medical research

1. OBSERVATIONAL (NON-EXPERIMENTAL)
STUDY DESIGN
AUWAL KABIR IBRAHIM
MSC. RADIOLOGY,(BUK) PRESENTATION.
5/12/2023
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2. • Introduction
• Types:
Descriptive & Analytical
• Measure of risk
• Bias in observational study
• Conclusion
OUTLINE
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3. Introduction
• In an epidemiological study there is one or both of the following:
(a) Outcome(s) of interest
(b) Exposure(s) (or potential risk factors) of interest
Plus
• Other exposures that may influence the outcome (potential
confounders)

4. Introduction cont.
• The definition of both the “exposure” and “outcome” depends on the
question you are asking
• Exposure may be an environmental hazard, chemical, or something as
simple as age or a genetic factor like blood group or sickle cell trait.

5. Cont.
• Question1: Is consumption of aflatoxin associated with increased risk
of liver cancer?
• Aflatoxin - Exposure Liver cancer -Outcome
• Question 2: Are certain people more prone to develop liver cancer
after consumption of aflatoxin than others?

6. Cont.
• An outcome in one study could be exposure in another
• e.g Is alcohol consumption during pregnancy associated with
increased risk of low birth weight?
• Is low birth weight associated with hypertension in later life?

7. • Epidemiological study design are broadly classified into two(2)
major groups:
1) Observational(non experimental)
2) Interventional(experimental)
Classification.
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8. RESEARCH/STUDY DESIGN
INTERVENTIONAL/EXPERIMENTAL
DECRIPTIVE
Case Report
Case series
Cross-sectional
study
Correlational
study
CASE-
CONTROL
study
COHORT
study
Randomize
d control
trial
Non
Randomized
control trial
OBSERVATIONAL
ANALYTICAL
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9. OBSERVATIONAL
• The investigator does not attempt to interfere with the process
being studied.
• He/she observes the events that occur in a population.
• In this kind of study allocation into groups on the basis of
exposure to a factor is not under the control of the investigator.
• Observational studies are subclassified into:
1) Descriptive
2) Analytical
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10. DESCRIPTIVE STUDIES
• These types of studies are the 1st stage in understanding of the
disease pattern or health problem in a given population.
• The researcher is often concerned about the distribution of
disease (or condition, or risk factors) in the population.
• The size and nature of distribution of diseases or health related
problem are described without any attempt at establishing a
relationship between cause and outcome.
• Distribution of the disease or health problem in terms of
frequency of occurrence, who(person) is affected, indices of
person include basic demographic factors example age, sex,
marital status 10

11. DESCRIPTIVE STUDIES
• Where(place) it occurs.
• Characteristics of place refers to geographical distribution of the disease including
variation among countries and within countries including urban and rural areas.
• When(time) it occurs for instance seasonal variation in disease occurrence,
disease trends over decades, occurrence in excess of expectancy(epidemic) etc…
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12. DESCRIPTIVE STUDIES
• Descriptive studies in general are useful for planning and
prioritization of health services.
• They also provide clues for the formulation of hypothesis.
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13. CORRELATIONAL/ECOLOGICAL STUDIES
• Use data from an entire population to compare disease frequencies between
different groups during the same period of time or in the same population at
different points in time.
• In correlational studies, the group rather than the individual is the unit of
comparison.
• Disease rates in various groups are usually defined as groups living within
specified geographical area example countries or communities are compared.
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14. CORRELATIONAL CONTD…
• The variation in rate from one area to another may be explained by correlation
between this rate and risk factors in these areas.
• While ecological studies are used for formulation of hypothesis, they cannot be
used to draw conclusions regarding individual risk because refer to groups rather
than to individuals.
• Our inability to draw conclusions about individual risk from group risk is called
ecologic fallacy.
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15. Cont.
• E.g Average intake of salt in a population and the mortality rate from stroke in
that same population.
• Can be done for several different countries and the data examined for a
relationship between the salt intake of a population and rate of disease.
• It is important to understand that the only conclusion one can draw relates to
populations.
• It is not possible from an ecological study to draw conclusions about exposure in
the individual and the risk of the outcome.

