A case-control study is a type of medical research investigation often used to help determine the cause of a disease, particularly when investigating a disease outbreak or a rare condition.
If public health scientists want a relatively quick and easy way to find clues about the cause of, for example, a new disease outbreak, they can compare two groups of people:
- Those who already have the disease - 'cases'
- Similar people who have not been affected - 'controls.'
A case-control study is retrospective - the researchers look back at data collected in the past, enabling them to test whether a particular outcome can be linked back to a suspected risk factor.
To test for specific causes, the scientists need to formulate a hypothesis about what they think could be behind the outbreak or disease.
They then compare how often the group of cases had been exposed to the suspected cause (risk factor), versus how often the controls had been exposed. If the risk factor has a greater prevalence among the cases, then this is some evidence to suggest that it is a cause of the disease.
Risk factors could be uncovered by researchers studying the medical and lifestyle histories of the people in each group. A pattern may emerge that links the condition under investigation to certain factors.
Case-control research is a central tool used by epidemiologists, who look into the factors that affect the health and illness of populations.
Just one risk factor could be investigated for a particular disease outcome. A good example of this is to analyze how many people with lung cancer, versus how many without, have a history of smoking.
When is a case-control study useful in medical research?
Relatively quick and easy
To test for specific causes, the scientists need to formulate a hypothesis about what they think could be behind the outbreak or disease. They then compare how often the group of cases had been exposed to the suspected cause (risk factor), versus how often the controls had been exposed.
Because a case-control study is retrospective, it is relatively quick to do, involving the analysis of health events that have already happened, and of risk factors that are in the past.
So there is no need for the scientists to wait and see what happens in a trial that unfolds over a future time course (known as a prospective study).
The fact that the data is already available for collation and analysis means that a case-control study is useful when quick results are desired, perhaps when clues are sought for what is causing a sudden disease outbreak.
This time-saving advantage to case-control studies also means they are more practical than other scientific trial designs if the exposure to a suspected cause is a very long time before the outcome of a disease.
For example, if you wanted to test the hypothesis that a disease seen in adulthood is linked to factors occurring in young childhood, a prospective study would take decades to do. A case-control study is a more feasible option in such a scenario.
Does not need large numbers of people
Numerous risk factors can be evaluated in case-control studies since they do not require large numbers of people to give statistically meaningful results. More resource can be put into the analysis of fewer people.
Limitations of case-control studies
While a case-control study can help to test a hypothesis about the link between a risk factor and an outcome, it is not as powerful as other types of study in determining a causal relationship between exposure to something and a specific outcome.
Case-control studies are often used to yield early clues that inform further research using more rigorous scientific methods.
The main problem with case-control studies is that, because they look into things that happened in the past (they are retrospective), they are not as reliable as studies planned in advance that record data at the time events actually happen.
The main limitations of case-control studies are:
People answering questions about certain risk factors exposed to them in the past may not remember them reliably. People with a certain disease outcome may be more likely to recall a certain risk factor, even if it did not exist - because participants may be tempted to make their own subjective links.
Case-control studies often rely on people trying to recall past symptoms or lifestyle factors, thus limiting their scientific value.
This bias may be reduced if data about the risk factors - exposure to certain drugs, for example - had been entered into reliable records at the time. But this may not be possible for lifestyle factors, for example, because they are usually investigated by questionnaire.
An illustrative example of recall bias is the difference between asking study participants to recall the weather at the time of the onset of a certain symptom, versus an analysis of scientifically measured weather patterns around the time of a formally recorded diagnosis.
Finding a biomarker of exposure to a risk factor is another example to reduce the subjectivity of case-control studies (the difference between asking about taking performance drugs or urine-testing for them).
Cause and effect
Just because an association has been found retrospectively between one thing and another, this does not necessarily mean one thing directly caused the other.
In fact, a retrospective study - which is not an 'experiment' - can never definitively prove that an association represents a cause. There are, though, questions that can be used to test the likelihood of a causal relationship - such as whether the association is large in magnitude or whether there is a 'dose response' to increasing levels of the risk factor.
One way of illustrating cause-and-effect limitations is to consider an association found between a cultural factor and a particular health outcome. The cultural factor itself - a certain type of exercise, say - may not be the cause of the outcome if some other plausible common factor - a certain food preference, perhaps - is shared by the same cultural group of cases.
The cases and controls selected for study may not be truly representative of the disease being investigated. An example of this is when cases are seen in a teaching hospital, which is a highly specialized setting compared with the community in which most cases of the disease may occur. The controls, too, may not be typical of the population - people volunteering their data for the study may have a particularly high level of health motivation.
There are other limitations to case-control studies. While they are good at studying rare conditions (because they do not require the many participants that prospective studies need), they are not very good at studying rare risk factors, which call for cohort studies.
Finally, case-control studies are unable to examine different levels or types of the disease being investigated. They can look at only one outcome, because the definition of a case is set by specific diagnostic criteria against the straightforward question of whether, yes, they had the condition, or no, they did not.
Other terms used to describe case-control studies include 'epidemiological,' 'retrospective,' and 'observational.'