case-control study design basics

1. CASE CONTROL STUDY
Dr. Chirag R Sonkusare
Dr. Komal Shelke
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2. EPIDEMIOLOGY:
“The study of the occurrence and distribution of health-related events,
states, and processes in specified populations including the study of determinants
influencing such processes and the application of this knowledge to control relevant
health problems”.
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4. HISTORY
The first modern case control study was Janet Lane Claypons study of breast
cancer in 1926.
It grew in popularity in 1950s after the publication of four case control studies that
established in link between smoking and lung cancer.
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5. Definition:
A method of sampling a population in which:
• Cases (Disease) are identified and enrolled
• Controls (Non disease)
Cases and controls must be comparable with respect to known “Confounding
factors” such as
Age, sex, occupation, social status, etc.
Unit is the Individual.
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6. Case control studies are Observational, Analytical studies &
Retrospective studies
Three distinct features of case control study :
1.Exposure and outcome have occurred before the start of the study
2.Proceed backwords from effect to cause
3.Uses controls or comparison group.
OUTCOME/
DISEASE
EXPOSURE/
CAUSE
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7. DESIGN OF
CASE
CONTROL
STUDY
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8. When is it desirable to conduct a case
control study ?
When exposure data are expensive or difficult to obtain
- Ex. Pesticide study
When disease has long induction and latent period
- Ex. Cancer, cardiovascular diseases
When the disease is rare
- Ex. Studying risk factors for birth defects
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9. • When little is known about the disease
• - Ex. Early studies of AIDS
• When underlying population is dynamic
• - Ex. Studying breast cancer
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10. Framework of case control study
Suspected or risk factors Cases
(disease present)
Control
(disease absent)
Present a b
Absent c d
a + c b + d
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11. Basic steps
Four basic steps in conducting a case control study:
1. Selection of cases and controls
2. Matching
3. Measurement of exposure
4. Analysis and Interpretation
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12. 1. Selection Of Cases And Controls
A. Definition of case:
Diagnostic Criteria-
-Diagnostic criteria of disease and stage of the disease (e.g., breast cancer stage I
must be included in the study must be specified.
-Once the diagnostic criteria are established, they should not be changed till the
study is over.
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13. • Eligibility Criteria
• -Only newly diagnosed (incident) cases within a specified period of time are
eligible
• -Not old cases or cases in advanced stages of disease(prevalent cases)
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14. B.Sources of cases:
a) Hospitals:
• Cases may be drawn from a single hospital or a network of hospitals ,admitted during a
specified period of time.
• The entire case series or random sample of it is selected.
b)General population:
• All cases of the study disease occurring within a defined geographic area, during a specified
period of time are ascertained, often through a survey, a disease registry or hospital network
• The cases should be representative of all cases in community.
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15. SELECTION OF CONTROLS:
• Must be similar to the cases but free from the disease.
• As a rule, comparison group identified before a study is done
• Difficulties may arise if the disease under investigation occurs in subclinical forms
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16. SOURCES OF CONTROLS
1.HOSPITAL CONTROLS:
 Controls may be selected from same hospital as cases, but with different
illneses other than study disease.
Hospital controls are often a source of “selection bias”.
2. RELATIVES:
Sibling controls are unsuitable where genetic conditions are under study.
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17. 3. NEIGHBOURHOOD CONTROLS:
 Controls may be drawn from persons living in same locality as cases, persons
working in the same factory or children attending the same school.
4. GENERAL POPULATION:
 Population controls can be obtained from defined geographic areas, by taking a
random sample of individuals.
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18. • Since both the cases and the hospital controls are selected from the defined population, any
factors that affected admission of cases to a certain hospital would also affect the admission of
hospital TOTAL POPULATION CASES DEFINED POPULATION
TOTAL POPULATION
Defined
population
Cases Controls
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19. 2. MATCHING
• Matching is defined as, the process by which we select controls in such a way that
they are similar to cases with regard to certain pertinent selected variables(eg.
Age) which are known to influence the outcome of disease and which, if not
adequately matched for comparability, could distort or confound the results.
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20. Examples to explain confounding.
