Case Control Studies

Stages of a Case-Control study

This diagram represents taking both the case (disease) and the control (no disease) groups and looking back at their histories to determine their exposure to possible contributing factors.  The researchers then determine the likelihood of those factors contributing to the disease. Heres an example using Lemons!

Lemons and Health: A Case-Control Study

Question: Do lemons influence a specific health condition? (e.g., urinary tract infections)

Design: Compare individuals with the condition (cases) to those without (controls).

Participants:

• Cases: Individuals recently diagnosed with the target condition.

• Controls: Healthy individuals with similar demographics.

Data Collection:

• Interview both groups about lemon consumption habits (frequency, duration).

• Consider other relevant factors (diet, lifestyle) through surveys or medical records.

Analysis:

• Compare lemon consumption patterns between cases and controls.

• Statistically assess if lemon intake differs significantly between groups.

Goal: Identify potential association between lemons and the chosen health condition.

Limitations: Reverse causality (illness influencing lemon intake), recall bias (difficulty remembering past habits), confounding factors.

Ethical Considerations: Informed consent, data privacy, transparency about study limitations.

This case-control study explores the potential link between lemon consumption and a specific health condition. It provides a quicker picture of the association compared to a cohort study, but establishing cause-and-effect is difficult.

What does a strong Case-Control study look like?

A strong study will have:

• Well-matched controls, similar background without being so similar that they are likely to end up with the same health issue (this can be easier said than done since the risk factors are unknown). 

• Detailed medical histories are available, reducing the emphasis on a patient’s unreliable recall of their potential exposures. 

What are the advantages and disadvantages to consider when using Case-Control?

Advantages

• Helps you find the source of an existing illness or epidemic. 

• Cheap and quick to conduct this type of study. The health issue has already occurred, you don’t need a lab or special equipment. 

• Few ethics issues as the patient already has the health condition 

• Looks at multiple risk factors in a patient’s life (environment, work, diet).

Disadvantages

• Patient recall about their history can be inaccurate (recall bias).

• Patients aware of certain risk factors may focus on those and ignore other exposures.  

• No randomisation is possible, lowering internal validity of the study.

• Finding a Control group that matches the Case group appropriately can be difficult.

• This study type does not prove a clear causal relationship between risk factors and illness, only calculates the odds. 

Opportunities

• Particularly useful for rare conditions, it’s often the only option as it’s not appropriate to try to cause a disease using RCTs. 

• Can be used to identify point of outbreak, looking into the past to see common exposure in the Case histories. 

• Can look at many exposure factors of the patient’s environment, medical history, diet. This is  useful where no single aspect of the patient’s life has been narrowed down as a potential cause. 

Confounding*

• If the health issue causes multiple common exposures, the study should attempt to differentiate between those exposures to identify which is more likely. For example, having a chronic illness may mean you spend more time in hospital environments, have a lower immune system, and suffer high levels of stress – so any of these could potentially be the cause of that chronic illness. The study must make an attempt to eliminate some of these exposures as causes if possible. 

• If the Control group is overmatched and starts to develop the health issue.

• If the Control group is under-matched and there aren’t enough comparable factors to differentiate what is specific to the Case population. For example, if you could not find female Controls to match female Cases, then you cannot assess whether gender is or isn’t a contributing risk factor. 

* Confounding occurs when the elements of the study design invalidate the result. It is usually unintentional. It is important to avoid confounding, which can happen in a few ways within Case-Control studies. This explains why it is lower in the hierarchy of evidence, superior only to Case Studies.

Statistical Analysis

Odds Ratio (Used to study rare once in a lifetime disease)

• Thinks in terms of odds, which is the ratio of the likelihood of something happening to the likelihood of it not happening.

• Compares the odds of having the outcome in an exposed group to the odds in an unexposed group.

• Imagine the same 100 people in each group. OR tells you how much more likely it is to find someone who is exposed among those with the outcome compared to finding someone exposed among those without the outcome.

• An OR of 2 means you're twice as likely to find someone who smokes among people with lung cancer compared to finding a smoker among those without lung cancer.

What are the pitfalls to look for?

• Poorly matched or over-matched controls.
  Poorly matched means that not enough factors are similar between the Case and Control. E.g. age, gender, geography. Over-matched conversely means that so many things match (age, occupation, geography, health habits) that in all likelihood the Control group will also end up with the same health issue! Either of these situations could cause the study to become ineffective. 

• Selection bias: Selection of Controls is biased. E.g. All Controls are in the hospital, so they’re likely already sick, they’re not a true sample of the wider population. 

• Cases include persons showing early symptoms who never ended up having the illness. 

What are the stages of a Case series study?

Conducting a case-control study typically involves the following stages:

1. Study Design: Define the research question and objectives of the study. Select cases (individuals with the outcome of interest) and controls (individuals without the outcome) based on specific criteria.

2. Case Selection: Identify and recruit cases from a defined population who have experienced the outcome of interest. Ensure proper case definition and consider factors such as time frame and severity.

3. Control Selection: Select a suitable control group that is comparable to the cases but does not have the outcome of interest. Controls should be selected from the same population or have similar characteristics as the cases.

4. Exposure Assessment: Collect data on the exposure(s) of interest, which are factors hypothesized to be associated with the outcome. Use standardized methods, such as interviews, questionnaires, or medical records, to assess the exposures in both cases and controls.

5. Data Analysis: Analyze the collected data using appropriate statistical methods, such as odds ratios or logistic regression, to estimate the strength of association between the exposure and outcome. Account for potential confounding factors and adjust the analysis accordingly.

6. Results Presentation: Present the findings in a clear and organized manner, using tables, figures, or graphs to summarize the distribution of exposures in cases and controls. Report odds ratios or other relevant measures of association.

7. Discussion and Interpretation: Discuss the implications of the findings in relation to the research question, considering strengths and limitations of the study design, potential biases, and the consistency with existing literature. Explore possible explanations or mechanisms underlying the observed associations.

8. Conclusion: Summarize the key findings and draw conclusions based on the analysis and interpretation of the data. Discuss the study's implications for understanding the relationship between exposure and outcome and identify areas for further research.

9. Reporting: Prepare a comprehensive report or manuscript adhering to the reporting guidelines, such as STROBE (Strengthening the Reporting of Observational Studies in Epidemiology), to ensure transparent and accurate reporting of the study methodology, results, and conclusions.

Case-control studies are retrospective in nature, comparing the exposure history of cases and controls to identify associations with the outcome of interest. They are particularly useful for studying rare outcomes and investigating potential risk factors. However, they cannot establish causality and are susceptible to biases such as recall bias and selection bias.