So many women have had breast cancer and seem to be fine. If an individual woman turns up with breast cancer, can doctors figure out what her own chances are? And, does that information affect how she is treated?
Oncologists routinely use clinical risk-profiles, including tumor size, hormone receptor content, extent of involvement of the axillary nodes, and other factors discerned only when a pathologist examines the tumor cells under the microscope (sometimes referred to as the grade of the cancer cells). These factors can be used to provide a general clinical profile that estimates the risk of a future relapse, and thereby helps doctors and patients weigh the pros and cons of adjuvant ("helping") chemotherapy as an additional option. Such adjuvant therapy itself has recognized risks and quality-of-life issues, and the physician and patient must discuss these topics in order to personalize breast cancer management. However, some risk factors are open to subjective interpretation and may vary from one observer to another.
The physician may also use the Adjuvant! algorithm, available free of charge, on-line. Adjuvant! is a mathematical predictive model that estimates risk of breast cancer-related death at 10-years of follow-up based on the original tumor size, the number of involved lymph nodes, hormone receptor status, and so forth. Information from this algorithm has an interface that can be shared with the patient.
Thus, this Internet-based risk application is one additional tool for establishing the benefits of adjuvant (or helping) therapy for women with early breast cancer. This is all based on the assumption that an individual patient will conform to the population's mathematical model.
Typically, if a woman's tumor contains receptors for hormones like estrogen, which is the case two thirds of the time, she will be offered adjuvant hormone-blocking therapy. This means using drugs that target the actions of these hormone receptors and thereby block the tumor-growth-promoting actions of the hormones for many years. Such drugs include tamoxifen or a newer class of hormone-blocking agents called aromatase inhibitors (for post-menopausal women). Some women have tumors that express the Her-2/neu protein, a special growth-signaling molecule for the cancer cells. For these women, the doctor may consider the use of new agents such as Herceptin, a monoclonal antibody that targets the Her-2/neu protein.
Yet despite advances using the available clinical profiles, one fundamental challenge remains. In real life not all people fit mathematical models. How does one decide precisely who among the two thirds of patients with hormone-receptor-containing breast tumors face a high probability of relapse and might, therefore, also need adjuvant chemotherapy to improve the odds?
So, a very common question arises when a woman over 50 presents with an estrogen-receptor- positive breast tumor and is axillary node negative at the same time. How does one personalize that woman's disease management so that her medical care is aligned to her risk as an individual, not the risk profile for a statistical group, or for the "average" patient—which is another way of saying the same thing?
The challenge is to avoid overtreatment, which might cause unnecessary side effects, and undertreatment, which might not be enough to prevent a relapse, for any given patient. And that's where the exploding field of genomics has stepped in to provide a molecular/genetic analysis of a given tumor. This helps physicians to be more precise in identifying individual differences that can be obscured by statistics. It is also important to keep in mind a woman's total health-risk profile. Thus, for some women with very early breast cancer (very small tumors, confined to the breast, without spread to lymph nodes or other organs), future heart disease may be a more significant risk than a recurrence of the breast cancer. Accordingly, prevention of cardiovascular disease can be a very important topic.
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