• In the study of the role of alcohol in the aetiology of oesophageal cancer, smoking
is a confounding factor because
-It is associated with alcohol consumption
-It is an independent risk factor for oesophageal cancer
• Matching protects against an unexpected strong association between the matching
factor(eg. smoking) and the disease (oesophageal cancer)
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21. 3. MEASUREMENT OF EXPOSURE:
Information about exposure should be obtained in precisely the same manner both
for cases and controls.
Obtained by interviews, by questionnaires or by studying past records of cases
such as hospital records, employment records, etc.
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22. 4. ANALYSIS:
• The final step, to find out
a) Exposure rates among cases and controls to suspected factor
b) Estimation of disease risk associated with exposure(Odds ratio)
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23. a) Exposure
rates:
Cases
( with lung
cancer)
Controls
(without lung
cancer)
Total
Smokers
(less than 5
cigarettes a
day)
33
(a)
55
(b)
88
(a+b)
Non-smokers 2
(c)
27
(d)
29
(c+d)
Total 35
(a+c)
82
(b+d)
n =a+b+c+d
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24. b) Estimation
of risk
• The estimation of disease risk associated with exposure is
obtained by an index known as “Relative Risk”or “Risk ratio”
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25. ODDS RATIO (CROSS-PRODUCT)
• Which is a measure of the strength of the association between risk factor and
outcome.
• The derivation of odds ratio is based on three assumptions:
-The disease being investigated must be relatively rare
-The cases must be representative of those with disease.
-The controls must be representative of those without the disease
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26. Bias in case control studies:
 Bias is any systematic error in determination of association between exposure and
disease.
1.Bias due to confounding: This can be removed by matching
2.Memory or recall bias:
When cases and controls are asked questions about their past history, it
may be more likely for the cases to recall the existence of certain events or factors,
than the controls
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27. • 3.Selection bias:
The selection bias can be best controlled by its prevention.
• 4.Berkesonian bias:
The bias arises because of the different rates of admission to hospitals for
people with different diseases.(i.e hospital cases and controls)
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28. 5. Interviewers bias:
-Bias may also occue when the interviewer knows the hypothesis and also
knows who the cases are.
-The prior information may lead him to question the cases more thoroughly
than controls.
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29. Comparison of Case Control study and Cohort study
Features Case Control study Cohort study
Type of design Observational, Analytical Observational, Analytical
Temporality Retrospective (backward in time) Prospective (forward in time)
Direction of reasoning From outcome to exposure From exposure to outcome
Occurrence of outcome output already occurred Outcome not occurred
(ex: retrospective cohort)
Strength of association Odds ratio Risk ratio
Temporal association Not proven proven
Recall bias/ Survivorship bias Potential problem Not a major issue
Lost to follow up bias Not a major issue Potential problem
Time Results available quickly Takes a long time
No. of subjects Small sample size Large sample size
Logistics efforts Less costly, req. less logistics Expensive, lot of efforts
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30. Design of case control study
Cases (with disease)
Control (without
disease)
Exposed a b
Non exposed c d
Total a+c b+d
Proportions who were
exposed
a/a+c b/b+d
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31. We find that of the 200 CHD cases, 112 were smokers and 88 were
nonsmokers. Of the 400 controls, 176 were smokers and 224 were
nonsmokers.
CHD Cases Controls
Exposed (cigarette
smoker)
112 176
Non exposed (do not
smoke cigarette)
88 224
Total 200 400
% Smoking cigarettes 56 % 44 %
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32. Distribution of 1,357 Male Lung Cancer Patients and a Male Control Group
According to Average Number of Cigarettes Smoked Daily Over the 10 Years
Preceding Onset of the Current Illness
Average Daily Cigarettes
Lung Cancer Patients Control Group
0 7 61
1-4 55 129
5-14 489 570
15-24 475 431
25-49 293 154
50+ 38 12
Total 1357 1357
From doll and hill. A study of the aetiology of carcinoma of the lung BMJ 1952:1271-1286
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33. Examples of Case-Control
Studies
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34. Selection of cases and controls
• Selection of cases:- The investigator should define the cases as specifically as
possible. Sometimes, definition of a disease may be based on multiple criteria;
thus, all these points should be explicitly stated in case definition.
