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 usually 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.
Prospective case-control studies are less common; these involve enrolling a specific cohort and following that cohort prospectively, with "cases" emerging as people who develop the disease or condition under investigation, and those unaffected forming the "control" group.
To test for specific causes, the scientists need to formulate a hypothesis about what they think could be behind the outbreak or disease. These are known as risk factors.
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.
If a specific risk factor (such as age, sex, smoking or eating red meat) has already been identified for a disease or condition, the researchers can use statistical methods to adjust for that risk factor, helping them to identify other possible risk factors more easily.
Case-control research is a central tool used by epidemiologists, researchers 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.
Why is a case-control study useful in medical research?
There are multiple reasons why case-control studies are useful to researchers.
Relatively quick and easy
To test for specific causes, scientists formulate a hypothesis as to the cause of an outbreak or disease. They then compare exposure to the suspected cause (risk factor) in the cases that emerge versus those unaffected by the disease or condition (the controls).
Because a case-control study is typically retrospective, it is relatively quick to do. Scientists can analyze existing data to look at health events that have already happened and risk factors already observed.
A retrospective case-control study does not require scientists to wait and see what happens in a trial that unfolds over a period of days, weeks or even years (known as a prospective interventional 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.
A prospective case-control study may also be helpful in this scenario as researchers can collect data on suspected risk factors while they monitor for new cases.
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.
Overcomes ethical challenges
As case-control studies are observational and usually retrospective, they do not pose the ethical obstacles seen with prospective interventional studies.
For example, it would be unethical to deprive a group of children of a potentially lifesaving vaccine in order to see who developed the associated disease, but a retrospective analysis of a group of children with poor uptake of or access to that vaccine can help determine who is at most risk of developing the disease and where to target future vaccination efforts.
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:
When people answer questions about their previous exposure to certain risk factors their recall may be unreliable. Compared to healthy people, individuals with a certain disease outcome may be more likely to recall a certain risk factor - even if it did not exist - because of a temptation to make their own subjective links in order to explain their condition.
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 way of reducing the subjectivity of case-control studies. For example, researchers may look at results of blood or urine tests for evidence of a specific drug, rather than asking a participant about drug use.
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.
Additionally, researchers have to take into account the clustering or overlap of some risk factors, such as leading a sedentary lifestyle, being depressed and living in poverty.
If researchers conducting a retrospective case-control study find an association between depression and weight gain over time, for example, they cannot say with any certainty that depression is a risk factor for weight gain without controlling for a sedentary lifestyle. This would involve looking to see if people who lead an active lifestyle and who suffer from depression are more likely to experience weight gain than people who lead an active lifestyle and are not depressed.
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" and "observational."