Casecontrolstudy

Presentation by: Dr. N. Sarah Sheela Emerald
2nd year PG student
Dept. of Public Health Dentistry

 Introduction
 Definition
 Study designs
 Epidemiological study cycle
 Analytical studies
 Case control study
 Definitions
 History
 Design
 Selection of cases and controls
 Matching
 Measurement of exposure
 Analysis and interpretation

 Outcomes
 Limitations
 Advantages and Applications
 Nested case control studies
 Important findings of case control studies
 Conclusion
 References

 Epidemiology is the branch of public health
which attempts to discover the causes of disease
in order to make disease prevention possible.
 Although the epidemiological approach has been
used for more than a century for the study of
communicable diseases, epidemiology has
considerably grown in scope and sophistication
in the last few decade as it has been increasingly
applied to the study of non communicable
diseases.

 Although epidemiologic thinking has been
traced from Hippocrates (circa 400 B.C.) through
Graunt (1662), Farr, Snow (both mid-1800’s), and
others, the discipline did not blossom until the
end of the SecondWorld War.

 There is no single definition of epidemiology to which all
epidemiologists subscribe,but three components are
common to most of them. First, studies of disease
frequency; second, studies of the distribution; and third,
studies of the determinants. Each of these components
confers an important message.
 Epidemiology has been defined by John M. Last in 1988
as "The study of the distribution and determinants of
health-related states or events in specified populations,
and the application of this study to the control of health
problems".

 A study design is a specific plan or protocol
for conducting the study, which allows the
investigator to translate the conceptual
hypothesis into an operational one.
 Study designs direct how the investigation is
conducted

Purpose :
 Exploratory -To formulate the problem, develop the
hypothesis, establish priorities for research, refine
ideas, clarify concepts.
 Descriptive - describe characteristics of certain
groups, estimate portion of people in a population
who behave in a given way and to make directional
predictions.
 Causal -To provide evidence of the relationship
between variables, the sequence in which events
occur, and or to eliminate other possible
explanations.

1) Observational Descriptive
2) Experimental Analytical
Analytical Case-control
Cohort Prospective cohort
Retrospective cohort
Combination

Experimental Randomized controlled trials
Non-randomized controlled trials
RCT types - Clinical trials
preventive trials
Community intervention trials
Non RCT types - Natural experiments
Before and after comparison studies

 The sequence of events starting with description
of disease or health related event in relation to
time, place, person searching for and finding
differences in occurrence in different populations
formulating hypotheses regarding possible
causative factors and testing them, analyzing the
results. Results may lead to further descriptive
studies or new hypotheses.

DESCRIPTIVE STUDY
• Ca Lung increasing  mostly smokers
• Death rates higher in populations with
higher per capita cigarette consumption
CASE CONTROL STUDY • Ca Lung patients and non patients
Clarifies if it was smokers who contributed
to high Ca Lung
COHORT STUDY • Follows a cohort of smokers and non
smokers without Ca Lung
•Smokers develop Ca Lung more frequently
INTERVENTIONALTRIAL
(RCT) •Proves hypothesis conclusively
•Gives inputs regarding other factors, control measures.
Hypothesis:
Smoking
causes Ca Lung

 Observational
 Case control (Retrospective) studies
 Cohort (Prospective) studies
 Experimental (Interventional):
 Animal experiments
 Human studies
• Therapeutic trials
• Preventive trials
Difference in study
groups is
ONLY observed &
analysed,
NOT created
experimentally
Difference in study
groups is
CREATED
EXPERIMENTALLY
and outcomes
observed

 Purpose:To produce a valid estimate of a
hypothesised cause-effect relationship between
suspected risk factor and disease.
Case Control Study Cohort Study
Starts with diseased (cases)
& not diseased (controls)
Starts with not diseased but
exposed
& not exposed
Determine if 2 groups differ in exposure
to specific factor or factors
Followed up to determine difference in
rates at which disease develops in
relation to exposure
Called as case control study due to the way
in which study group is assembled
Called so because of the use of a “cohort”
(a group of people who share a common
characteristic or experience)

Retrospective
(Case-Control)
a b
dc
DISEASEpresent absent
E
X
P
O
S
U
R
E
present
absent
cases controls
Total Total
Prospective
(Cohort)
exposed
Not exposed
A fourfold table
Mausner, 1985

