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The breast cancer equation

September 11, 2006|Melissa Healy | Times Staff Writer

As personal ratings go, a woman's calculation of her breast cancer risk is a new, relatively quick ritual -- taking into account family history and other obvious factors. But assessing that risk is about to become considerably more complicated. A study in the Sept. 6 issue of the Journal of the National Cancer Institute finds that the density of a woman's breasts could be a powerful predictor of whether she will develop the disease in her lifetime.

But who has dense breasts, and how does one measure that? Let's just put it this way: You won't be able to compute your breast- cancer risk in the span of a coffee break anymore.

Although the science of individual risk assessment for breast cancer is in its infancy, it's been catching on across the country. Each month, about 22,000 women log on to a National Cancer Institute website and answer seven simple questions. In a matter of seconds, the "Gail Model" -- named for NCI's chief biostatistician, Mitchell H. Gail -- spits out a woman's five-year and lifetime risk of developing invasive breast cancer.

It's not as much fun as doing the "How Spontaneous Are You?" quiz poolside. But learning your breast-cancer risk is easier than checking a credit rating, less time-consuming than taking the SATs and more consequential than computing your sleep number. And, as evidence mounts that a woman can drive down her breast-cancer risk with behavior changes and medication, it's one of those personal ratings that's worth knowing.

In the United States, breast cancer strikes 1 in 8 women, a rate that has been on the rise since 1980. But after years of living in passive dread of the disease, American women and their doctors have begun to seize the offensive against breast cancer, slowing its rate of increase and boosting the odds of survival.

But researchers are still tinkering with the central equation women must use to make decisions about, for instance, having their breasts surgically removed, or taking medication that can drive down breast-cancer risk but also may increase the risk of blood clots and stroke. And practicing physicians are rushing to keep up with research and its implications for their patients.

It's an often frustrating game of catch-up.

That exasperating truth has been demonstrated anew this month with a study that finds that women with dense breasts had a significantly greater risk of breast cancer than women whose breasts were not dense. According to Gail, the study's lead author, breast density appears to be a factor as powerful as family history of breast cancer in determining a woman's risk of developing breast cancer. Currently, there is no stronger predictor of a woman's breast-cancer risk than whether -- and how many of -- her direct relatives (mother, sisters, daughters) have had breast cancer.

But a woman's breast density is not currently considered in the Gail Model, and if it were, few women -- and few of their physicians -- could currently provide the measure of breast density that is thought to indicate a woman's breast-cancer risk. "Technologically, it's feasible, but you can't just go to your doctor right now and get that," Gail says. "You can't just order it like another lab test right now."

For the thousands of women and their physicians who have used the Gail Model since it was first posted on the NCI website in 1998, the test has involved little to no data-hunting. In addition to asking how many direct relatives have had breast cancer and how many benign breast biopsies she's had, the test asks a woman to provide the age at which she began menstruating, whether and at what age she gave birth, her current age and her race. It may take a phone call, or a hunt for that old diary, but for most women, the breast- cancer risk calculator is a snap.

Now comes evidence that the calculator could be better at helping women and their doctors determine how far they should go to reduce the odds of breast cancer. But it won't be as easy anymore.

In an editorial accompanying the study, breast cancer specialists Melissa L. Bondy and Dr. Lisa A. Newman called the potential inclusion of breast density in the Gail Model an "exciting" prospect. But they cautioned that even a model that predicts cancer risk perfectly won't be much good if women and their doctors don't have or can't understand the data that's needed to make the computation.

Radiologists who read mammograms sometimes characterize the density of a woman's breasts in their interpretive reports, most often when breast density interferes with their ability to read X-ray films. But the practice is not required by regulations governing the practice of mammography. Moreover, the qualitative classifications recognized and used by many radiologists do not approach the level of detail used by Gail to improve prediction of breast-cancer risk. Such precise measurements of a woman's breast density, say experts, will likely come only with a new generation of breast-imaging machines.

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