16. CASE REPORT & CASE SERIES
• The case report is the most basic type of descriptive study of
individuals.
• It consist of a careful detailed report of the profile of a single
patient who has some unusual presentations of a known or
unknown disease.
• Represent first clues in the identification of new diseases or
adverse effects of exposures
• Example, first case of Ebola, Covid-19 etc.
• Such a cases could be investigated as clinical history, physical
examination, laboratory investigation with discussion segment
and could be reported through a journal as a case report. A
collection of similar cases constitutes case series.
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17. CROSS-SECTIONAL STUDIES
• This study design is used for study of disease prevalence in a given community or
population at a given point in time.
• Are the simplest type of epidemiological studies.
• The status of an individual with the present or absent of disease and risk factors
are assessed at the same point in time.
• It involves a single examination of a cross-section of a population(snap shot).
• The disease occurrence is related to personal characteristics such as age, sex,
occupation, educational status, social class, religion, ethnicity etc…
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18. CROSS-SECTIONAL STUDIES CONTD…
• It also describe in terms of place of occurrence using
geographical location, sunlight, rainfall, vegetation, urban and
rural areas, humidity and temperature.
• The cross sectional study takes a snap shot at a point in time in
a given population to describe the frequency of occurrence of
a given disease and associated factors.
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19. CHARACTERISTICS OF CROSS-SECTIONAL STUDY
• They measure the prevalence of the disease.
• They are useful for description of characteristics of those that are affected in
terms of who(person), when(time) and where(place)
• They are more useful for disease of long duration(chronic) rather than those of
short duration.
• They are relatively easier to execute and take a short time
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20. Types of cross-sectional study
• Cross‐sectional studies may be either descriptive or analytical.
- Descriptive
• Information is collected from individuals on outcome(s), or exposure(s), but
not both.
• They aim to provide estimates of prevalence of disease, traits such as
smoking, behaviour, people′s attitudes, knowledge or health behaviour.
- Analytical
• Information is collected from individuals on both outcome(s) and
exposure(s).
• They aim to assess associations between different parameters.

21. Disadvantages
• Unable to measure the incidence.
• Not suitable for studying rare diseases or diseases with a short
duration.
• Cannot measure risk
• Difficult to make a causal inference.
• Prone to both non-response bias and recall bias.

22. LONGITUDINAL STUDIES
• This study type is used to describe or monitor the occurrence
of new cases of disease in a given population over a period of
time.
CHARACTERISTICS
• They measure incidence rate of disease.
• They are useful for studying natural history of disease and
surveillance.
• They are useful for studying diseases with short
duration(acute)
• They are costly to organize and time consuming.
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23. ANALYTICAL STUDIES
• They are concerned with the assessment of determinants/causes of diseases.
• They are expected to provide answers as to why and how the disease occurs.
• This is done by testing a given hypothesis which has linked a particular causative
agent or risk factor to a given disease.
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24. TYPES OF ANALYTICAL STUDIES
• 1) Case control/Retrospective study
• 2) Cohort/Prospective study
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25. CASE CONTROL STUDY
• Is aimed at testing a given epidemiological hypothesis regarding the association
between a suspected etiological/risk factor and the occurrence of a disease by
comparing frequency of exposure to the etiological factor in a group with the
disease(cases) and another group without the disease(control).
• The investigator select cases(those with the disease under study) and control that
have similar characteristics with the cases but don’t have the disease under
study.
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26. CASE CONTROL CONTD…
• He/she examines their previous experience in terms of history of exposure to the
suspected risk factor.
• The investigator looks backward in time or retrospectively.
• Case control studies are relatively easier, quicker and cheaper compared to
cohort studies.
• It is reserve for rare disease and a number of risk factor can be assessed
simultaneously.
• However, it does not give a direct measure of risk instead it gives an
approximation called odd ratio(OR) 26

27. • The starting point in case-control studies is the definition of a group of people
with a particular disease or condition.
• Suitable controls without the disease, and representing the population from
which the cases originated, are also selected.
• Information on the prevalence of past exposure in cases and controls is then
collected.

28. • The source of the cases needs to be clearly defined.
• In a population-based study, cases might be all possible individuals with the
disease arising within a defined population within a fixed period of time.
• In this situation the ‘base’ is the defined population, and there might be multiple
sources of cases - surveillance, death certificates, pathology records etc.
• Alternatively, the study may be hospital-based – the source of cases might be all
patients fulfilling the case definition who attend one or more specific hospitals.
• Here, the cases in the study may arise from a more selective population.

