Current Applications of Epidemiology
In case you’re still confused about what this marvelous new (old) science is all about, this section provides some topical examples of epidemiologic studies and a hint of some of the techniques that were used.
Identifying the Cause of a New SyndromeThe late 1970s saw a number of cases of menstruating women who experienced a cluster of symptoms including fever, hypotension, and a rash, followed by desquamation (a fancy term that simply means “peeling”) on the hands, soles, fingers, or toes. Within a short time, 50 cases had been reported to the Centers for Disease Control and Prevention (CDC) in Atlanta, and three women had died. Two questions required an urgent response: (1) Is this a new syndrome? and (2) What is causing it?
Through an examination of the records, it was determined that these 50 cases were presenting a new clinical entity, described by Langmuir as a “distinct clinical syndrome of marked severity and considerable clinical specificity.” This was labeled TSS. Let’s take a closer look at the history of this disorder because it nicely highlights many of the steps used to discover the cause of a problem and, in this case at least, the interventions needed to alleviate it.
The first step was passive surveillance. Neither the CDC nor the local public health agencies initially went out looking for cases of this new disorder. Rather, they relied on reports submitted voluntarily by local physicians and other agencies. The major advantage of passive surveillance is that no single agency is always on the lookout for an outbreak of something, especially if they don’t how what that something is or if indeed anything is breaking out at all. There is the hope that any new and especially any potentially dangerous syndrome will be noticed by the front line people (e.g., family physicians, laboratory workers, community health nurses) and reported to the health office. The downside of remaining passive is that reporting is extremely sporadic; a person first has to notice that something is amiss and then take the time and effort to report this to some agency. So passive surveillance can alert people that something is happening, but it can’t really say how big the problem is or where the hot-spots are. This is exactly what happened with TSS; the CDC learned that there was an outbreak of a possibly new disorder, but it was still in the dark regarding the outbreak’s magnitude or what may be causing it.
Once an agency suspects that a problem may exist, it usually then relies on active surveillance. The agency becomes more active and tries to solicit complete reporting of the new syndrome by contacting family physicians, medical officers of health, or laboratories. Depending on the degree of cooperation received, it’s now possible to get a better handle on the magnitude of the problem and perhaps to develop some hypotheses about what may be causing the outbreak. The CDC and state agencies begin to look for cases, such as TSS, using active surveillance by both getting frontline workers to report to them and examining the charts and discharge codes in selected hospitals.
To sharpen their hypotheses the agencies began a series of studies in which people who had TSS were compared with those who didn’t (these are called case control studies, and we’ll discuss them in more depth in Chapter 3). They were particularly interested in tampon use because the previous observations led them to believe that TSS may be associated with menses. These case control studies, especially those conducted by the CDC, finally nailed down the cause. In their first study, all 52 cases used tampons but only 85% of the control women did. In the second study, women who used the Rely brand of tampons were almost eight times more likely to develop TSS than women who used other brands. Finally, it was found that other brands were involved and that the culprit was the increased absorbency of the “new and improved” versions.
Now to the intervention. In Fig.1144, we see a sharp increase in TSS cases until 1980. At that point, Rely was voluntarily withdrawn from the marketplace, resulting in a dramatic decrease in reported cases. For the next 4 years, the proportion of women using very high-absorbency products dropped from 42% to 18% and down to 1% by 1986, and the most absorbent tampons, those made with polyacrylate, were taken off the market in 1985. The effect of these changes on the number of reported cases is striking.
TSS hasn’t completely disappeared because it is caused by the staphylococcus organism, not by tampons. There are still a few cases every year, usually as a result of surgery. On the whole, though, this example demonstrates the strength of epidemiologic methods. Even given a relatively rare condition, such as TSS, associated with a common practice, such as tampon use, it could nonetheless be established that high-absorbency tampons were the culprit and that removing them from store shelves could stop the outbreak.
Figure 1144 – (Figure 1-1) Incidence of toxic shock syndrome cases per year
Streiner DL, Norman GR. PDQ Epidemiology-Second Edition, 1996, BC Decker Inc., Hamilton, Ontario.