Case Control Studies Cohort Studies
Proceeds from effect to cause Proceeds from cause to effect
Starts with the disease
Starts with people exposed to the risk factor
or suspected cause
Tests whether the suspected cause occurs
more frequently in those with disease than
those without disease
Tests whether disease occurs more frequently
in those exposed than in those not exposed
Usually the 1st approach to the testing of
hypothesis, but also useful for exploratory
studies
Reserved for the testing of precisely
formulated hypothesis
Involves fewer study subjects Involves larger number of subjects
Yields results relatively quickly Long follow-up, delayed results
Suitable for study of rare diseases
Inappropriate when disease or exposure under
investigation is rare
Generally, yields only estimate of relative risk
(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
Relatively inexpensive Expensive

 Case control study synonyms:
 Case comparison study
 Case compeer study
 Case history study
 Case referent study
 Retrospective study
 Case control study definitions:
 The observational epidemiologic 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: 3rd ed; John M Last. 2000)

 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). (National
Institute of Health, USA)
 A case control study involves two populations –
cases and controls and has three distinct features
 Both exposure and outcome have occurred before the
start of the study.
 The study proceeds backwards from effect to cause.
 It uses a control or comparison group to support or refute
an inference.
(Park’sTextbook of Preventive and Social Medicine – 22nd ed; K. Park. )

 Case : A person in the population or study group
identified as having the particular disease, health
disorder or condition under investigation. (Dictionary
of Epidemiology: 3rd ed; John M Last. 2000)
Control: Person or persons in a comparison
group that differs, in disease experience (or
other health related outcome) in not having
the outcome being studied. (Dictionary of Epidemiology: 3rd
ed; John M Last. 2000)

 Bias: Any systematic error in the design, conduct, or
analysis of a study that results in mistaken
estimates of the effect of the exposure on disease.
 Confounding: When a measure of the effect of
an exposure on risk is distorted because of the
association of exposure with other factors that
influence the outcome. It creates data where it
is not possible to separate the contribution that
any single causal factor has made an effect.

 The basic study design has a long history, extending
back at least to Guy’s 1843 comparison of the
occupations of men with pulmonary consumption to
the occupations of men having other diseases.
 Beginning in the 1920’s, it was used to link cancer to
environmental and hormonal exposures.
 Broders (1920) discovered an association between pipe
smoking and lip cancer.

 Lane-Claypon (1926), who selected matched hospital
controls, investigated the relationship between
reproductive experience and female breast cancer; and
Lombard and Doering (1928) related pipe smoking to
oral cancer.
 The landmark study of Doll and Hill (1950, 1952), in
particular, inspired future generations of
epidemiologists to use this methodology. It remains to
this day a model for the design and conduct of case-
control studies, with excellent suggestions on how to
reduce or eliminate selection, interview and recall bias.

 From the mid-1950’s to the mid-1970’s the number of
case-control studies published in selected medical
journals increased four to sevenfold (Cole 1979).

The investigator selects
cases with the disease
and appropriate
controls without the disease
and obtains
data regarding past exposure
to possible etiologic factors in both groups.
The investigator then compares the frequency of
exposure of the two groups.

 Hallmark of Case Control Study: Starts from cases
and controls and searches for exposure.
Disease No Disease
“CASES” “CONTROLS”
Not ExposedExposed Exposed Not Exposed

FIRST: Select
CASES CONTROLS
(With Disease) (Without Disease)
THEN: Were exposed a b
Measure
Exposure Were not exposed c d
TOTALS a + c b + d
Proportions a b
Exposed a + c b + d

 The 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

 The first step is to identify a suitable group of
cases and controls.
 The selection of case involves two main
components:
1. Definition of a case
2. Sources of case

Definition of a case:
The definition of what constitutes case is crucial to
the case control study.
It involves two specifications:
a) Diagnostic criteria
b) Eligibility criteria
The diagnostic criteria of the disease and the stage
of disease, if any, to be included in the study
should be specified before the study is undertaken.

Once the diagnostic criteria are established, they
should not be altered or changed till the study is
over.
An eligibility criterion customarily employed is the
requirement that only newly diagnosed (incident)
cases within a specified period of time are eligible
than old cases or cases in advanced stages of the
disease
It eliminates the possibility of long term survivors
of a disease were exposed to the investigated risk
factors after the onset of disease.

Sources of cases:
 Hospitals
 General population
 Incident cases in an ongoing cohort study
 Incident cases of an occupational cohort

 Ideally, cases are a random sample of all cases of
interest in the source population (e.g. from vital data,
registry data).
 More commonly they are a selection of available cases
from a medical care facility. (e.g. from hospitals,
clinics)
 Selection may be from incidence or prevalence case:
Incident cases are those derived from ongoing-
ascertainment of cases over time.
Prevalent cases are derived from a cross-sectional
survey.

