1. Introduction to study Designs
Dr Ajithkumar K
Dean (Research)
KUHS
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3. Pigment reduction in nevus of Ota following leech therapy Sanjeev Rastogi1, Priyanka Chaudhari2
Nevus of Ota is a congenital blue-gray color nevus afflicting unilaterally, the area near the eyes. It poses a huge cosmetic concern besides being a potential threat for developing melanoma sometime in the course of the disease. The treatment options are neither many nor promising besides they are too expensive. We have treated a case of nevus of Ota with leech therapy where leech was applied upon the lesion for five times spanned in a period of 2 months. The results in terms of change in the color of lesion were evaluated with the help of serial photographs following every treatment session to mark the level of color changes in the lesion. A substantial reduction in color of the nevus was reported following the completion of the therapy. The results were demonstrated with the photographs. Although, recommended as the classical Ayurvedic management for skin diseases, leech therapy is not reported earlier in such conditions. It proposes a novel approach to deal with such congenital pigment lesions where other options are not promising.
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6. Case Reports
Detailed presentation of a single case or handful of cases
Generally report a new or unique finding
e.g. previous undescribed disease
e.g. unexpected link between diseases
e.g. unexpected new therapeutic effect
e.g. adverse events
Case reports are in many ways “sentinel events” which can lead to testable hypotheses
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7. Case Reports/ Case Series
The most basic descriptive study
Link between clinical medicine and epidemiology
Hypothesis generating
feasible study designs, are easy to conduct and require less time and financial resources than randomised-controlled trials, case-control, or cohort studies
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8. Case Series Experience of a group of patients with a similar diagnosis
Assesses prevalent disease
Cases may be identified from a single or multiple sources
Generally report on new/unique condition
May be only realistic design for rare disorders
Case series also provide suggestive evidence many times leading to more extensive testing.
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9. cases with denominator
One case of unusual
findings
Case Report
Multiple cases of
findings
Case Series
Descriptive
Epidemiology Study
Descriptive study designs include case reports, case series, incidence studies, and ecologic studies. The case report is the most elementary study design in the literature. It generally describes an injury or injuries to one or two individuals that have been identified in a medical setting. There is also usually a unique feature to the noted chronic disease . The case series design is an extension of the case report. In a case series, a number of events are described. These events usually have been observed over a set period of time (such as one year) and are identified from one reporting source (e.g. a hospital).
The descriptive epidemiology study is noted by the collection of events over a defined population base and by the use of denominator data to determine rates. The most frequent information generated from these designs are incidence rates for injuries. The ecologic study is a hypothesis generating study. Usually using group-level data, it examines if two factors are correlated with each other.
Population-based
cases with denominator
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10. Case series represents an observational study that reports on data from a subject group without a comparison population.
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11. Case series also need methodology
Clear study objective/question
Well-defined study protocol
Explicit inclusion and exclusion criteria for study participants
Specified time interval for patient recruitment
Consecutive patient enrollment
Clinically relevant outcomes
Prospective outcome data collection
High follow-up rate
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12. Natural history effect
Selection bias
Placebo effect, 
Hawthorne effect:  tendency of some people to work harder and perform better when they are participants in an experiment
Rosenthal effect: the greater the expectation placed upon people, the better they perform. 
Natural history effect
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15. Cross-Sectional Study
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16. Cross-sectional studies
An “observational” design that surveys exposures and disease status at a single point in time (a cross-section of the population)
Cross section al studies are some of the first studies completed because of ease and low cost
time
Study only exists at this point in time
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17. Cross-sectional Design
factor present
No Disease
factor absent
Study
population
factor present
Disease
factor absent
Cross-sectional studies examine a point in time
time
Study only exists at this point in time
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18. Cross-sectional Studies
Often used to study conditions that are relatively frequent with long duration of expression (nonfatal, chronic conditions)
It measures prevalence, not incidence of disease
Example: community surveys
Not suitable for studying rare or highly fatal diseases or a disease with short duration of expression
Cross-sectional studies involve point prevalence, not incidence. For very infrequent diseases they are of limited utility
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19. Cross-sectional studies
Disadvantages
Weakest observational design, (it measures prevalence, not incidence of disease).
Prevalent cases are survivors
The temporal sequence of exposure and effect may be difficult or impossible to determine
Usually don’t know when disease occurred
Rare events a problem.
Quickly emerging diseases a problem
Cross-sectional study
From Wikipedia, the free encyclopedia
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20. SURVEYS Prevalence and incidence are obtained from surveys
The denominator i.e. the population at risk should be clearly
defined.
