A case-control study is a type of study design in epidemiology. Case-control studies are used to identify factors that may contribute to a medical condition by comparing subjects who have that condition (the 'cases') with patients who do not have the condition but are otherwise similar (the 'controls').[1]
Case-control studies are a relatively inexpensive and frequently-used type of epidemiological study that can be carried out by small teams or individual researchers in single facilities in a way that more structured experimental studies often cannot be. They have pointed the way to a number of important discoveries and advances.
The great triumph of the case-control study was the demonstration of the link between tobacco smoking and lung cancer, by Sir Richard Doll and others after him. Doll was able to show a statistically significant association between the two in a large case control study.[2] Opponents argued for many years that this type of study cannot prove causation, but the eventual results of cohort studies confirmed the causal link which the case-control studies suggested, and it is now accepted that tobacco smoking is a cause of about 87% of all lung cancer mortality in the US.
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The case-control is a type of epidemiological observational study. An observational study is a study in which subjects are not randomized to the exposed or unexposed groups, rather the subjects are observed in order to determine both their exposure and their outcome status and the exposure status is thus not determined by the researcher.
Porta's Dictionary of Epidemiology[3] defines the case-control study as an "observational epidemiological study of persons with the disease (or another outcome variable) of interest and a suitable control group of persons without the disease (comparison group, reference group). The potential relationship of a suspected risk factor or an attribute to the disease is examined by comparing the diseased and nondiseased subjects with regard to how frequently the factor or attribute is present (or, if quantitative, the levels of the attribute)in each of the groups (diseased and nondiseased)."[3] The case-control study is frequently contrasted with cohort studies, wherein exposed and unexposed subjects are observed until they develop an outcome of interest.[3][4]
One useful trait of case-control studies is that they tend to be less costly to carry out than prospective cohort studies, as well as having the potential to be shorter in duration. Another aspect is the greater statistical power of this type of study in several situations, given the fact that cohort studies must often wait for a 'sufficient' number of disease events to accrue.
Case-control studies are observational in nature and thus do not provide the same level of evidence as randomized controlled trials. It may also be more difficult to establish the timeline of exposure to disease outcome in the setting of a case-control study than within a prospective cohort study design where the exposure is ascertained prior to following the subjects over time in order to ascertain their outcome status. The most important drawback in case-control studies relates to the difficulty of obtaining reliable information about an individual’s exposure status over time. It should however be noted that many high quality and reliable case-control studies have been carried out and have produced useful results.
One of the most significant triumphs of the case-control study was the demonstration of the link between tobacco smoking and lung cancer, by Sir Richard Doll and others after him. Doll was able to show a statistically significant association between the two in a large case-control study.[5] Opponents argued for many years that this type of study cannot prove causation, but the eventual results of cohort studies confirmed the causal link which the case-control studies suggested, and it is now accepted that tobacco smoking is the cause of about 87% of all lung cancer mortality in the US.
Case-control studies were initially analyzed by testing whether or not there were significant differences between the proportion of exposed subjects among cases and controls.[6] Subsequently Cornfield[7] pointed out that, when the disease outcome of interest is rare, the odds ratio of exposure can be used to estimate the relative risk (see rare disease assumption). It was later shown by Miettinen in 1976 that this assumption is not necessary and that the odds ratio of exposure can be used to directly estimate the incidence rate ratio of exposure without the need for the rare disease assumption.[6][8][9]
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