 Incident cases should be all newly diagnosed cases
over a given period of time in a defined population.
 Prevalent cases do NOT include patients with a short
course of disease. So patients who recovered early
and those who died will not be included.
 Diagnostic criteria regarding diagnosis of cases,
types of cases and stage of disease to be included
should be predefined.
 Validity is more important than generalizability i.e.
the need to establish an etiologic relationship is
more important than to generalize results to the
population.

 They must be as similar to the cases as possible,
except for the absence of the disease under study.
 As a rule, a comparison group is identified before
a study is done, comprising of persons who have
not been exposed to the disease.
 The control group should be representative of the
general population in terms of probability of
exposure to the risk factor.

 They should also have had the same opportunity to
be exposed as the cases have.
 Not that both cases and controls are equally exposed;
but only that they have had the same opportunity for
exposure.
 Usually, cases in a case-control study are not a
random sample of all cases in the population. And if
so, the controls must be selected in the same way
(and with the same biases) as the cases.
 The control should be at risk of the disease

“Total” Population
Reference
Population
Cases Controls

Selection of Controls: Sources

 Large study: Cases: Control :: 1:1
 Small study: Cases: Control :: 1:2, 1:3, 1:4.
 Use of multiple controls
1. Controls of same type:
Cases: Control :: 1:1 ( for rare diseases, cases cannot be
increased in that time), ( increases power of the study).
2. Multiple controls of different types:
controls- 1 hospital, 1 neighbourhood e.g. case-
Children with brain tumour, control- children with other
cancer, normal children, risk factor- h/o radiation
exposure.

Selection of Controls: Objectives
 Elimination of selection bias - Selection
 Minimization of information bias - Blinding
 Minimization of confounding - Matching

 Problems in control selection – Confounding
variables.
 Confounding variables are factors associated with
the exposure of interest and causally with the
disease of interest.
 May lead to a spurious/ biased relationship
between risk factor and disease.
 Common confounding variables are : age, sex,
educational status, socioeconomic level, etc.
 These can be adjusted by :
• Designing the study through Matching

 Matching:
 Definition: It is the selection of controls so that they
are similar to the cases in specified characteristics.
(Epidemiology: An IntroductoryText; Mausner & Bahn, 1985)
 Matching is defined as the process of selecting
controls so that they are similar to cases in certain
characteristics such as age, sex, race, socioeconomic
status and occupation. (Epidemiology; Leon Gordis,
2004)

Matching variables (e.g. age), and matching criteria
(e.g. within the same 5 year age group) must be set up
in advance.
Controls can be individually matched (most common)
or Frequency matched.
Individual matching (Matched pairs): search for one
(or more) controls who have the required matching
criteria, paired (triplet) matching is when there is one
(two) control (s) individually matched to each cases.
 Group matching (Frequency matching): select a
population of controls such that the overall
characteristics of the case, e.g. if 15% cases are under
age 20, 15% of the controls are also.

 Matching: Problems –
 Individual matching on too many variables – is time
consuming, costly, cumbersome and may lead to
too less controls.
 Cannot explore possible association of disease with
any variable on which cases and controls have been
matched.Therefore only factors which are known
to be associated with the disease are studied.
 Suppose we know that breast cancer rates are higher
among single women than in married women; then
matching cases for marital status would spuriously NOT
detect any relation regarding this factor.

 Overmatching: Matching on variables other than
those that are risk factors for the disease under study,
either in a planned manner or inadvertently.
Example: In a study on OCP use as a risk factor for
cancer, if we use “best friend controls”, it is most
likely that the controls would also be OCP users. In
effect we would have matched for the very factor
we want to study.
Example: If we use neighborhood controls in a study
on nutrition and tuberculosis, we would be
inadvertently matching for socioeconomic status
and thus nutrition.

 Definition: Any systematic error in the design,
conduct, or analysis of a study that results in
mistaken estimates of the effect of the exposure
on disease.
 Types of bias in case control studies:
Selection bias
Information bias
Confounding bias

 Selection bias:
 Selection bias is a distortion of the estimate
of effect resulting from the manner in which
the study population is selected.
 The cases and controls may not be
representative of cases and controls in the
general population

 Selection Bias:
 Sources –
1. Selective loss to follow-up
2. Incomplete ascertainment of cases (Detection or
Diagnostic bias)
3. Inappropriate control group
4. Differential motivation to participate

 Special types of selection bias:
a) Prevalence – incidence bias (selective
survival)
b) Admission rate (Berkson’s or Berkesonian)
bias

Selective survival - only surviving subject
available to be studied;
those surviving differ from those dying in potentially
important ways.
Solution: :Rapid case ascertainment and
interview