Cross sectional survey
a one time measurement conducted on a sample derived from a population
Prevalence = No. of persons with disease
Population at risk
Longitudinal Survey
A group of subjects under surveillance over a period of time.
Incidence rate = Number of new cases occurring over the period
Population at risk X time of observation
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21. cross-sectional studies
The exposure and disease status are examined for a sample from a defined population at the same time point.
The prevalence as well as
the OR can be determined.
OR=
No of diseased exposed/no of diseased non exposed
No exp.control /non exposed control
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22. Cross-Sectional Study
Population -
- Risk Factor +
- Risk Factor - +
+ Risk Factor
+ Risk Factor
Present
Steps in Cross-Sectional Study
1.     Select a sample from the population
2.     Simultaneously measure predictor and outcome variables
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24. Case-Control Study Steps in Case Control Study Population with Disease
Risk Factor
Population with Disease - + +
Population without Disease - + -
Past
Present
Steps in Case Control Study
1.   Select a sample of patients who already have the disease (Cases)
2.   Select a sample of patients at risk but do not have the disease (Controls)
3. Measure predictor variables
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25. Case-Control Studies
an “observational” design comparing exposures in disease cases vs. healthy controls from same population
exposure data collected retrospectively
most feasible design where disease outcomes are rare
Case-control studies in epidemiology are the most used type of study design
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26. Case Control Studies
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27. Case Control Studies
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28. Case-Control Design Study begins here factor present Cases (disease)
factor absent
Study
population
factor present
Controls
(no disease)
factor absent
Case-Control Design
present
past
time
Study begins here
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29. Case-Control Study Strengths Limitations
Less expensive and time consuming
Efficient for studying rare diseases
Limitations
Inappropriate when disease outcome for a specific
exposure is not known at start of study
Exposure measurements taken after disease occurrence
Disease status can influence selection of subjects
Case control studies provide low cost answers to health questions.
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30. case-control studies
Persons suffering from the studied disease are compared with controls who do not have the disease.
The odds ratio (OR) is calculated as a comparative effect measure.
= OR=
No of diseased exposed/no of diseased non exposed
No exp.control /non exposed control
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31. Cohort Study - Steps in Cohort Study Design: - Risk Factor
Population
Disease + -
- Risk Factor
+ Risk Factor
Present
Future
Steps in Cohort Study Design:
1.     Select a sample from the population
2.     Measure predictor variables
3.     Follow-up the cohort
4.     Measure outcome variables

32. Epidemiologic Study Designs
Cohort Studies
an “observational” design comparing individuals with a known risk factor or exposure with others without the risk factor or exposure
looking for a difference in the risk (incidence) of a disease over time
best observational design
data usually collected prospectively (some retrospective)
The cohort studies is the best for observational studies as the environmental event can be assessed before any disease outcome
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33. Cohort Design Study begins here disease Factor present no disease
population
free of
disease
disease
Factor
absent
no disease
Cohort Design
present
future
A cohort studies follows a cohort of individuals who do not have disease, and then identified over time those individuals who have an outcome
time
Study begins here
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34. Prospective Cohort study
Exposed
Outcome
Measure exposure
and confounder
variables
Non-exposed
Outcome
Baseline
Case-control studies are perhaps the most frequent form of analytic study design. These designs are very good for events that are rare in occurrence..
Still, there are some situations where cohort study designs would be appropriate in the field. The classic design in a cohort study is shown here. The study begins by assessing baseline levels of the exposure and other variables. Study subjects are then followed on a regular basis to identify the outcome. The frequency of outcomes are tested between persons who had exposure to the possible risk factor at baseline and persons with no exposure.
time
Study begins here
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35. Retrospective Cohort study
Exposed
Outcome
Measure exposure
and confounder
variables
Non-exposed
Outcome
Baseline
An alternative form of the cohort study is something termed the retrospective cohort study. Other researchers may also call this a historical prospective study. This design is nearly identical to the prospective cohort study. The sequence of baseline exposure determination and longitudinal follow-up for outcomes is similar. The difference lies in the time in which the study begins. In this retrospective design, the researcher constructs the cohort study by looking back in time and placing data in the appropriate order and sequence. These studies are possible to do with large medical databases, such as the membership files of the Health Maintenance Organizations, or the medical files in the Scandinavian countries.
time
the investigator collects data from past records and does not follow patients up as is the case with a prospective study. However, the starting point of this study is the same as for all cohort studies
Study begins here
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36. Cohort Study Strengths Limitations
Exposure status determined before disease detection
Subjects selected before disease detection
Can study several outcomes for each exposure
Limitations
Expensive and time-consuming
Inefficient for rare diseases or diseases with long latency
Loss to follow-up
-- Exp. Measured before disease - so no temporal ambiguity
-- Exposure measured before disease - so disease cannot influence the amount of error with which exposure status is measured
-- Subject selection before disease, disease status does not influence of subjects
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37. Cohort studies
Persons exposed to specific risk factors are compared with persons not exposed to these factors.
