There are two main types of study design:
observational studies and experimental studies (
4). In observational studies, patients or groups of patients are observed over a period of time, and their characteristics are recorded. In an experimental design, an intervention such as a drug, procedure, or technology is introduced into the population, and the effect on the study subjects is observed.
Types of observational studies vary. We will consider a few with which the reader should be familiar. These include case-control studies and cohort studies. Regarding experimental studies, we will mainly consider randomized controlled trials.
Case-Control Studies
A case-control study is typically performed on previously collected, retrospective data. In these studies, there are five steps to consider.
First, one begins with either the presence or absence of an outcome of interest. Second, one defines a group of cases that have this measure of interest—typically, this is a disease or an outcome event. Third, a control group is identified that does not have the disease or the measure of interest, but may be matched on common characteristics such as age or gender. Fourth, the investigator looks at the history of cases to detect possible causes or risk factors that were not controlled for in the matching process. Step five is an attempt to answer the question of what happened or what is the difference between the cases and the controls that might explain the outcome of interest. A case-control study might be useful, for example, to consider whether the use of a medication is related to the development of a disease. When considering a treatment, the cases and controls should be carefully matched on important risk factors in order to be as certain as possible that only the treatment effect varies between the two groups.
Figure 12-1 and
Table 12-2 show examples.
Case-control studies have certain advantages and disadvantages. This may be the best design for studying diseases or conditions that develop over a long time or are extremely rare. They may be very useful for investigating a preliminary hypothesis, because they are typically a very rapid way of performing a study, provided the data on the population have already been collected. The major disadvantage is that the case-control study depends on existing records, which may have been collected for other reasons. This particular study design is subject to a fair degree of bias or error, because the data are typically collected in advance of the question being asked, so one is limited by the existing data. For example, factors associated with the outcome may not be equally distributed between the two treatments. If these factors are not available to be examined, one cannot test whether the differences in the factors, rather than the treatment being studied, are responsible for any statistically significant treatment results. In addition, patient care may have changed since the data were collected, making the results no longer applicable. Choosing an appropriate control group (including one that is matched for certain characteristics) is critical, but may prove to be quite difficult.
Cohort Studies
In a cohort study, information is collected on a group of subjects who have something in common and who remain part of that group for an extended period of observation or follow-up. Typically, in this type of design, one begins with the identification of an exposure to some event that is felt to be relevant to the development of some outcome in the future. One then identifies two groups of subjects, the exposed group and the nonexposed group. One then looks forward in time from the exposure to determine the effect of the defining characteristics or exposure on the outcome of interest. This design attempts to answer the prospective question: what will happen?
An example of a cohort study design is seen in
Figure 12-2 and
Table 12-3. A cohort study is a good design when one is interested in studying the particular causes of a condition, the course of a particular disease, or the impact of risk factors over time. The Framingham Study, which has provided so much critical information on the understanding of the association between cardiac risk factors and cardiac outcome, is an example of a cohort study (
5). One of the major disadvantages of a cohort design is that studies such as the Framingham study may take a long time to conduct. Because of this, they tend to be resource-intensive. It is also a difficult methodology when one is interested in causation: one may define association, but because there is no intervention being introduced into the population, it is difficult to prove causation. It may also be a difficult design when a disease is rare in the population, because the requisite large sample size may be prohibitive.