Berkesonian bias:
The bias arises due to different rates of
admission to hospitals for people with different
diseases
Eg., Hospital cases and controls

Information Bias:
 Occurs due to -
1. Imperfect definitions of study variables
OR
2. Flawed data collection procedures.
 Leads to – Misclassification of disease and exposure.
 Types of Information bias –
 Recall bias
 Interviewer bias
 Telescopic bias

Recall bias (usually in case-control studies): Cases who
are aware of their disease status may be more likely to
recall exposures than controls
e.g. congenital malformation with prenatal infections
Results in misclassification
Solution
• Achieving similarity in the procedures used to
obtain information from cases and controls
• Verify exposure with existing records
• Objective measure of exposure
• Use of information recorded prior to the time
of diagnosis.

 Interviewer bias: When interviewer is not
blinded (knows) case status of subjects there
is potential for interviewer bias.
 Solution –
 Blinding of interviewer as to case status
 Equal interview time for all participants

Telescopic bias:
If a question refers to recent past (say last
month), episodes that occurred longer ago may
also be reported

 Confounding: When a measure of the effect of an
exposure on risk is distorted because of the
association of exposure with other factors that
influence the outcome.
Not possible to separate the contribution that any
single causal factor has made
 Confounding Factor: is one which is associated with
both exposure & disease , and is distributed unequally
in study & control groups.
 E.g.: Alcohol & EsophagealCa ; confounding factor-
smoking
 Solution: Study design : Matching

 Definitions and criteria about exposure (or
variables which may be of etiological importance)
are just as important as those used to define cases
and controls
 This may be obtained by
 Interviews
 Questionnaires
 Study past records of cases such as hospital records,
employment records etc
 Clinical or laboratory examination

 Information about exposure should be obtained
in precisely the same manner for both cases and
controls.
 Investigator should not know whether a subject
is in case or control group (Blinding).

 Exposure rates:
 A case control study provides a direct estimation of the
exposure rates (frequency of exposure) to the suspected
factor in disease and non-disease groups.
Exposure rates
 Cases = a/ (a + c) = 33/ 35 = 94.2%
 Controls = b/ (b + d) = 55/82 = 67.0%
Cases
(lung cancer)
Controls
(without lung cancer)
Smokers 33 (a) 55 (b)
Non Smokers 2 (c) 27 (d)
TOTAL 35 (a + c) 82 (b+d)

 Odds Ratio / Relative odds (estimate of relative
risk).
 Odds: Odds of an event is defined as the ratio of the
number of ways an event can occur to the number of
ways an event cannot occur. (Epidemiology; Leon Gordis. 2004)
 If the probability of event X occurring is P, then odds of it
occurring is = P/ 1-P.
 Odds ratio: Ratio of the odds that the cases were
exposed to the odds that the controls were exposed.

 Odds ratio:
 Using the four-fold table –
Odds that case was exposed
 Odds ratio =
Odds that control was exposed
= (a/c)/ (b/d) = ad / bc
Diseased/ Cases Not diseased/
Controls
Exposed a b
Not exposed c d

 Odds ratio ( = cross products ratio) can also be
viewed as the ratio of the product of the two cells that
support the hypothesis of an association (cells a & d –
diseased people who were exposed and non diseased
people who were not exposed), to the product of the
two cells which negate the hypothesis of an
association (cells b & c – non diseased people who
were exposed and diseased people who were not
exposed).

 Odds ratio is a good estimate of the relative risk in
the population when ..
 Cases studied are representative
 Regarding history of exposure of all people with the
disease in the population from which cases are drawn.
 Controls studied are representative
 Regarding history of exposure of all people without the
disease in the population from which cases are drawn
 When the disease being studied does NOT occur
frequently

 Problems of bias relies on memory or past records,
the accuracy of which may be uncertain; validation
of information obtained is difficult or sometimes
impossible
 Selection of an appropriate control group may be
difficult
 We can’t measure incidence, and can only estimate
the relative risk

 Do not distinguish between causes and associated
factors
 Not suited to the evaluation of therapy or
prophylaxis of diseases
 Another major concern is the representativeness of
cases and controls

 Relatively easy to carry out
 Rapid and inexpensive
 Require comparatively few subjects
 Particular suitable to investigate rare diseases about
which little is known
 No risk to subjects

 Allows the study of several different aetiological
factors
 Risk factors can be identified
 Rational preventive and control programmes can be
established
 No attrition problem, because there is no follow up
 Minimal ethical problem

Rare disease:
Case-control approaches are the most efficient for
rare diseases, e.g idiopathic pulmonary fibrosis, most
cancers.
Cohort approaches would require large populations
and prohibitive expense and follow-up time.