29. Measurement of Association
• The statistic used to evaluate case-control studies is the Odds Ratio
(OR)
• The OR estimates the ratio of the forces of morbidity between
persons exposed and not exposed to a risk factor

30. Concept of Odds
• Odds of event can be defined as the ratio of the number of ways the
event can occur to the number of ways the event cannot occur.
• Odds = probability of event occurring
probability of event not occurring

31. MEASURES OF RISK IN CASE CONTROL STUDIES(OR)
• OR = Odds of exposure among cases
Odds of exposure among controls
0R= A over B = AD
C D BC 31
CASES CONTROL
DISEASE PRESENT DISEASE ABSENT
EXPOSED A B A+B
UNEXPOSED C D C+D
A+C B+D A+B+C+D

32. MEASURES OF RISK IN CASE CONTROL STUDY(OR)
QUIZ
Data from a case control study of exposure to the gonads on
fluoroscopic procedure with and without protective lead apron and
development of sterility among men aged 30-40years is as follows:
Compute an appropriate measure of risk and interpret.
32
STERILITY
PRESENT
STERILITY ABSENT
YES 23 304 327
NO 133 2816 2949
156 3120 3276
HISTORY
OF
USE
OF
APRON

33. MEASURES OF RISK IN CASE CONTROL(SOLUTION)
OR= AD/BC
OR=1.6 33
STERILITY
PRESENT
STERILITY
ABSENT
YES 23 304 327
NO 133 2816 2949
156 3120 3276
HISTORY
OF
USE
OF
APRON

34. Case-control study: Merits
• They are particularly well-suited for the evaluation of rare diseases
• Useful for testing hypothesis
• Relatively cheap
• Require fewer participants
• There is no problem with losses to follow-up since this is a
retrospective design

35. Demerits
• Prone to biases, especially recall bias.
• Can only look at one outcome.
• Selection of appropriate control group may be difficult.
• Cannot measure incidence.
• Problem in sorting out the temporal relationship between exposure
and disease
• Not suitable for studying rare exposures.

36. COHORT STUDIES
• This derives its name from the term cohort, which means a
group of people who share a common experience within a
defined period.
• Some example of cohort include birth cohort, marital cohort,
occupational cohort, resident preparing for
membership/fellowship examination etc…
• Cohort studies are prospective studies, because they look
forward in time from exposure to disease
• They are used in investigating the relationship between a risk
factor and disease.
• In this type of study the investigator compares the incidence
rate of disease in a group of individuals exposed to the
factor(study cohort) compared to another group of individuals
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37. Cont.
• The key concept to remember is that in cohort studies, the exposure status is
always determined before the outcome.
• Cohort studies are not always conducted in real time – they can be conducted
using historical records, or data collected in the past.

38. COHORT STUDIES CONTD…
• The investigator starts with cohort of healthy individuals who
are classified according to exposure to risk factor as study and
control cohorts.
• Both groups are followed up into the future(prospectively) and
the incidence rate of the disease are compared between the
two groups.
• A cohort study has the advantage of giving direct estimation of
risk exposure to a given factor.
• However, cohort studies are expensive and time consuming.
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39. Cohort studies: Purpose
• The goal of a cohort study is to identify the effects of an exposure
with respect to a certain outcome
• Research Question:
• Is prior exposure related (or not) to the occurrence of an outcome ?

40. COHORT STUDIES CONTD…
• They are better suited for common diseases with shorter
incubation period.
• Overall, the evidence obtained from cohort study is stronger than
that obtained from case control study.
• The measure of risk in cohort study is relative risk(RR).
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41. • The Relative Risk (RR) is used to determine whether the rate of
incidence among the Exposed is greater than the rate of incidence
among the Unexposed
• The RR can assume the following values:
• >1
• =1
• <1

42. Developed disease
Present (exposed)
Yes No
Absent (not exposed)
Total
a
c
b
d
a + b
c + d
Exposure or
characteristic
Cohort studies: Analysis
RR =
Incidence in exposed group
Incidence in unexposed group
=
a/(a + b)
c/(c + d)
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1/7/2024 11:46 AM

