This document discusses case control studies, an observational study design that compares individuals with a disease or condition (cases) to individuals without the disease or condition (controls) to determine associations between exposures and disease outcomes. It provides an overview of key elements of case control studies, including the selection and matching of cases and controls, measurement of exposure, analysis using odds ratios, potential biases, advantages and disadvantages compared to cohort studies, and examples of case control studies conducted.

1. Research Methodology
‘Case control study’
Dr. Rizwan S A, M.D.,
Assistant Professor,
Department of Community Medicine,
VMCH&RI, Madurai.
17.11.2014
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2. Classification of research methods
Research
methods
Observational
Descriptive
Case series,
case reports,
CS, cohort
Analytical
Ecological Cross-sectional
Experimental
Controlled
Case control Cohort
Uncontrolled,
Non-random
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3. Procedures in descriptive epidemiology
1. Define the population
2. Define and describe the disease
3. Measure the disease
4. Compare
5. Formulate hypothesis
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4. Association
• Defined as the co-occurrence of two or more
variables at a frequency which is more than
that expected by chance
• Association does not mean causation
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5. Causation - Hills criteria
1. Temporality
2. Strength
3. Specificity
4. Consistency
5. Biological plausibility
6. Coherence
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6. Dogma of cohort study
Healthy people Exposure occurs Exposed &
unexposed
Disease
occurs
Diseased &
non-diseased
Time
Direction of enquiry
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7. CASE CONTROL STUDY
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8. Position in the evidence hierarchy
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9. Dogma of case control study
Assemble
cases –
diseased
Time
Direction of enquiry
Assemble
controls –
not having
disease
Measure
exposure
status
Exposed
and non-exposed
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11. Introduction
• Synonyms – retrospective study
• A study that compares two groups of people: those
with the disease or condition under study (cases) and a
very similar group of people who do not have the
disease or condition (controls).
• Essential elements
– Both exposure and disease have occurred
– Proceeds from effect to cause
– Uses a comparison ‘control’ group
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12. 2 by 2 table
Diseased
- Cases
Non-diseased
– Controls
Total
Exposed A B A+B
Non-exposed C D C+D
Total A+C B+D A+B+C+D
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13. Steps in case control study
1. Selection of cases and controls
2. Matching
3. Measurement of exposure
4. Analysis and interpretation
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14. 1. Selection of cases and controls
• Define case – diagnostic and eligibility criteria
• Source of cases – hospital, general population
• Define control – free from disease
• Source of controls – hospital, relatives,
neighbourhood controls, general population
• Number of controls
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15. 2. Matching
• Ensure comparability between cases and controls
• A confounding factor is defined as one which is
associated both with exposure an disease, and is
distributed unequally in study and control groups.
• Examples:
• Suspected aetiological factor should not be
matched
• Types of matching: pair, frequency
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16. 2. Matching
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17. 3. Measure the exposure
• Define exposure
• Measure in precisely the same manner both
for cases and controls
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18. 4. Analyse
• Exposure rates among cases and controls
• Odds Ratio (Cross-product ratio)
– AD/BC
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19. 4. Analysis – Example
• E.g. 1. Depression and Vegetable eating
Individuals With
Depression
(Cases)
Individuals Without
Depression
(Controls)
Total
Eat
Vegetables
90 90 180
Do Not Eat
Vegetables
130 130 260
Total 220 220 440
• Odds of exposure among cases: a/c = 90/130 = 0.6923
• Odds of exposure among controls: b/d = 90/130 = 0.6923
• Odds ratio = 0.6923/0.6923 = 1.0
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20. Biases
• Bias due to confounding
• Memory or recall bias
• Selection bias
• Berkesonian bias
• Interviewer bias
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21. Pros & Cons
Advantages Disadvantages
Easy to carry out Subject to several biases
Rapid results Selection of controls difficult
Inexpensive Incidence can’t be measured
Suitable for rare diseases Association doesn’t mean causation
No risk to subjects Not practical for rare exposure
Minimal attrition
Multiple exposures can be
studied
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22. Case controls studies Cohort studies
Direction of inquiry from effect to
cause
Direction of inquiry from cause to
effect
Starts with the disease
Starts with people exposed to the
risk factor or suspected cause
Usually the 1st approach to the
testing of hypothesis, but also useful
for exploratory studies
Reserved for the testing of
precisely formulated hypothesis
Fewer study subjects Larger number of subjects
Quick Long follow-up, delayed results
Suitable for rare diseases
Inappropriate when disease or
exposure under investigation is rare
Generally, yields only Odds ratio
Yields incidence rates, relative risk,
attributable risk
Cannot yield information about
disease other than that under study
Can give information about more
than one disease outcome
Inexpensive Expensive
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23. Examples
• Adenocarcinoma of vagina and DES
• OCP and thrombosis
• Thalidomide tragedy
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24. Email your doubts to: sarizwan1986@outlook.com
You can download these slides at http://www.slideshare.net/RizwanSa
THANKS FOR LISTENING
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