5.2. Types of Observational Studies: Case-control studies
1. Case-control studies
Case-controlled studies are studies which involve identifying individuals who have the outcome/disease of interest (cases) and matching them with individuals who have similar characteristics, but do not have the outcome of interest (controls). Data about exposure of interest (i.e., the hypothesised causal or contributing factors) are then collected retrospectively, typically by interview, extracted from records, or survey. Case-control studies assess whether there is a statistically significant difference in the rates of exposure to the risk factor(s) between the groups. This can suggest associations between the risk factor(s) and development of the disease in question, although no definitive causality can be determined. The main outcome measure in case-control studies is the odds ratio (OR).
It is imperative that defined inclusion and exclusion criteria prior to the selection of cases are formulated to best ensure that all cases included in the study are based on the same diagnostic criteria. Cases should be selected from a reliable source such as a disease registry. Regardless of how the cases are selected, they should be representative of the broader disease population to support generalisability.
A particular problem in case-control studies is the selection of a comparable control group. Since the validity of the study depends upon the comparability of these two groups, principally, the distribution of exposure should be the same among cases and controls; in other words, ideally both, cases and controls, should come from the same source population. For example, if cases are selected from a defined population such as a general practitioner (GP) register, then controls should comprise a sample from the same GP register.
Investigations examining rare outcomes may have a limited number of
cases to select from, whereas the source population from which controls can be taken
is much larger. In such scenarios, the study may be able to provide more
information if multiple controls per case (about three or four) are added thus
increasing the sample size. Also, matching controls to the selected cases on
the basis of various factors (e.g., age, sex) is a possibility to prevent
confounding of the study results. Matching may even increase the “statistical
power” and precision of the study.