43. COHORT CONTD…(SOLUTION)
• Data from a cohort study of abdominal CT exposure and
development of fetal anomalies among pregnant women aged 18-
35years is as follows
RR = 5151 = 1.4
37114
43
FETAL ANOMALY
PRESENT
FETAL ANOMALY
ABSENT
YES 27 455 482
NO 77 1831 1908
104 2286 2390
ABDOMINAL
CT
EXPOSURE

44. ATTRIBUTABLE RISK
• Is a measure of excess risk of disease in those exposed
compared to the unexposed.
• It is the difference between incidence rate of the disease
among the exposed group(Ie) and the unexposed group(Io)
divided by incidence rate of disease among exposed(Ie)
multiply by 100
• Measures the benefit those exposed will derive if they avoid
the exposure.
• It is express in percentage.
• Mathematically expressed as: AR= Ie-Io x100%
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45. MEASUREMENT OF RISK IN COHORT STUDIES CONTD
• Attributable risk(AR)
 AR= Incidence rate of disease among exposed(Ie) - Incidence
rate of the disease among unexposed group(Io) X 100%
Incidence rate of disease among exposed group
• AR= Ie-Io x100%
Ie
AR= {27 } - {77} over 27 = answer multiply by 100%= 27.9%
482 1908 482
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46. Cohort study - benefits
• Incidence rates can be calculated therefore true relative risk can be
calculated.
• Useful for testing hypothesis
• Cohort studies permit observation of many outcomes i.e. can yield
association with additional disease as by-product e.g. coronary
heart disease in smoking.
• Less possibilities of introducing bias if good criteria and procedures
for conducting the study are established in advance

47. Cohort study- demerits
• Large number of subjects required
• Usually requires long follow up periods
• High attrition rate- loss of study unit
• Participation in the study can affect the behavior of the exposed and unexposed
subjects (Hawthorne effect)
• Very costly
• Changes in diagnostic criteria and methods with time

48. BIAS IN OBSERVATIONAL STUDY
• Bias is an error in the research methodology that may cause the results of the
study to deviate from the truth.
• The main source of bias in radiology studies are:
Patient
Intervention/exposure
Data gathering
Interpretation/reporting approaches.
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49. BIAS CONTD…
• Bias can occur at any point during the study including
recruitment, intervention, data collection, analysis and
publication.
• While there are some advanced statistical techniques that can
be used to ameliorate the impact of bias introduced by errors
in the study design, it is best to avoid introducing the bias as it
may not be possible to minimize the impact of bias on the
results once introduced.
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50. Types of bias
1. Selection bias
2. Information bias
3. Comfounding

51. Selection bias
• Is the distortion in a measure of association due to a sample selection that does
not accurately reflect the target population.
• It occurs when the selected study participants are systematically different in
characteristics from the eligible participants who are not selected for the study.
• Eg health studies that recruit participants directly from clinics miss all cases who
do not attend clinics or seek care during study
• Due to this, the sample and the target population differ in significant ways
limiting your ability to generalized your findings.
• Types of selection bias- attrition, sampling bias, non response bias etc

52. Information bias
• Refers to systemic errors in measurement(misclassification) of the exposure or
outcomes.
• Eg wrong, incomplete or inexact recording of variables

53. CONFOUNDING
• Confounding is a particular type of bias that results from a factor being
introduced that is associated with the exposure and the outcome, but is not part
of the casual pathway between the exposure of interest and the outcome, yet
impacts the outcome.
• Confounding is a particular concern in nonexperimental designs, whereby factors
other than random chance determines which treatment a subject receives and it
is these factors (confounders) that may impact outcome, rather than differences
in the treatment received.
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54. CONFOUNDING CONTD…
This type of confounding is referred to as confounding by
indication, and is a key reason why randomization , by avoiding
confounding by indication, allows for unbiased assessments of
treatment response.
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55. METHODS OF CONTROLLING FOR SELECTION BIAS AND CONFOUNDING
• Randomization
• Specification
• Matching
• Stratification
• Simple adjustment
• Multiple adjustment
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56. Conclusion
• Observational study make important contribution to the knowledge
of the distribution and causes of the diseases
• Observational studies are often the best approach, particularly for
long period of observation, for rare effect or when experimental
studies would be un ethical.

57. THANK YOU FOR LISTENING