatives with breast cancer and hormonal and reproductive risk factors. The data are presented in a series of tables.

The Tyrer–Cuzick model integrates a wide variety of personal risk factors as well as an extensive family history of breast and ovarian cancer (19). This model incorporates age, height, weight, Jewish inheritance, age at menarche, menopausal status, age at first live birth, hormone replacement use, history of high-risk breast lesions (including atypia and lobular carcinoma in situ [LCIS]), as well as extended paternal and maternal family history of both breasts, male breast and ovarian cancer, including ages of onset. It also incorporates positive and negative BRCA1/2 genetic test results.

The BRCAPRO model calculates lifetime breast cancer risk as well as the probability of a BRCA1/2 mutation. It requires input of a full family history, including breast cancer under age 50 and ovarian cancer (20). The BRCAPRO model will underestimate risk in BRCA-negative, breast cancer–only families because it does not account for genes other than BRCA1/2 that can contribute to cancer risk.

In addition to the Claus model and Tyrer–Cuzick model, the BRCAPRO and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) models are also endorsed by the ACS for identifying candidates for breast MRI screening as an adjunct to mammography.

The BOADICEA model accounts for BRCA1/2 mutations as well as a polygenic factor that aims to address the idea that multiple genes exist and that each have small effects on breast cancer risk but act multiplicatively when factored together. BOADICEA does not incorporate information about nonhereditary risk factors and will likely underestimate risk in these women (21).

Future directions include models that incorporate additional risk factors to improve discriminatory power. A recently developed deep learning model that uses full-field mammograms yielded substantially improved risk discrimination compared with the Tyrer–Cuzick (version 8) model (22).

Genetic testing for hereditary susceptibility to cancer increasingly informs oncology care, allowing tailored treatment and preventive care. Genomic cancer risk assessment serves as a tool to identify patients and families who are at elevated risk for cancer. Several organizations published clinical practice guidelines describing indications for genetic testing, including the American Society of Breast Surgeons (ASBrS) (23), the National Comprehensive Cancer Network (NCCN) (24), and the U.S. Preventive Services Task Force (USPSTF) (25). Table 5-2 summarizes the commonly used criteria.

Genetic counseling serves to guide the patient through a genetic testing process. The counselor (1) assesses personal and familial risk for a cancer syndrome and identifies candidates for testing; (2) provides education about a cancer syndrome and mode of inheritance; (3) explains the benefits, harms, and limitations of genetic testing; (4) helps with interpretation of the test results; and (5) identifies potential strategies for risk reduction. The genetic counselor also helps to guide the patient through the emotional aspects of genetic testing, assists the patient to make an informed decision to proceed with testing or halt/defer the workup and treatment processes.

The possible outcomes of genetic testing is a true positive, a true negative (i.e., an individual in a family with a known mutation tests negative for that mutation), uninformative (i.e., a negative test in a family where a mutation has yet to be identified), or a variant of unknown significance (VUS). By definition, a VUS is a detected genetic change without a good description of any correlating clinical risk.

The passing of the Genetic Information Nondiscrimination Act of 2008 by Congress provides protection against health insurance discrimination based on genetic information, but not against life or disability insurance discrimination. The availability of testing options has changed since the 2013 U.S. Supreme Court ruling that determined human genes are not patentable (Association for Molecular Pathology et al. v. Myriad Genetics). Since the ruling, the number of testing options has significantly increased, with more than 80 multigene panels
that include BRCA1 and BRCA2. The nature of genetic counseling has grown increasingly complex with the identification of non-BRCA mutations associated with breast cancer syndromes. While guidelines for some non-BRCA hereditary syndromes have been established (i.e., Li–Fraumeni syndrome [LFS], Cowden syndrome), it has been suggested that genetic counseling and preventive strategies be carefully recommended to patients with less common mutations in the absence of strong consensus or official guidelines.

Several interventions showed to reduce the incidence of BRCA-related cancer and mortality. These include intensive screening (earlier and more frequent mammography or breast MRI), risk-reducing medications (aromatase inhibitors, tamoxifen, or raloxifene), and risk-reducing surgery (mastectomy or salpingo-oophorectomy). There are rare potential adverse effects however, that include harms associated with breast imaging, risk-reducing medications, and risk-reducing surgery and ethical, legal, and social implications. Therefore, genetic counseling and testing should be offered by appropriately trained health care providers to minimize harm from inaccurate risk assessment, inappropriate testing, or misinterpretation of test results (26).

Recent studies suggest that up to 50% of women with germline predisposing mutations do not qualify for testing based on current testing criteria. In addition, family history–based criteria have limited applicability in patients who are adopted, have limited family structure, or are not aware of the cancer history in the family. In response to these limitations, the ASBrS (23) recently updated their guidelines to suggest that all patients with breast cancer should receive genetic testing, regardless of age at onset of disease or the extent of family history. Although the logistical challenges of testing all patients with breast cancer, including insurance coverage, are not clear at this time, it is evident that testing criteria will continue to be modified to include a greater proportion of possible mutation carriers. Although population-based testing for hereditary breast cancer risk is not yet ready for clinical practice, it may become a reality in the future, as studies evaluating population-based mutation screening provide information on the feasibility of population testing, improved yield, and cost effectiveness. Until that happens, clinicians should understand that genetic risk evaluation is not a one-time event but an ongoing assessment, because guidelines for testing are frequently updated and the personal and family history of patients may change (27).