The occurrence of diseases or deaths in these two groups is observed prospectively.
incidence rate and mortality rate
Relative risk (RR) or hazard ratio (HR) Standardized incidence ratios (SIR) or standardized mortality ratios (SMR) are used for comparison with the general population.
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38. RR= -------------------------------------------
Cohort studies
No: disease in exposed / Total no: exposed
RR=
No: disease in non exp /Total no: of non exposed
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39. ECOLOGICAL STUDY TIME Direction of injury Population ED+ ED- E D+ E D-
Not Exposed
Exposed
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40. Broad street –London
studies of risk-modifying factors on health or other outcomes based on populations defined either geographically or temporally. Both risk-modifying factors and outcomes are averaged for the populations in each geographical or temporal unit and then compared using standard statistical methods.
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41. Individual exposure and disease relationship cannot be assessed
 Ecological studies
Measures combined occurrence of risk factors and disease in a population
Individual exposure and disease relationship cannot be assessed
Eg: Occupational and industrial exposure to toxins, Environmental risk
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42. Epidemiologic Study Designs
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43. Descriptive Study Design
To determine the frequency & Burden of the Disease
To generate Hypotheses
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44. Evidence Pyramid
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45. Are you going to observe or experiment?
Observational – cross sectional, case-control studies, cohort studies
identify participants
observe and record characteristics
look for associations
Experimental – before and after, comparative trials (controlled or randomised trials)
place in common context
intervene
observe/evaluate effects of intervention
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46. So…….. To identify the risk factors: Case-Control Study Design
To confirm the risk factors:
Cohort Study Design
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47. Intervention Study Essential Feature:
Intervention Group Vs Control Group
Comparison
Prove the Causation/ Effect
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48. Intervention /Experimental Studies
In an experiment, we are interested in the consequences of some treatment on some outcome.
The subjects in the study who actually receive the treatment of interest are called the treatment group.
The subjects in the study who receive no treatment or a different treatment are called the comparison group.
Experimental Studies
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49. Randomized Controlled Trials
Population
Defined
Randomization
Treatment
Group
Improve
Do Not Improve
Therapy
Standard
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50. Experimental Design time Study begins here (baseline point) outcome
RANDOMIZATION
Intervention
no outcome
Study
population
outcome
Control
no outcome
Experimental Design
baseline
future
Experimental and observational studies
A common goal for a statistical research project is to investigate causality, and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response. There are two major types of causal statistical studies: experimental studies and observational studies. In both types of studies, the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies in how the study is actually conducted. Each can be very effective. An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements. In contrast, an observational study does not involve experimental manipulation. Instead, data are gathered and correlations between predictors and response are investigated.
From Wikipedia, the free encyclopedia
time
Study begins here (baseline point)
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51. Epidemiologic Study Designs
Randomized Controlled Trials (RCTs)
the “gold standard” of research designs
provides most convincing evidence of relationship between exposure and effect
trials of hormone replacement therapy in menopausal women found no protection for heart disease, contradicting findings of prior observational studies
It is not unexpected to find that observational studies find different results than for clinical trials. For example there have been 100s of observational studies demonstrating that hormone replacement was protective for women. However, when this was put to a clinical trail, the surprising result was that hormone replacement was not protective
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52. Randomized Controlled Trials
Disadvantages
Very expensive
Not appropriate to answer certain types of questions
it may be unethical, for example, to assign persons to certain treatment or comparison groups
Understanding controlled trials: Why are randomised controlled trials important? By Bonnie Sibbald and Martin Roland
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53. Secondary Analysis Systematic Review Meta-Analysis
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54. Meta-Analysis
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55. Study Designs Descriptive Analytic Case report Cohort study RCT
Case series
Case-Control
study
Study Designs
Descriptive
Epidemiology/survey
Case-Crossover
study
Qualitative study
Epidemiologic studies may be descriptive in nature (describing the frequency or characteristics of events) or analytic (testing relationships between common traits and outcomes). Differing forms of descriptive studies exist. These designs are outlined in the next slide.
