BRIEF PRESENTATION OF STUDY DESIGN WITH THE BIASES

1. DR. SWATI SHIKHA
JR(A)
Dept of PSM
RIMS

2.  Introduction : need and the design of case control
study
 Basic steps
 Estimating the sample size
 To describe measure of association in case control
study and its interpretation
 To discuss potential biases in case control study
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5.  Definition:
“The observational epidemiological study of persons with the
disease (or other outcome variable) of interest and a suitable
control(comparison / reference) group of persons without the
disease”
(Dictionary of epidemiology; 4th edition, John M Last)
 Subtype of analytical observational study
 Also called as - Retrospective study design
- TROHOC study etc
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6. population
cases
controls
Exposed
Not exposed
EEExposed
Not exposed
Direction of study
Time
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7.  Observational, non experimental
 Explanatory (analytical)
 Both exposure and outcome have occurred before the start of
the study
 Proceeds backward from outcome(effect) to exposure (cause)
i.e Retrospective
 It uses a control or a comparison group to support or refute an
inference
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8.  Disease Perspective
 The disease is rare
 The disease has a long
incubation and latent period
 Data on exposure is
meager or expensive to
obtain
 The study population is
dynamic
 The risk factors for the
disease is not known
 Researcher perspective
 Limited resources in terms
of material and time.
 Investigating multiple risk
factors
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9.  Research question- based on PECO
 Methods – objectives and sample size
 Selection of cases and controls
 Matching
 Ascertainment of exposure
 Analysis and interpretation
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11.  Clear case definition for accurate classification of diseased
and non-diseased
 Cases comprise all (or a representative sample of) members
of a defined population who develop a given health outcome
during a given period of time.
 Efficient and accurate sources should be used to identify cases
 Incident cases are preferable to prevalent cases
 Sources of cases:
Hospital, disease registries, Special surveys etc .
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12.  Most important step
 The guiding principle for valid selection of cases and
controls is that they represent the same base population
 Controls must be sampled independently of exposure
status
 Sources
Population controls
Hospital or clinic controls
Dead controls
Friend, spouse and relative controls (case nominate)
Neighborhood controls
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13.  At least 1 control for each case.
 Can select 2 /3/ 4 … 100 controls per case: BUT
More Controls, More Resources
 Do not gain much statistical power if more that 4
Controls per case are enrolled
 Multiple controls a) Same type
b) Different type
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15.  Arises when cases and control may not be representative of
cases and control in the general population.
 There may be systematic differences in the characteristic of
cases and control
 Types:
• Berkson’s Paradox
• Neyman Fallacy
• Selective Referral
• Detection Bias
• Non-Response
• Length of Hospital Stay Bias
• Survival Bias
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17.  A type of selection bias which arises when the samples are not
taken from the general population but from sub population,
eg: hospital.
 Hospital samples may exhibit spurious associations between
two variables, even though these variables are independently
distributed in the general population.
 eg: medication-diseases associations Laxative use and
arthritic disease
OR (General Population): 1.48
OR (Hospital Sample): 5.00
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20.  A selection bias where the very sick or very well (or both) are
erroneously excluded from a study.
 Excluding patients who have died will make conditions look
less severe.
 Excluding patients who have recovered will make conditions
look more severe.
 also called prevalence-incidence bias, selective survival bias
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21.  If cases within the population are differentially reported to
study hospital.
 Tertiary Care Hospital: Complicated/Severe D Which may
differ etiologically from other cases.
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22.  A situation in which an association between an
exposure and an outcome is entirely or partially due
to another exposure which is called confounder
 Must be associated with exposure of interest
 Must be a risk factor for outcome of interest
 Must not be on the causal pathway
 Confounding masks the true effect of a risk factor on
a disease or outcome due to the presence of another
variable
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Confounder
(Smoking)
Exposure of
interest
( Drinking
coffee)
Outcome of
interest
(Carcinoma
pancreas)

