At 53, Angela DeMarco suffered from hot flashes that were "almost unbearable." They came every twenty minutes, she says: "day and night." For five years, she had also been experiencing mood swings, vaginal dryness, and sleeplessness and tests showed she was at risk for osteoporosis-- thinning of the bones. She had tried a soy-based herbal medicine, but her symptoms, all common to menopause, were getting worse. Sometimes, she would think, "there is no hope for me."

DeMarco (not her real name) knew that her symptoms might be alleviated through hormone replacement therapy, or "HRT," in which drugs are used to replenish the estrogen that diminishes as part of women's natural aging process. But she also knew that HRT increases some women's risk of breast cancer--and both her aunt and her sister had died of that disease. As might be expected, DeMarco felt desperate. And she was in a quandary about whether to try HRT.

For many women, weighing the risks and benefits of HRT is complicated, says Dr. Nananda Col of the Tufts New England Medical Center in Boston. Much of the research on HRT in its early stages, and the existing questionnaire-based studies conducted on large population groups cannot accurately predict the health experiences of individual women. What is more, most of those studies have examined HRT's effects on one illness at a time, but many women are at risk for several illnesses, on which HRT may have differing effects.

To help women like DeMarco in their decision-making process, Col and her colleagues have developed a mathematical model that calculates the comparative risks and benefits associated with HRT. The model, or "algorithm," is based on the results of population studies conducted over many years. The algorithm is unusual because it individualizes the findings of those studies. It can be used to assess the likelihood that a particular patient will contract heart disease, breast cancer or hip fractures-- conditions many women develop as they grow older. The algorithm can also be used to calculate the extent to which taking HRT will increase or decrease a woman's chances of developing each illness, and the effect HRT is likely to have on the length of a woman's life.

In employing the algorithm, Col questions a patient about her family and personal medical histories, and tests the patient's cholesterol level, blood pressure and the like. Col also asks about lifestyle factors such as smoking, drinking and exercise that are known risks for particular diseases. Col then types the information she collects into a software program based on the algorithm. The software calculates the patient's risks, and Col prints out a personalized 30-50-page report.

When DeMarco went through Col's process, she was "very surprised" by the results. Whereas DeMarco had been afraid she would get breast cancer, she says, she was "shocked" to learn that she was at far greater risk for hip fractures. (Her report showed that without HRT, she would have a 16 per cent chance of developing breast cancer and a 17 per cent chance of getting cardiovascular disease--compared with a 39 per cent chance of fracturing a hip). Col's report also showed that HRT could reduce DeMarco's risks for hip fracture by almost 50 percent and cut her risk of heart disease by 6 percent. However, HRT would increase DeMarco's chances of developing breast cancer by the same degree--about 6 percent. DeMarco also learned that different varieties of HRT could have different effects on those risks, and that HRT's effects could vary depending on when she started treatment, and how long she stayed on it.

Having that knowledge made it much easier to decide on a course of treatment, DeMarco says, and today, she feels "much better." She now takes calcium supplements to prevent hip fractures and, now that she has added flaxseed oil, and Vitamins E and B complex to her diet, her menopausal symptoms have been reduced. Where once DeMarco had adamantly refused HRT based on her breast cancer concerns, she now says that she will consider hormone replacement if she develops osteoporosis.

While Col's algorithm cannot predict with certainty whether a woman will or won't develop an illness, it can be "reassuring" because it helps a woman quantify her decision, says Maureen Connelly, MD/ Ph.D., co-director of the Harvard Vanguard Menopause Consultation Service in Boston. Since the algorithm is updated as new research is reported, a woman can rest assured that she has based her decision on the best available evidence.

Col cautions that the algorithm is designed primarily for women who are healthy, and is not appropriate for women whose immune systems may be compromised in any way. Also, because the studies on which it is based were conducted primarily on Caucasian women, its effectiveness in assessing risks for minority women is not yet clear.

A software version of Col's questionnaire will be widely available to health care providers in the Spring of 2000, according to Lynn Rubin, Executive Director of Consumer Education for Women First Healthcare, Inc., a San Diego company that has licensed the algorithm for commercial use.

Resources:

Website of the North American Menopause Societyhttp://www.menopause.org/

Books:
Nananda, A Woman Doctor's Guide to Hormone Therapy: How to Choose What's Right for You, Tatnuck Bookseller Press, 1997.
Shiff, Isaac, MD Menopause, Times Books, Random House, 1995.Col,

Articles:
"Individualizing Therapy to Prevent Long-term consequences of Estrogen Deficiency in Postmenopausal Women," Nananda Col, et al., Archives of Internal Medicine, 159 July 12, 1999, 1458-1466.