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Smart designs

Smart designs . Case control studies FETP India. Competency to be gained from this lecture. Design a case control study . Key areas. Analytical case control studies Population base of case control studies Case and control recruitment Measurement of exposure. Case control study.

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Smart designs

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  1. Smart designs Case control studies FETP India

  2. Competency to be gained from this lecture Design a case control study

  3. Key areas • Analytical case control studies • Population base of case control studies • Case and control recruitment • Measurement of exposure

  4. Case control study • Recruitment of: • Case-patients affected with a disease • Unaffected control-subjects • Comparison of exposure status • Observation of the in past presence of one or more potential risk factors Analytical case control studies

  5. Objective of a case control study • Case control studies are analytical in nature • Case control studies compare in terms of exposure status : • Case-patients affected by a disease • Unaffected control-subjects Analytical case control studies

  6. Exploratory case control studies • Risk factors for a disease are unknown • The case control study explores potential risk factors for further investigation • Risk of multiple comparisons! • If the p value is set at 0.05, every 20 tables will generate a “significant” association Analytical case control studies

  7. Case control studies designed to test a limited number of hypotheses • Risk factors for a disease are better framed • Established risk factors • Unclear risk factors • Possible risk factors • A limited number of hypotheses are examined • Unclear risk factors • Possible risk factors • Ideal situation from a methodological point of view Analytical case control studies

  8. 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 Analytical case control studies

  9. Presentation of the data of a case control study in a 2 x 2 table Cases Controls Total Exposed a b - Non-exposed c d - Total a+c b+d - Analytical case control studies

  10. All case control studies come from a theoretical cohort • Cohorts follow exposed and unexposed subjects for the development of illness • Cases and controls can be thought of as extracted from a theoretical cohort in which they are “nested” • Thinking of case control studies as nested in a theoretical cohort help investigators in designing them appropriately Population base

  11. Representation of a cohort study Legend One year Study subject followed up Study subject censored Study subject developing the illness Observation

  12. Nesting a case control study in a cohort for a disease with a one year referent exposure period Legend Case Control

  13. Case control study with two cases and three controls Population base

  14. Time comparability of cases and controls • Cases have an onset date • Controls have no onset dates • The need to identify a referent exposure period is less obvious • Controls must nevertheless be observed over a referent exposure period that needs to be clarified Population base

  15. Come from the same population Can be exposed the same way Can develop the disease the same way Could have been identified as cases the same way Have identical exposure windows Characteristics of the two cases and three controls Population base

  16. Impossibility to calculate a relative risk in a case control study Case Control Total Exposed a.f1 b.f2 N/A Non exposed c.f1 d.f2 N/A Total C1.f1 C0.f2 N/A Cases are sampled from all cases (sampling fraction: f1) Controls are sampled from all controls (sampling fraction: f2) f1 and f2 are unknown, risks cannot be calculated Population base

  17. Unexposed and exposed study subjects in the cohort Legend Subject exposed Subject unexposeda= ? b= ? c= ? d= ?

  18. Presentation of the data of the analytical cohort study in a 2 x 2 table ill Non-ill Total Exposed 1 2 3 Non-exposed 1 4 5 Total 2 6 8 Relative risk = (1/3) / (1/5) = 33% / 20% = 1.7 Population base

  19. Sampling fraction for cases and controls in the example Legend Subject exposed Subject unexposedf1 = f0 = Population base

  20. Calculation of the odds ratio in a case control study Case Control Total Exposed 1x1=1 2x0.5=1 N/A Non exposed 1x1=1 4x0.5=2 N/A Total 2x1=2 6x0.5=3 N/A Odds ratio = (1x2) / (1x1) = 50 / 100 = 2 Higher than the relative risk? Why? The disease is not rare! Attack rate: 25% Population base

  21. Prospective case control studies • Identification of cases prospectively • Surveillance • Recruitment in a health care facility • Recruitment with health care providers • Recruitment of controls prospectively • Investigators look at exposure retrospectively Population base

  22. Retrospective case control studies • Identification of cases retrospectively • Surveillance data • Health care facility registers • Case records • Recruitment of controls retrospectively • Investigators look at exposure retrospectively Population base

  23. Specific case control study designs • Truly “nested” case control studies • Set of cases and controls identified prospectively from a cohort to obtain intermediate results • Case-cohort studies • Cases obtained from surveillance data • Controls selected from a cohort study Population base

  24. Case definitions in case control studies • Person • Signs and symptoms • Biological criteria • Demographic characteristics • Time • Time of onset • Place • Place of residence Cases and controls

  25. Control recruitment strategies in case control studies • Population based • Sampling of the general population • Random digit sampling • Health care facility based • Hospital based • Patients with other diseases • Case-based (Beware of matching) • Friends • Neighbourhood Cases and controls

  26. Defining the recruitment strategy in case control studies • Person • Signs and symptoms (or absence of…) • Biological criteria(e.g., susceptibility) • Demographic characteristics • Time • Referent exposure period • Place • Place of residence Cases and controls

  27. Collecting good data on exposure • Objectively • Reproducibility of exposure measurement • Accurately • Information reflecting as closely as possible the effect of exposure • Precisely • Quality management in exposure measurement Exposure

  28. Measuring the dose of exposure • Dichotomous exposure measurement • Exposed / unexposed • Measurement of the dose of exposure • Accurate measurement of the dose of exposure(e.g., Cumulated number of cigarettes smoked) • Exposure categories • Dose / response effect Exposure

  29. Understanding the basic relation between exposure, time and outcome when designing a case control study Referent exposure period(Time during which exposure occurs) Time at risk for exposure effects Time Outcomes(e.g., Disease) Exposure Exposure

  30. Take home messages • Case control studies refine or test hypotheses • Case control studies come from cohorts • Case definition and control recruitment are the keystone of the design • Information on exposure is collected retrospectively

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