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Assessing the Risks Associated with a Harmful ExposureEpidemiologic methods can be used to assess the risks to health that result from exposure to noxious agents. For example, with the worldwide use of nuclear reactors to generate power, the public, the nuclear power industry, and nuclear regulatory bodies are all interested (obviously for different reasons) in determining the risks associated with exposure to the radioactive emissions resulting from a nuclear “accident“ (a benign term for a malignant condition). These interests are not merely hypothetical or academic. In 1957 the first documented nuclear “accident,” or substantial release of radioactivity from a nuclear power plant, occurred when a reactor caught fire at Sellafield on the Irish coast of Great Britain; in 1979 a nuclear accident occurred when a reactor was damaged at Three Mile Island; and in 1986 the most severe nuclear accident to date occurred at Chernobyl, in the former Union of Soviet Socialist Republics (USSR), when the graphite core of a reactor caught fire and caused the rupture or “meltdown” of fuel rods and the release of radioactive fission products into the atmosphere. Winds distributed the radioactive particles over large areas of Europe and the Northern Hemisphere.
It is of obvious importance to determine the immediate and long-term risks to the populations in the immediate vicinity of the nuclear accident and to those farther from the reactor (in other regions or countries). Fortunately, there is already a great deal of evidence available about the risks of cancer, childhood leukemia, birth defects, and so forth that result from exposure to high-level and low-level radiation. By far the most extensive source of human evidence resulted from careful follow-up during the past 5 decades of the survivors of the Hiroshima and Nagasaki bombings. The basic strategy is to document, as carefully as possible, the radiation exposure of each individual and then to compare the rate of onset of various diseases at different levels, from no exposure to a high level. Other sources of evidence derive from the documented exposure of soldiers in the atom bomb tests of the 1950s, workers at the shipyards where nuclear submarines were serviced, populations exposed to the fallout clouds in Utah and Nevada, atomic workers, and even kids (now in their 40s) who put their feet in fluoroscopy machines at the local shoe store.
Based on this evidence the scientists have predicted that there might be as many as 39,000 additional cancer deaths worldwide during the next 50 years. Because there are expected to be approximately 630 million deaths from cancer during the same period, the increase will not be detectable. Within the former USSR estimates range from 5,000 to 50,000 excess deaths against a background of 9.5 million cancer deaths; again, the difference will not be statistically significant. However, among the 24,000 people who lived within 15 km of the reactor site, the estimated excess number of cancers is 13, which raises the total to 624; this will be statistically detectable. Interestingly, actual data collected since that time tell a different story. One huge study of childhood leukemia involved national registries of all the European countries. There were 3,679 observed cases versus 3,533 expected casesa— relative risk of 1.04. There was no association between risk and exposure, leading the authors to discount any causal connection between the observed increase in leukemia and Chernobyl radiation. Another study looked at thyroid nodules (an early indicator of cancer from radiation exposure), comparing people in highly exposed villages near the reactor and control villages. Again, no significant increase. One thing has significantly increased since the accident—the number of articles about Chernobyl. A Medline search retrieved more than 1,200 articles since 1986.
Epidemiologic studies have played a fundamental role in demonstrating the risk to health from such domestic exposures as smoking, nitrates in food, high dietary cholesterol, and occupational exposure to factors like asbestos, lead, and rubber. Conversely, epidemiologic methods have shown that there exists little evidence of harm from other exposures. For example, formaldehyde release from urea formaldehyde foam insulation, “yellow rain” in Southeast Asia, video display terminals, and silicone breast implants have all, at one time or another, been featured prominently in news reports. Subsequent epidemiologic investigations, however, have revealed little in the way of measurable health problems from these highly publicized cases.
In turn the identification of these risk factors may lead to the identification and effective treatment of those already exposed (e.g., screening and treatment for hypertension) and can suggest strategies for prevention (e.g., guarantees of adequate income for single-parent families to prevent some childhood psychiatric disorders).
How to Determine if a Treatment is EffectiveYou are a 33-year-old mother of two children. Last week you noticed a small lump in one breast. With considerable apprehension you made an appointment with your family physician. Today the doctor announced that your fear was justified; the lump is malignant. Your physician recommends total mastectomy (a surgical procedure that involves amputation of the breast but not of the underlying muscle and lymph nodes) and assures you that if you have this procedure, your condition is almost certainly curable. A friend of yours had a diagnosis of breast cancer more than 1 year ago, and her physician removed just enough tissue to eliminate the tumor (lumpectomy) and gave her radiation therapy. You are frightened by the disease and want the treatment that will be most effective in preventing a recurrence of the cancer. On the other hand, you are devastated at the prospect of losing your breast. Clearly, if the treatment your friend had is as effective as total mastectomy, it would be your treatment of choice.
How do you decide what to do? Being human, you would likely seek out other friends who have gone through the procedures. In the absence of friends there is still Family Circle and Consumer Reports (the latter actually does a good job of reporting medical research). However, if you or your close friends had access to Medline and a medical library, there is the option of seeking out the original articles.
