At the moment, at least three plausible explanations exist for the discrepancy between the clinical trial results and those of the Nurses' Health Study and other observational studies. One is that the associations perceived by the epidemiologic studies were due to healthy-user and prescriber effects and not H.R.T. itself. Women who took H.R.T. had less heart disease than women who didn't, because women who took H.R.T. are different from women who didn't take H.R.T. And maybe their physicians are also different. In this case, the trials got the right answer; the observational studies got the wrong answer.
A second explanation is that the observational studies got the wrong answer, but only partly. Here, healthy-user and prescriber effects are viewed as minor issues; the question is whether observational studies can accurately determine if women were really taking H.R.T. before their heart attacks. This is a measurement problem, and one conspicuous limitation of all epidemiology is the difficulty of reliably assessing whatever it is the investigators are studying: not only determining whether or not subjects have really taken a medication or consumed the diet that they reported, but whether their subsequent diseases were correctly diagnosed. "The wonder and horror of epidemiology," Avorn says, "is that it's not enough to just measure one thing very accurately. To get the right answer, you may have to measure a great many things very accurately."
The most meaningful associations are those in which all the relevant factors can be ascertained reliably. Smoking and lung cancer, for instance. Lung cancer is an easy diagnosis to make, at least compared with heart disease. And "people sort of know whether they smoke a full pack a day or half or what have you," says Graham Colditz, who recently left the Nurses' study and is now at Washington University School of Medicine in St. Louis. "That's one of the easier measures you can get." Epidemiologists will also say they believe in the associations between LDL cholesterol, blood pressure and heart disease, because these biological variables are measured directly. The measurements don't require that the study subjects fill out a questionnaire or accurately recall what their doctors may have told them.
Even the way epidemiologists frame the questions they ask can bias a measurement and produce an association that may be particularly misleading. If researchers believe that physical activity protects against chronic disease and they ask their subjects how much leisure-time physical activity they do each week, those who do more will tend to be wealthier and healthier, and so the result the researchers get will support their preconceptions. If the questionnaire asks how much physical activity a subject's job entails, the researchers might discover that the poor tend to be more physically active, because their jobs entail more manual labor, and they tend to have more chronic diseases. That would appear to refute the hypothesis.
The simpler the question or the more objective the measurement the more likely it is that an association may stand in the causal pathway, as these researchers put it. This is why the question of whether hormone-replacement therapy effects heart-disease risk, for instance, should be significantly easier to nail down than whether any aspect of diet does. For a measurement "as easy as this," says Jamie Robins, a Harvard epidemiologist, "where maybe the confounding is not horrible, maybe you can get it right." It's simply easier to imagine that women who have taken estrogen therapy will remember and report that correctly -- it's yes or no, after all -- than that they will recall and report accurately what they ate and how much of it over the last week or the last year.
But as the H.R.T. experience demonstrates, even the timing of a yes-or-no question can introduce problems. The subjects of the Nurses' Health Study were asked if they were taking H.R.T. every two years, which is how often the nurses were mailed new questionnaires about their diets, prescription drug use and whatever other factors the investigators deemed potentially relevant to health. If a nurse fills out her questionnaire a few months before she begins taking H.R.T., as Colditz explains, and she then has a heart attack, say, six months later, the Nurses' study will classify that nurse as "not using" H.R.T. when she had the heart attack.
| • | Do We Really Know What Makes Us Healthy?
The New York Times, Sunday, Sept. 16, 2007 Byline: Gary Taubes |
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