...(greater age 30 years), increase a woman's breast cancer risk (Lynch, 2002). The two most important risk factors for breast cancer are age at diagnosis and family history. Having one first-degree or second-degree relative with breast cancer can increase a woman's lifetime risk of breast cancer significantly (Srivasta, McKinnon, & Wood, 2001). Risk assessment may be used for screening as well as medical decision making about chemoprevention and prophylactic surgery, for clinical trial eligibility, and in genetic counseling for pretest decision making and posttest interpretation (Rubinstein, O'Neill, Peters, Rittmeyer, & Stadler, 2002).

One in eight women in the United States develops breast cancer; this translates to a 12.6% lifetime probability (Ries et al., 2004). Sponsored by the National Cancer Institute (NCI), the Surveillance Epidemiology and End Results (SEER, 2007) group collects cancer information from nine different geographic locations throughout the United States and has provided accurate demographic statistics on cancer every year since 1973. The group estimated that 178,480 women will be diagnosed with and 40,460 women will die of breast cancer in 2007 (SEER, 2007) (see Table 1).

Breast Cancer Risk Assessment Tools

Recent advances in the understanding of breast cancer have led to the use of tools that use mathematical methods to identify risk in the general population. The best scenario would be a risk assessment tool that gives a "yes" or "no" answer, indicating that the patient either will develop breast cancer in the future or not. None of the risk assessment tools can do that, but they do provide a relative risk of developing breast cancer in comparison to the general population (Constantino, Gail, & Pee, 1999).

The modified Gail model is the most widely used risk assessment model. It is available online without charge (http://www.cancer.gov/bc risktool/Default.aspx) and does not require approval from insurance companies for its use, making it very attractive for anyone desiring to use the model. The modified Gall model is the only risk assessment tool that has been independently tested and validated, which provides evidence of accuracy (Constantino et al., 1999).

In a study by Constantino and colleagues (1999), the Gall model predicted that 159 women in a placebo group would be diagnosed with breast cancer; 155 actually developed breast cancer over a 5-year period. Of importance is the fact that women in the study were obtaining yearly mammograms and following other established NCI guidelines. The modified Gall model calculations/ predictions work best on a population that is compliant with annual mammograms (Constantino et al., 1999). At the Arizona Cancer Center (an NCI-designated facility), the modified Gail model is used to calculate lifetime exposure to estrogen and calculate relative risk.

One limitation of the modified Gail model is its failure to account for second-degree relatives with breast cancer, or paternal relatives with breast cancer (Euhus, Leitch, Huth, & Peters, 2002). The model is slanted heavily toward risks associated with estrogen or hormone exposures.

The Food and Drug Administration (FDA) uses the modified Gail model to calculate risk. Tamoxifen (Nolvadex[R]) was approved by the FDA for preventing breast cancer in women whose risk is greater than 1.7% over 5 years using the modified Gail model. It is reported that tamoxifen can reduce breast cancer by 50% (only in tumors that are hormone receptor-positive), and prophylactic mastectomy can reduce incidence by 90% in patients who have either a strong family history or a genetic mutation for breast cancer (Euhus, 2001).

Another widely used risk assessment tool is the Claus model. The Claus model was developed prior to the onset of genetic testing and is a better model for predicting risk in patients with a strong family history (Euhus et al., 2002). The Claus model also uses the age of onset of relatives with breast cancer, which is a predictor for a genetic mutation. Because the Claus model only has been tested in Caucasian women, its reliability is less certain in other races. It assigns risk to women based only on their inherited predisposition to breast cancer, creating a limitation in not accounting for environmental causes of breast cancer such as estrogen exposure (Euhus et al., 2002).

Screening Mammography

Breast cancer survival has increased over time; at least some of the improvement is attributed to mammography (NCI, 2007). Screening mammography in the general population starting at age 40 is the gold standard in the United States, as supported by multiple research studies (Miller, To, Baines, & Wall 2002; Moss et al. 2006; Shapiro, 1988; Zahl, Strand, & Maehlen, 2004). The "absolute mortality benefit for women screened annually starting at age 40 is 4 per 10,000 at 10.7 years" (NCI, 2007). Also, the reduction in breast cancer mortality was estimated using seven different statistical methods that attributed a 7%-23% reduced rate (mean 15%) of breast cancer death due to screening mammography (Berry et al., 2005). Screening mammography in women age 40-49 leads to a decrease of 15%-20% in breast cancer mortality, with 15%-35% mortality decrease in women age 50-69. A screening mammogram is particularly effective in decreasing mortality in women who are asymptomatic (NCI, 2006). This is important because earlier detection leads to earlier treatment. It will detect about 2 cancers per 1,000 exams (NCI, 2007). Although the screening mammogram is recommended for every female starting at age 40, it is not a perfect diagnostic test because approximately 10%-15% of breast cancers will not be detected by mammography (NCI, 2006). Mammograms should always be compared to an earlier mammogram to increase sensitivity (Berry et al., 2005). At the Arizona Cancer Center, patients are encouraged to get copies of their earlier films for comparison over time. They also...

NOTE: All illustrations and photos have been removed from this article.



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