There are already several approaches available to increase the chances of diagnosing breast cancer at an early, curable stage, or of reducing the chances of getting breast cancer at all. Some examples include enhanced surveillance with periodic breast MRI, chemoprevention, or even prophylactic surgery. These interventions cannot be applied widely and indiscriminately because each exacts a cost of its own—be it financial, physiological, psychological, or social. The risks and benefits of these interventions must be considered on a case-by-case basis and this requires some sense of the balance between the risks of the proposed intervention and the risks of the disease it is trying to address.
It is well known that breast cancer can run in families, and it is not uncommon for a woman whose mother has died of breast cancer to suffer a great deal of anxiety about her own "impending" breast cancer, and even to undertake extraordinary measures, including prophylactic mastectomy, to prevent it. Individuals with a family history of breast cancer frequently overestimate their own chances of developing the disease and often experience a sense of relief when presented with quantitative information suggesting that their actual risk is quite a bit lower than they would have imagined.1,2 Conversely, a healthy woman whose recent breast biopsy has diagnosed high-risk preneoplasia, such as atypical hyperplasia, may be spurred to effective action when presented with a quantitative estimation of her breast cancer risk over time.
Quantitative breast cancer risk assessment is also an integral component of prevention research. It can be used as a surrogate for breast cancer incidence in studies evaluating biomarkers of breast cancer risk,3-5 and is always considered in the inclusion criteria for trials that include breast cancer incidence as an end point.6 The value of quantitative risk assessment in the later case cannot be overstated as these calculations permit accurate estimation of the number of end-point events that will occur. This is critical for designing the most efficient study possible.
Finally, third-party payors have begun to consider quantitative risk assessment data in their determinations of medical necessity. This is best illustrated by fairly wide adoption of recently published American Cancer Society guidelines that support screening breast MRI for women with a lifetime risk of breast cancer 20% or more.7 The best approach for incorporating quantitative risk assessment into medical decision-making can and should be debated, but at this juncture it is reasonable to ask how one goes about estimating breast cancer risk, and whether such estimations are accurate.
A variety of metrics are available to quantify risk and each is valuable when used in the appropriate context. Relative risk is often used to identify new risk factors from case-control data and is sometimes used in calculations of absolute risk. Simply stated, relative risk expresses the strength of association between exposure to a risk factor and the presence of breast cancer. For example, the relative ...