Epidemiologic Study Designs

Epidemiologic Study DesignsCase-Control studyCross-sectional study

Hierarchy of Epidemiological Study Designs

Hierarchy of Epidemiological Study DesignsCross-sectional studiesCase-Control studies

Strength of evidence Strongest

Weakest Meta-analysis of RCTRandomized Controlled TrialsCommunity Intervention DesignQuasi Experimental designMeta-analysis of observational st.Cohort DesignCross-sectional designCase-Control designCase seriesCase report

Case-Control Studies

SynonymsRetrospective studyCase reference study Case comparison studyCase history study

DefinitionAn epidemiological approach in which the researchers start by picking up cases (with disease) and controls (without the disease) and finds out the presence of particular exposure which he/she thinks is a risk factor and compares the two groups as regards the presence of exposure

Design of a Case-control study

AdvantagesInexpensive, requires only a few subjects gives quick results Well suited for diseases which have a long latent period (e.g. cancers, AIDS, MI, CVA etc.)Well suited for an outcome which is rare Well suited for conditions in which medical care is usually soughtHelps in examining multiple etiologic factors - once we have the cases of the disease, we can take history of all the factors that we feel may be risk factorsReasonably good for diseases that have a relatively rapid onset and are usually hospitalized (e.g. most of the acute infections; injuries etc.)

DisadvantagesNot a good method for studying rare exposuresDoes not give any idea of incidence or prevalence; it only gives us a measure of Odds Ratio (OR)Particularly prone to various forms of selection and information biases, particularly survivorship Bias, Recall Bias and observers bias.Temporal Relationship is usually only a matter of conjecture but not a proof

Designing and Conducting a Case-Control study 1. Specify the total population and actual (Study) population2. Specify the major study variables and their scales of measurement3. Calculate the sample size4. Specify the selection criteria of cases 5. Specify the selection procedure of controls6. Specify the procedures of measurement and specially take care to ensure validity and reliability7. Do a pilot study8. Conduct the study9. Analysis of data

1: Specify total population and actual (Study) populationGives us an complete idea of study populationCases and controls should represent the same population

2: Specify the major study variables & their scales of measurementOutcome Variable: Dichotomous scale i.e disease present or absentExposure Variable: Particular cause associated with diseaseScales of measurement of exposure variable: DichotomousPotential confounding Factors: Through literature and expert discussion

3: Calculate the Sample Sizewhere, n = minimum sample size for each group; Z 1-/2 = value of alpha error; z 1-= value of beta error; For the usual situation when alpha error = 0.05 two tailed, the value is 1.96 and for beta error = 0.20, it is 0.84; P0= Proportion of those without the exposure who are likely to develop the outcome (in a prospective study) or Proportion of those without the outcome who are likely to have the exposureZ 1-/2 + z 1-)2 * p * q n = ----------------------------- (p1 - p0)2

4: Specify the selection criteria of cases Diagnostic Criteria: Clear-cut (Preferably by expert bodies) State inclusion and exclusion criteria: Inclusion criteria had a reasonable chance of exposureExclusion criteria no exposureSource of cases: Hospitals, OPDs, General Practitioners, communityIncident or Prevalent cases: Newly occurring or already having diseaseIncident cases are betterMethods of Sampling: Systematic random samplingSimple random sampling

5: Specify the selection procedure of controlsSource : hospital based or population based Advantages and DisadvantagesExclusion / Inclusion Criteria: same as for casesNumber of controls per case: At least 1 control per case Number of Control groups: Usually one group Two groups can improve validity like hospital and communityMatching: list out all confounding factors, as well as universal confounding factor age, sex etc.

6: Specify the procedures of measurement Selection and information biasesSpecially take care to ensure validity and reliabilityQuestionnaire

7: Do a Pilot StudyPre-testing of part of a sample In order to improve the actual studys quality and efficiency Can reveal deficiencies in the design of a proposed study Bias can be avoided

8: Conduct the StudyValidityAnemia: Reliability Check for variations due toObserverSubjectsInstruments and techniques

9: Analysis of DataCalculateOdds Ratio with 95% Confidence IntervalTesting of HypothesisUse Chi-square test or t test depending upon variableControl confounding variable through stratified analysis with Mantel-Hanszel technique or Multiple logistic RegressionPair-matched study use McNemars Chi-square, OR, 95% CI of OR.

Odds ratioA ratio that measures the odds of exposure for cases compared to controlsOdds of exposure = number exposed number unexposedOR Numerator: Odds of exposure for casesOR Denominator: Odds of exposure for controls

400200Total22488Non-smoker176112SmokerExposure StatusNo CHD(Controls)CHD cases(Cases)Disease StatusCalculating the Odds RatioOdds Ratio==ADBC112 x 224176 x 88=1.62

Exposure increases disease risk (Risk factor)Particular exposure is not a risk factorExposure reduces disease risk(Protective factor)Exposure as a risk factor for the disease?Odds of exposure for cases are greater than the odds of exposure for controlsOdds of exposure are equal among cases and controlsOdds of exposure for cases are less than the odds of exposure for controlsOdds comparison between cases and controlsOR>1OR=1OR

Interpreting the Odds RatioorThe odds of exposure for cases are 1.62 times the odds of exposure for controls.

Interpreting the Odds RatioThose with CHD are 62% more likely to be smokers than those without CHD Those with CHD are 1.62 times more likely to be smokers than those without CHDor

Classical Case-Control studies

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