Analytic studies include experimental designs (the randomized controlled trial) and observational designs (case-control studies, cohort studies, etc.). The case-crossover study design has received a lot of attention in the past few years.
Cross-sectional
study
Before-After
study
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Ecologic study

56. Epidemiological Study Designs
From
Doesn’t include before and after studies
descriptive studies
case report, case series, qualitative study, cross sectional survey
show what’s happening in a population and in subgroups
analytic studies
examine effect of intervention (I)/exposure (E) on outcome (O)
compare frequency of outcomes in a comparison (C) group with frequency in intervention or exposed group to quantify effect
may be experimental or observational
Centre for Evidence Based Medicine, Oxford, UK cebm.net
Prospective
A prospective study watches for outcomes, such as the development of a disease, during the study period and relates this to other factors such as suspected risk or protection factor(s). The study usually involves taking a cohort of subjects and watching them over a long period. The outcome of interest should be common; otherwise, the number of outcomes observed will be too small to be statistically meaningful (indistinguishable from those that may have arisen by chance). All efforts should be made to avoid sources of bias such as the loss of individuals to follow up during the study. Prospective studies usually have fewer potential sources of bias and confounding than retrospective studies.
Retrospective
A retrospective study looks backwards and examines exposures to suspected risk or protection factors in relation to an outcome that is established at the start of the study. Many valuable case-control studies, such as Lane and Claypon's 1926 investigation of risk factors for breast cancer, were retrospective investigations. Most sources of error due to confounding and bias are more common in retrospective studies than in prospective studies. For this reason, retrospective investigations are often criticised. If the outcome of interest is uncommon, however, the size of prospective investigation required to estimate relative risk is often too large to be feasible. In retrospective studies the odds ratio provides an estimate of relative risk. You should take special care to avoid sources of bias and confounding in retrospective studies.  
Doesn’’t include basic science studies: often uncontrolled with convenience samples – acceptance of evidence depends on replication.
Basic science theories and schemata can be used to
provide a mechanistic explanation;
(ii) yield predictions and
(iii) provide a `blueprint' for designing research (to design tests and, if necessary, refute mechanistic hypotheses (La Caze A. The role of basic science in EBM.
Descriptive studies answer “what’s happening?”
Analytic observational studies answer “why or how is it happening?”
Analytic experimental studies answer “can it work?”

57. Increasing Knowledge of
Develop
hypothesis
Descriptive Studies
Investigate it’s
relationship to
outcomes
Case-control Studies
Increasing Knowledge of
Disease/Exposure
Define it’s meaning
with exposures
To further illustrate, if one seeks to identify the etiologic factors (e.g. causal factors) behind an outcome (e.g. an MI), then each step in the epidemiologic framework provides new and important information.
Descriptive studies are useful for identifying hypotheses to test in analytic studies. Case-control studies are then usually applied to evaluate if the hypothesized factor is related to the outcome of interest. Subsequently, cohort or longitudinal studies are applied to further define the importance of exposure to the causal agent for the development of the outcome.
Cohort Studies
Test link
experimentally
Clinical trials
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58. Research Designs….. Descriptive Analytic To: Describe an
experience,
programs, treatment,
unusual observation
Analytic
Examine etiology, efficacy
Experimental
Evaluate the efficacy of
a therapeutic , or other
interventions
Observational
Association of cause and effect
Comparison between 2 treatments
Examples:
1) Case Reports or series
Side effect of a drug
Cluster of cases
2) Population
Prevalence or incidence
of disease in populations
3) Ecological study
Examples:
Clinical Trial
Community education
Examples:
1) Cross-sectional
2) Case-control
3) Cohort
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59. Hierarchy of Epidemiologic Study Design
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60. Chance/Confounder/bias
While the results of an epidemiological study may reflect the true effect of an exposure(s) on the development of the outcome under investigation, it should always be considered that the findings may in fact be due to an alternative explanation.
Observational studies are particularly susceptible to the effects of chance, bias and confounding, and these need to be considered at both the design and analysis stage of an epidemiological study so that their effects can be minimized.
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61. Confounding
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62. Bias
Information bias ---differences in the way data on exposure or outcome are obtained 
Observer bias --differences in the way information is collected
Recall bias---in retrospective studies
Selection bias-- differences in the characteristics between those who are selected in both groups
Bias results from systematic errors in the research methodology
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63. Important epidemiological frequency measures and comparative measures;
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64. Thank You
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