Is hormone replacement therapy safe?

What Different Kinds of Studies Tell Us
A brief explanation of the types of studies that contribute to the advance of medical
knowledge will help you understand how we reached the crisis of confidence about hormone therapy, after years of widespread belief that it was beneficial for most women.

Laboratory studies, also known as basic or experimental research, investigate the effects of a given intervention on animals, body cells from animals, or body cells from humans. Such studies allow for far greater control than studies of human beings, but results from animals or cells in tightly regulated environments may not always apply directly to actual people living in the real world. Nevertheless, laboratory studies often provide important insights into whether and how a purported medical treatment might work in humans.

Studies of people living in the real world are known as epidemiologic studies. The two main types of epidemiologic studies are observational studies and randomized clinical trials. In an observational study, researchers observe study participants and record their characteristics, behaviors, use of medications, and health outcomes but do not otherwise intervene in the participants’ lives. This type of study uncovers possible relationships between various “exposures” and diseases, but it cannot prove a cause-and-effect link. Two common subtypes of observational studies are casecontrol studies and cohort studies.

Case-control studies gather histories from a group of people who have developed a particular disease (the cases) and a similar group of people who are free of that disease (the controls) and compare the two groups to look for factors that might have contributed to the development of disease. The information is obtained by questioning the subjects or their family members about their history or by reviewing medical, employment, or other archival records. Case-control studies are an efficient way to study connections between exposures and chronic diseases, which usually take many years to develop. However, having a disease may color the participants’ recall of their behaviors and use of medications, which can distort results.

Cohort studies assemble a group of people who typically have some characteristic in common, such as occupation, place of residence, or menopausal status. Unlike a case-control study, none of the participants in a cohort study has the disease of interest at the start of the study. The group is then followed over time via periodic checkups or mailed questionnaires, or by monitoring death certificates, to see who develops the disease. Once enough time has elapsed, researchers can examine the information to test a variety of hypotheses concerning the development of disease. By gathering exposure information from participants before the disease has occurred, cohort studies avoid the problems of faulty recall that can sometimes affect case-control studies.

Both cohort and case-control studies have suggested major health benefits of hormone therapy, including reductions in heart disease and hip fractures, but have also suggested major risks, such as an increased chance of breast cancer and stroke. It’s because of these results that most healthcare providers have for many years cautioned women who were already at higher-than-average risk for breast cancer or stroke not to choose hormone therapy.

However, observational studies are open to the criticism that the apparent benefits seen in these studies may simply reflect the fact that women who choose to use hormone therapy tend to be healthier, have greater access to medical care, and embrace health-promoting habits, such as eating a nutritious diet and exercising regularly, more readily than women who do not choose to use hormones. In short, the argument goes, it’s not that taking estrogen promotes health, it’s that being healthy promotes the taking of estrogen. To address this concern, researchers typically use statistical techniques to factor out the effect of variables, such as age, diet, physical activity, smoking, and so forth, that may vary between hormone users and nonusers. This strategy is effective, though not perfect, because it’s impossible to anticipate, measure, and account for all the factors that could conceivably distort, or confound, the relationship between an exposure and disease. So there’s always some possibility that the results are at least partially due to external factors (so-called “confounders”) rather than the exposure of interest.

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