Case-Control Study - BSc Medical Sciences - PDF

Case-Control study BSc Medical Sciences: Epidemiology Assistant Prof. Dr. Soza Th. Baban Introduction and Review In session 8, we discussed: i. Understand the role of descriptive studies in identifying disease patterns based on time, place, and person. ii. Define and differentiate between...

Case-Control study BSc Medical Sciences: Epidemiology Assistant Prof. Dr. Soza Th. Baban Introduction and Review In session 8, we discussed: i. Understand the role of descriptive studies in identifying disease patterns based on time, place, and person. ii. Define and differentiate between the types of descriptive epidemiological studies: case reports, case series, and cross-sectional studies. iii. Discuss the advantages and limitations of descriptive studies in public health research. iv. Analyse real-world examples of descriptive studies, evaluating their contribution to identifying public health trends and informing interventions. Learning objectives i. Definition of Case-Control study. ii. Criteria of designing Case-Control study. iii. Calculate and interpret the odds ratio as a measure of association in Case-Control study iv. Discuss the advantages and disadvantages of Case-Control study. v. Analyse real-world examples of Case-Control study. Let’s go through each of these points in detail!  Analytical Epidemiology Analytical studies are the second major type of epidemiological studies. In contrast to descriptive studies that look at entire populations, in analytical studies, the subject of interest is the individual within the population to identify and understand the causes or risk factors of diseases.  Case-Control study Cases Controls Time Exposure Outcome  Case-Control study A case-control study is designed to help determine if an exposure is associated with an outcome (i.e., disease or condition of interest). Cases (a group known to have the disease or outcome) Controls (a group known to be free of the disease or outcome) Then, look back to determine which individuals were exposed and compare exposure frequency between cases and controls. It is called ‘’retrospective studies’’ because it starts with an outcome then traces back to investigate exposures. Design of a Case-Control Study  Features of Case-Control Study A. Both exposure and outcome (disease) have occurred before the start of the study. B. The study proceeds backwards from effect to cause. C. It uses a control or comparison group to support or refute an inference.  Features of Case-Control Study Case control studies are basically comparison studies. Cases and controls must be comparable with respect to known "confounding factors" such as age, sex, occupation, social status, etc.  Case-Control Studies: Smoking and Lung Cancer Study objectives Test the hypothesis: "cigarette smoking causes lung cancer" Determine if smoking history is more common among lung cancer cases than controls. Suspected or Cases Control risk factors (Lung cancer present) (Lung cancer absent) Smoking A B No smoking C D Study design: A+C B+D Assemble two groups: Cases (a+c): individuals with lung cancer Controls (b +d): matched individuals without lung cancer.  Case-Control Studies: Smoking and Lung Cancer Study design: Explore the past history in both groups for the presence or absence of smoking, which is suspected to be related to the occurrence of cancer lung: Exposed : smokers Non-exposed : non-smokers Suspected or Cases Control risk factors (Lung cancer present) (Lung cancer absent) Smoking A B No smoking C D A+C B+D  Case-Control Studies: Smoking and Lung Cancer Study design: If the frequency of smoking, a/ (a+c) is higher in cases than in controls b/(b+d), an association is said to exist between smoking and lung cancer. Suspected or risk Cases Control factors (Lung cancer present) (Lung cancer absent) Smoking A B No smoking C D A+C B+D  Case-Control Studies: Smoking and Lung Cancer Study design: If the frequency of smoking, a/ (a+c) is higher in cases than in controls b/(b+d), an association is said to exist between smoking and lung cancer. Suspected or risk Cases Control factors (Lung cancer present) (Lung cancer absent) Smoking A B No smoking C D A+C B+D  How to Design a Case-Control Study? Basic steps: There are four basic steps in conducting a case control study :  How to Design a Case-Control Study? Basic steps: 1. Selection of cases and controls (A) Selection of a case: refers to an individual within a population who has a specific disease, condition, or health outcome of interest.  How to Design a Case-Control Study? Basic steps: (B) Selection of a control: it must be free from the disease under study. They must be as similar to the cases as possible, except for the absence of the disease under study.  