Case ascertainment system in place:
The conduct of a case-control study may be
facilitated by the availability of a case-
ascertainment system.
a) Population-based cancer registry
b) Hospital-based surveillance systems
c) Mandated disease reporting systems
When funding and time constraints are not
compatible with a cohort study.

 A nested case–control study is comprised of
subjects sampled from an assembled
epidemiological cohort study in which the
sampling depends on disease status.
 Nested case – control studies are generally used
when disease is rare and, at the minimum,
disease outcome has been obtained for all
cohort subjects, but it is too expensive to collect
and/or process information on covariates of
interest for the entire cohort.

 A case-cohort study is similar to a nested case-
control study in that the cases and non-cases are
within a parent cohort; cases and non-cases are
identified at time t1, after baseline.
 In a case-cohort study, the cohort members were
assessed for risk factors at any time prior to t1.
Non-cases are randomly selected from the
parent cohort, forming a sub-cohort. No
matching is performed.

 In a case-cohort study, all incident cases in the
cohort are compared to a random subset of
participants who do not develop the disease of
interest.
 In contrast, in a nested-case-control study, some
number of controls are selected for each case
from that case's matched risk set.

Study Population
TIME 1
YEARS
TIME 2
Develop
Disease
Do Not
Develop
Disease
CASES CONTROLS
(Subgroup)
CASE-CONTROL STUDY
Obtain
interviews,
blood,
urines, etc.

 Advantages:
1. Possibility of recall bias is eliminated, since data on
exposure are obtained before disease develops.
2. Exposure data are more likely to represent the pre-
illness state since they are obtained years before
clinical illness is diagnosed.
3. Costs are reduced compared to those of a
prospective study, since laboratory tests need to be
done only on specimens from subjects who are later
chosen as cases or as controls.

1950’s
Cigarette smoking and lung cancer
1970’s
Diethyl stilbestrol and vaginal adenocarcinoma
Post-menopausal estrogens and endometrial cancer
1980 ’s
Aspirin and Reyes sydrome
Tampon use and toxic shocks syndrome
L-tryptopham and eosinophilia-myalgia syndrome
AIDS and sexual practices
1990’s
Vaccine effectiveness
Diet and cancer

 Adenocarcinoma of vagina ~

 Oral contraceptives and thromboembolic
disease

 Thalidomide tragedy (Britain 1958 – 1961)

 Case-control studies may prove an association
but they do not demonstrate causation.
 The temporal relationship between the
supposed cause and effect cannot be
determined by a case-control study.
 We must be aware that the term ‘case-control
study’ is frequently misused. All studies which
contain ‘cases’ and ‘controls’ are not case-control
studies.

 One may start with a group of people with a
known exposure and a comparison group
(‘control group’) without the exposure and follow
them through time to see what outcomes result,
but this does not constitute a case- control
study.
 Case-control studies are sometimes less valued
for being retrospective.

 However, they can be a very efficient way of
identifying an association between an exposure
and an outcome.
 Sometimes they are the only ethical way to
investigate an association.
 If care is taken with definitions, selection of
controls, and reducing the potential for bias, case-
control studies can generate valuable
information.

 Marya CM. A textbook of Public Health Dentistry.
New Delhi: Jaypee brothers Medical Publishers
(P) Ltd; 2011
 Leon Gordis. Epidemiology. 3rd edition.
Pennsylvania: Elsevier Publications; 2004
 Park K. Park’s textbook of preventive and social
medicine. 19th edition. Jabalpur: M/s Banarsidas
Bhanot publishers; 2012

 World Health Organization. Health Research
Methodology, A guide forTraining in Reseasrch
Methods. 2nd edition. Manila: Regional office for
theWestern Pacific; 2011
 Norman E. Breslow. Handbook of Epidemiology.
Berlin: Springer. 2005, pp. 287-319
 Bryan Langholz. Case–Control Study, Nested.
Encyclopedia of Biostatistics Second Edition.
Volume 1, pp. 646–655

 Ursula J. Blumenthal, Jay M. Fleisher, Steve A.
Esrey and Anne Peasey. Epidemiology: a tool for
the assessment of risk.
 Kenneth F Schulz, David A Grimes. Case-control
studies: research in reverse.THE LANCET •Vol
359 • February 2, 2002 • www.thelancet.com
 Nigel Paneth, Ezra Susser, Mervyn Susser.
Origins and early development of the case-
control study. History of epidemiology;2002.

 Susan Lewallen MD Paul Courtright DrPH .
Epidemiology in Practice:Case-Control
Studies

Casecontrolstudy

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