1. A question of perspective Types of epidemiological studies FETP India

2. Competency to be gained from this lecture Choose a design adapted to the objective of a study

3. Key areas Cohort studies Case control studies Cross-sectional studies

4. Observational and interventional studies Observational studies  Descriptive (e.g., What is the incidence of measles?)  Analytic (e.g., What are the risk factors for leishmaniasis?) Interventional studies  Descriptive (e.g., “demonstration” studies / projects)  Analytic (e.g., What is the effect of this intervention?)

5. Basic relation between exposure, time and outcome Exposure Outcomes (e.g., Disease) Time Referent exposure period

6. General considerations about analytical studies All risk factors studies should be conducted with incident cases Prevalent cases expose to difficulties:  Selective survival  Impossibility to determine when the disease occurred  Impossibility to determine when the exposure occurred  Lack of information about the exposure - disease sequence prevents causal inference

7. Key areas Cohort studies Case control studies Cross-sectional studies Cohorts

8. Cohort study Recruitment of study participants at risk  Population  Population sample Follow-up over time Observation for the occurrence of one or more outcomes Cohorts

9. Potential objectives of a cohort study Descriptive  Estimate incidence Analytic  Compare the incidence of a disease in various subgroups Exposed Unexposed Cohorts

10. Elements defining an analytical cohort study Study participants  At risk for the outcome  Selected on the basis of their exposure status Logic  Prospective follow-up to measure incidence Logistic  Prospective  Retrospective Cohorts

11. IllNon-illTotal Exposedaba+b Non-exposedcdc+d Totala+cb+da+b+c+d Presentation of the data of an analytical cohort study in a 2 x 2 table Cohorts Known at the beginning of the study

12. Examples of cohort studies Retrospective cohort study to investigate an outbreak  Wedding dinner Long-term cohort to estimate the incidence of cardio-vascular diseases  Framingham Clinical trials  An example of interventional studies Cohorts

13. Key areas Cohort studies Case control studies Cross-sectional studies Case control studies

14. Case control study Recruitment of:  Case-patients affected with a disease  Unaffected control-subjects who are at risk Comparison of exposure status Observation for the presence in the past of one or more potential risk factors Case control studies

15. Objective of a case control study Analytic  Compare, in terms of exposure status: Case-patients affected by a disease Unaffected control-subjects Case control studies

16. Elements defining a case control study Study participants  Selected on the basis of their disease status Logic  Retrospective examination of potential exposures Logistic  Prospective  Retrospective Case control studies

17. CasesControlsTotal Exposedab- Non-exposedcd- Totala+cb+d- Presentation of the data of a case control study in a 2 x 2 table Case control studies Fixed at the beginning of the study

18. Examples of case control studies Case control study to investigate an outbreak  Risk factor for hepatitis E during an outbreak in a metropolitan area Case control study to investigate the risk factors for a rare disease  Creutzfeld-Jacob Case control studies

19. Key areas Cohort studies Case control studies Cross-sectional studies Cross sectional studies

20. Cross-sectional study Recruitment of study participants  Population  Population sample Observation for the presence of:  One or more outcomes  One or more exposures Cross sectional studies

21. Potential objectives of a cross-sectional study Descriptive  Estimate prevalence Analytic  Compare the prevalence of a disease in various subgroups, exposed and unexposed  Compare the prevalence of an exposure in various subgroups, affected and unaffected Cross sectional studies

22. Elements defining an analytical cross-sectional study Study participants  Selected independently from their disease or exposure status Logic  Simultaneous measurement of outcomes and potential exposures Logistic  Cross-sectional Cross sectional studies

23. IllNon-illTotal Exposedaba+b Non-exposedcdc+d Totala+cb+da+b+c+d Presentation of the data of an analytical cross-sectional study in a 2 x 2 table Cross sectional studies Known simultaneously when the study is completed

24. Limitations of causal inference in analytical cross-sectional studies Prevalent cases Exposure and outcome examined at the same time Cross-sectional studies

25. Examples of cross-sectional studies Census Population surveys Cross sectional studies

26. Compared logic and logistics of cohorts, case control and cross-sectional studies CohortsCase-control studies Cross-sectional studies Logic Prospective Retrospective Cross-sectional Logistic Prospective Retrospective Prospective Retrospective Cross-sectional

27. Comparing cohorts and case control studies (1) Case controlCohort Rare outcomesAdaptedLess adapted Rare exposuresLess adaptedAdapted Multiple exposuresYesDifficult Multiple outcomesNoYes Estimation of incidenceNoYes

28. Comparing cohorts and case control studies (2) Case controlCohort Outcome statusEasierDifficult if retrospective Exposure statusRecall biasEasier Natural history-Can be studied Use of existing dataYesYes (Retrospective) Sample sizeSmallerLarger

29. Comparing cohorts and case control studies (3) Case controlCohort CostLowerHigher Time neededShortLonger Follow-up (F/U)N/ALost to F/U LogisticsEasierMore difficult ConceptDifficultEasier EthicsEasierMore difficult

30. Take-home messages Cohort studies go from exposure to outcome(s) Case control studies go from outcome to exposure(s) Cross-sectional studies examine outcome and exposure at the same time