How to Design a Case-Control Study? Basic steps: There are four basic steps in conducting a case control study :  How to Design a Case-Control Study? Basic steps: 2. Matching It is the process by which we select controls in such a way that they are similar to cases with regard to certain relevant selected variables (e.g., age) which are known to influence the outcome of disease and this is done to prevent distortion or confounding of the results by ensuring comparability between the cases and controls.  How to Design a Case-Control Study? 2. Matching Confounding factor is defined as one which is associated both with exposure and disease, and is distributed unequally in study and control groups. Although this factor is associated with ‘exposure’ under investigation, is itself, independently of any such association, a ‘risk factor’ for the diseases.  2. Matching Example: Alcohol consumption contributes to the development of oesophageal cancer. Smoking is a confounding factor because: It is associated with alcohol consumption. It is an independent risk factor for oesophageal cancer. The effects of alcohol on oesophageal cancer can only be accurately determined if the influence of smoking is neutralized (e.g., by matching). Researchers ensure that the groups being compared (e.g., those with and without oesophageal cancer) have similar distributions of smokers and non- smokers. This makes sure that the differences in cancer rates are not due to smoking but rather to alcohol consumption.  2. Matching Example: Steroid contraceptive use is associated with an increased risk of breast cancer. There is a potential confounding effect caused by age, which can distort the results. Age is a known risk factor for breast cancer. As women get older, the risk of developing breast cancer increases. If women who use steroid contraceptives tend to be younger than those in the comparison group (who are not using contraceptives), the younger women would naturally have a lower risk of breast cancer. This is because breast cancer is less common in younger women, so any observed differences in breast cancer rates could be due to age rather than the contraceptive use.  2. Matching Matching Protects Against False Associations: Researchers ensure that the groups being compared (those using steroid contraceptives and those not using them) have equal proportions of women in each age group. By doing this, the study can more accurately assess the relationship between steroid contraceptives and breast cancer, without the confounding effect of age. Matching helps control for confounding variables (like age) to ensure that the study results are not distorted by factors that are unrelated to the main hypothesis, providing a clearer picture of the relationship being studied.  2. Matching Matching is also done by pairs. For example: For each case, a control is chosen which can be matched quite closely. Thus, if we have a 50 year old chef with a particular disease, we will search for 50 year old chef without the disease as a control.  How to Design a Case-Control Study? Basic steps: There are four basic steps in conducting a case control study :  How to Design a Case-Control Study? Basic steps: 3. Measurement of exposure Exposure information (such as risk factors) should be collected consistently for both groups, using methods like interviews, questionnaires, or reviewing past records. Bias can occur if the information about exposure is not collected consistently for both cases (those with the disease) and controls (those without the disease). P-value is a statistical measure used to determine whether the results of a study are statistically significant (i.e., unlikely to have occurred by chance).  How to Design a Case-Control Study? Basic steps: 3. Measurement of exposure Exposure information (such as risk factors) should be collected consistently for both groups, using methods like interviews, questionnaires, or reviewing past records. Bias can occur if the information about exposure is not collected consistently for both cases (those with the disease) and controls (those without the disease). P-value is a statistical measure used to determine whether the results of a study are statistically significant (i.e., unlikely to have occurred by chance).  