24. During study design:
 Randomisation
 Restriction
 Matching
During analysis:
 Stratification
 Standardization
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25.  Cases and controls might differ in the characteristic or exposure
other than the one that is targeted for the study
 Purpose: To adjust - effects of relevant confounders
 Involves only those variables which improve statistical efficiency or
eliminate bias from the effect of interest.
 Matching is of two types:
(a) group matching
(b) individual matching
 Unplanned matching
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26. Matching of variables other than those which we are
sure are not risk factors for the disease of interest
either in a planned manner or inadvertent manner is
called overmatching.
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27.  Standardized methods should be used:
by Interview by review
Questionnaire records, biomarkers
 Methods should be applied similarly in both case and control
groups
 Selection on particular source depends on availability,
accuracy, logistics and cost
 Accuracy is a particular concern in case-control study
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28.  Occurs when the means for obtaining information about the
subject in the study are inadequate so that as a result some of
the information gathered regarding exposure or disease
outcome is incorrect.
 Types:
- Interviewers bias
- Surveillance bias
- Recall bias ( main problem in case control study)
- Reporting bias
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29.  When interviewer knows the hypothesis and also
knows who the cases are. Eg: OCP consumption
leads to breast carcinoma.
 Check on this type of bias can be made by noting the
time of interview of cases and control.
 Eliminated by double blinding.
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30.  A non random type of information bias
 Refers to the idea : the more you look, the more you find.
eg: DVT reported after trauma.
REPORTING BIAS
 Reporting bias is defined as "selective revealing or
suppression of information" by subjects (for example about
past medical history, smoking etc)
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31.  Also called as memory bias
Eg: A study to find out whether maternal infection
during pregnancy leads to congenital malformation in
the neonate.
 Cases can better recall the past history as compared
to controls
 Called as rumination bias by “Ernst Wynder”
 Eliminated by : prospective studies
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32.  Compare rates of exposure across cases and
controls i.e Proportion exposed rates among cases
and controls
 Measure of Associations
- Odds Ratio and confidence interval
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33. a b
c d
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Cases [CHD]
(with disease)
Controls[no CHD]
(without disease)
Exposed
[Smokers]
Not Exposed
[Non Smokers]
a + c b + dTotals
Proportions Exposed a / a+c b / b+d

34. Exposure Diseased Non diseased Total
Yes a b a + b
No c d c + d
Total a + c b + d a + b + c + d
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 Odds that cases were exposed = a/c
Odds that controls were exposed = b/d

35. = Odds that cases were exposed
Odds that controls were exposed
= a/c
b/d
= a * d
b * c
Odds ratio is a measure of strength of association.
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36.  OR = 1 Exposure is not related to the
disease
 OR >1 Exposure is positively related to the
disease i.e causal to disease
 OR <1 Exposure is negatively related to the
disease i.e protective to the disease
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37.  95% CI value is taken.
 An odds ratio of 5.2 with a confidence interval of 3.2 to 7.2
suggests that there is a 95% probability that the true odds
ratio would be likely to lie in the range 3.2-7.2 assuming
there is no bias or confounding.
 Odds ratio should ideally be given with limits of confidence
interval.
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38. Research Question:
Whether there is an association between coffee
drinking and occurence of pancreatic carcinoma??
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exposure Cases
(pancreatic
carcinoma)
Controls
(healthy
individuals)
total
Coffee drinking
+
90 20 110
Coffee drinking
-
10 80 90
total 100 100 200

39. Research Question:
Whether there is any association between the
development of lung cancer and history of uranium
exposure through mining??
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Exposure Cases
(lung cancer
pts.)
Controls
(Healthy
individuals)
Total
Uranium mining
+
23 0 23
Uranium mining
-
9 64 73
Total 32 64 96

40. ADVANTAGES
 Can obtain findings quickly
 Can often be undertaken
with minimal funding
 Efficient for rare diseases
 Can study multiple
exposures
 Generally requires few
study subjects
DISADVANTAGES
 Inefficient for rare exposure
 Subject to bias
 Difficult if record keeping
is either inadequate or
unreliable
 Selection of controls can be
difficult
 Difficult to ascertain
temporal relationship
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41.  Evaluating Vaccine Effectiveness
 Evaluations of Treatment & Program
 Efficacy
 Evaluation of Screening
 Outbreak Investigations
 Indirect Estimation in Demography
 Genetic Epidemiology
 Occupational Health Research
 Predictive Modeling
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42.  Study material from workshop on advanced
epidemiology – NIMHANS
 Epidemiology – Leon Gordis, 5th edition
 Parks textbook of Preventive and Social Medicine,
24th edition
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