Clinical epidemiology figures prominently in the review. The methods of clinical epidemiology have contributed much to the assessment of the effectiveness of particular treatments. In the case of breast cancer the primary issue is whether there is any greater chance of survival with total mastectomy versus lumpectomy. The question of effectiveness must be clearly defined, including both the specifics of the treatment and the particular cases to which it is applied. For example, lumpectomy may be just as effective in treating early stage breast cancer, whereas it may well be ineffective in treating later stage breast cancer after the malignant cells have spread beyond the immediate area.
Some additional concerns may relate to the side effects. If there is no difference in survival between two treatments, it becomes a tradeoff between the short-term discomfort from chemotherapy or hair loss from radiation and the disfigurement and disability from the loss of the breast. An approach that may help when examining side effects is to seek out information about the differences in psychologic adjustment after total mastectomy versus lumpectomy and radiation therapy.
The best data on whether a treatment does more good than harm come from an experimental study design called the randomized controlled trial (RCT). Here, patients with the disorder are randomly allocated to receive either the experimental treatment or conventional therapy (or a placebo) and then are followed up so that the clinically relevant outcomes of the disease and treatment can be described and compared (see Chapter 3 for more complete details of the RCT design). If you were the woman in our breast cancer example and if, in an improbably objective frame of mind, you wanted to apply epidemiologic principles to determine the treatment of choice, you would want to know if any RCTs had been conducted comparing total mastectomy to more conservative surgery and radiation therapy.
As it turns out, there are several such trials. A recent study found that lumpectomy, with or without irradiation, was equivalent to total mastectomy ( Fig.1145). Similar numbers of women remained disease-free and were alive 12 years after the procedure. So your literature search would give you the ammunition to say that the lumpectomy is less disfiguring than mastectomy and leads to a similar outcome.
Figure 1145 – (Figure 1-2) Data from a randomized controlled trial showing survival rates after total mastectomy and lumpectomy, with and without irradiation
From Fisher et al: Reanalysis and results after 12 years of follow-up in a randomized clinical trial comparing total mastectomy with lumpectomy with or without irradiation in the treatment of breast cancer, N Engl J Med 333:1456-1461, 1995.
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How to Identify Health Service Use Needs and TrendsModern epidemiology plays an important role in the development of methods that can be used to describe health services and to test alternative ways to “deliver the goods.” For example, one often-debated health service question concerns the effect of health insurance coverage on the health services used by poor and near-poor populations. Conservatives claim that allowing people free access to health care services will open the floodgates and result in massive increases in health care costs. In so doing they ignore two kinds of data: (1) the several decades of experience in Canada and western Europe that provide ample demonstration that there is a practical ceiling on use of health services and (2) the unpleasant experience of cooling one’s heels in a physician’s waiting room, thumbing 10-year-old copies of Reader’s Digest. The idea that people would prefer this to doing almost anything else is bizarre. By contrast, socialists live in their own version of utopia where all are equal—in access, income, and reason. In socialist heaven, no clear-thinking individual would dare to take undue advantage of free health care services, and rates of use would not differ regardless of the method of payment.
Obviously, truth lies somewhere in between these extremes. Taube and Rupp conducted a study to assess the effect of Medicaid coverage on access to ambulatory mental health care for the poor and near-poor less than 65 years of age. By analyzing data from the National Medical Care Utilization and Expenditure Survey, they found that the poor and near-poor with continuous Medicaid coverage used almost twice as much service as the poor and near-poor not enrolled in Medicaid ( Fig.1148).
They concluded that the higher probability of use in those covered by Medicaid reflects the impact of the increased financial accessibility to needed mental health services. (This is a fine demonstration of the art of sciencemanship. Take an obvious and self-evident conclusion from the data, and clothe it in big obscure words so it sounds profound.)
This is only one example. Our personal favorite, which neatly skewers those who assume that every additional dollar spent on health care is a dollar well spent, is the repeated demonstration (in Scandinavia, Israel, and Canada) that when the physicians go on a protracted strike, the mortality rate drops.
Some other variations on this theme are health economics, which combines epidemiologic and economic methods to examine the cost-effectiveness of alternative models of delivery, and policy analysis, which seeks to link research findings to change in health policy.
Figure 1148 – (Figure 1-3) Data showing the effect of Medicaid coverage on access to ambulatory mental health care for the poor and near-poor populations less than 65 years of age
From Taube CA, Rupp A: The effect of Medicaid on access to ambulatory mental health care for the poor and near-poor, Med Care 24:677-687, 1986.
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| 5476. | Streiner DL, Norman GR. PDQ Epidemiology. 2nd ed. Hamilton, Ontario: BC Decker Inc.; 1996. |