How to Design a Case-Control Study? Basic steps: There are four basic steps in conducting a case control study :  How to Design a Case-Control Study? Basic steps: 4. The final step is analysis, to find out: (a) Exposure rates among cases and controls to suspected factor (b) Estimation of disease risk associated with exposure (Odds ratio) 4. The final step is analysis, to find out: Exposure rates among cases and controls to suspected factor: a. Cases = a/(a+c) = 94.2% b. Controls = b/(b+d) = 67.0% A case control study of smoking and lung cancer Exposure rates among cases and controls to suspected factor: a. Cases = a/(a+c) = 94.2% b. Controls = b/(b+d) = 67.0% This shows that the frequency rate of lung cancer was definitely higher among smokers than among non-smokers. A case control study of smoking and lung cancer  How to Design a Case-Control Study? Basic steps: 4. The final step is analysis, to find out: (b) Estimation of disease risk associated with exposure is obtained by an index known as "Relative Risk“ (RR) Relative Risk is the ratio between the incidence of disease among exposed persons and incidence among non-exposed. It is given be the formula: RR = incidence among exposed/ incidence among non-exposed In a case-control study, we can't directly calculate relative risk because we don’t have a complete picture of how many people were at risk of getting the disease. The study doesn’t track people over time to see who develops the disease, so we can’t calculate how many people in total were exposed to the risk (like smoking) and how many got the disease. What Can We Calculate in a Case-Control Study? Instead of Relative Risk (RR), in a case-control study, researchers calculate the odds ratio (OR). The odds ratio (OR) tells us how much more likely the cases (people with the disease) were to have had the exposure (e.g., smoking) compared to the controls (people without the disease). OR is a measure of the strength of the association between risk factor and outcome. In this example, smokers of less than 5 cigarettes per day showed a risk of having lung cancer 8.1 times that of non-smokers. Odds ratio is a key parameter in the analysis of case control studies. How to Calculate the Odds Ratio The odds ratio is calculated using a 2x2 table: Cases Controls (No (Disease) Disease) Exposed A B Not Exposed C D Formula: OR = (A / C) ÷ (B / D) This tells us how much more likely the exposed group is to develop the disease compared to the non- exposed group. Strengths of Case-Control Studies 1. Efficient for studying rare diseases or outcomes. 2. Suitable for diseases with long latency periods (e.g., cancers, chronic diseases). 3. Relatively quick and inexpensive to conduct compared to cohort studies. 4. Useful for studying multiple exposures related to a single outcome. 5. Can be done retrospectively, making them faster and more flexible. Limitations of Case-Control Studies 1. Prone to recall bias: Participants may not remember past exposures accurately. 2. Selection bias: If cases and controls are not properly matched, the results may be skewed. 3. Cannot establish causality: Only shows associations, not direct cause-effect relationships. 4. Confounding variables: Factors other than the exposure may influence the outcome.  Case-Control studies Advantages 1. Relatively easy to carry out. 2. Rapid and inexpensive 3. Suitable for rare diseases. 4. Study of several different aetiological factors (e.g., smoking, physical activity and personality characteristics in myocardial infarction). 5. Can be done retrospectively, making them faster and more flexible.  Case-Control studies Disadvantages 1. Problems of bias relies on memory or records, often with uncertain accuracy. 2. Selection of an appropriate control group may be difficult. 3. We cannot measure incidence, and can only estimate the relative risk. 4. Cannot establish causality: Only shows associations, not direct cause-effect relationships. 5. Confounding variables: Factors other than the exposure may influence the outcome. Case-Control studies: 1. Smoking and Lung Cancer – The British Doctors Study (Doll & Hill, 1950s) 2. The Association Between Aspirin Use and Reye’s Syndrome (1980s) 3. Waterborne Cholera Outbreak in London (John Snow, 1854) Datasets: 1. Smoking and Lung Cancer 2. Contaminated Food and Foodborne Illness Case scenario: Investigating the Risk Factors for Hypertension in a Local Population Worksheet: Designing a Study to Address a Public Health Issue  Recap and Q&A Key Points from Today’s Lecture: i. Define and explain the concept of a case-control study and its role in epidemiology. ii. Understand the methodology involved in designing and conducting a case- control study, including selecting cases and controls. iii. Calculate and interpret the odds ratio as a measure of association in case- control studies. iv. Discuss the strengths and limitations of case-control studies, particularly in relation to bias and confounding factors. v. Analyses real-world examples of case-control studies, evaluating their contribution to identifying risk factors and informing public health interventions. Preparation for Next Session In the next session we'll explore the Cohort study studies (Analytical Epidemiology). Read Chapter 10 (Pages 240-266) from "Gordis Epidemiology" by Celentano DD and Szklo M. Review Chapter 4 (Pages 75-81) from "Parks Textbook of Preventive & Social Medicine" by K. Park