• Selection of controls:- an important aspect of selecting a control is that they
should be from the same ‘study base’ as that of the cases. Thus, the pool of
population from which the cases and controls will be enrolled should be same.
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35. Smoking and lung cancer study
• In their landmark study, Doll and Hill (1950) evaluated the association between smoking and lung cancer.
• They included 709 patients of lung carcinoma (defined as cases).
• They also included 709 controls from general medical and surgical patients.
• The selected controls were similar to the cases with respect to age and sex. Thus, they included 649
males and 60 females in cases as well as controls.
• They found that only 0.3% of males were non-smokers among cases. However, the proportion of
nonsmokers among controls was 4.2%; the different was statistically significant (P = 0.00000064).
• Similarly, they found that about 31.7% of the female were non-smokers in cases compared with 53.3% in
controls; this difference was also statistically significant (0.01< p <0.02).
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36. Melanoma and training (lazovic et al. 2010)
• The authors conducted a case-control study to study the association between melanoma and tanning.
• The 1167 cases - individuals with invasive cutaneous melanoma – were selected from Minnesota Cancer
Surveillance System. The 1101 controls were selected randomly from Minnesota State Driver's License list;
they were matched for age (+/- 5 years) and sex.
• The data were collected by self administered questionnaires and telephone interviews. The investigators
assessed the use of tanning devices (using photographs), number of years, and frequency of use of these
devices.
• They also collected information on other variables (such as sun exposure; presence of freckles and moles;
and colour of skin, hair, among other exposures. They found that melanoma was higher in individuals who
used UVB enhances and primarily UVA-emitting devices.
• The risk of melanoma also increased with increase in years of use, hours of use, and sessions.
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37. Risk factors for erysipelas (Pitche et al 2015)
• Pitché et al (2015) conducted a case-control study to assess the factors associated with leg
erysipelas in sub-Saharan Africa.
• This was a multi-centre study; the cases and controls were recruited from eight countries in sub-
Saharan Africa.
• They recruited cases of acute leg cellulitis in these eight countries. They recruited two controls for
each case; these were matched for age (+/- 5 years) and sex.
• Thus, the final study has 364 cases and 728 controls. They found that leg erysipelas was associated
with obesity, lympoedema, neglected traumatic wound, toe-web intertrigo, and voluntary cosmetic
depigmentation.
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38. Strengths of a Case-Control Study
• Case-Control studies can usually be conducted relatively faster and are
inexpensive – particularly when compared with cohort studies (prospective)
• It is useful to study rare outcomes and outcomes with long latent periods.
• For example, if we wish to study the factors associated with melanoma in India, it
will be useful to conduct a case-control study. We will recruit cases of melanoma
as cases in one study site or multiple study sites. If we were to conduct a cohort
study for this research question, we may to have follow individuals (with the
exposure under study) for many years before the occurrence of the outcome
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39. • It is also useful to study multiple exposures in the same outcome.
• For example, in the metabolic syndrome and psoriasis study, we can study other factors such as
Vitamin D levels or genetic markers
• Case-control studies are useful to study the association of risk factors and outcomes in outbreak
investigations.
• For instance, Freeman and colleagues (2015) in a study published in 2015 conducted a case-control
study to evaluate the role of proton pump inhibitors in an outbreak of non-typhoidal salmonellosis.
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40. Limitations of a Case-control Study
• The design, in general, is not useful to study rare exposures. It may be prudent to conduct a cohort
study for rare exposures
• We are not able to estimate the incidence or prevalence in a case-control study
• Why can’t we comment on the incidence or prevalence of the disease?
• Since the investigator chooses the number of cases and controls, the proportion of cases may not be
representative of the proportion in the population. For instance if we choose 50 cases of psoriasis
and 50 controls, the prevalence of proportion of psoriasis cases in our study will be 50%. This is
not true prevalence. If we had chosen 50 cases of psoriasis and 100 controls, then the proportion of
the cases will be 33%.
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41. • The design is not useful to study multiple outcomes. Since the cases are selected based on the
outcome, we can only study the association between exposures and that particular outcome
• Sometimes the temporality of the exposure and outcome may not be clearly established in case-
control studies
• The case-control studies are also prone to certain biases
• In general, individuals may not be able to recall all exposures accurately.
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