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Smart designs Case control studies FETP India. Competency to be gained from this lecture Design a case control study.

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Presentation on theme: "Smart designs Case control studies FETP India. Competency to be gained from this lecture Design a case control study."— Presentation transcript:

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 CasesControlsTotal Exposedab- Non-exposedcd- Totala+cb+d- Presentation of the data of a case control study in a 2 x 2 table 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 One year Study subject developing the illness Study subject censored Study subject followed up Observation Legend

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

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 Characteristics of the two cases and three controls 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 Population base

16 Case ControlTotal Exposeda.f 1 b.f 2 N/A Non exposedc.f 1 d.f 2 N/A TotalC 1.f 1 C 0.f 2 N/A Impossibility to calculate a relative risk in a case control study Cases are sampled from all cases (sampling fraction: f 1 ) Controls are sampled from all controls (sampling fraction: f 2 ) f 1 and f 2 are unknown, risks cannot be calculated Population base

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

18 i llNon-illTotal Exposed123 Non-exposed145 Total268 Presentation of the data of the analytical cohort study in a 2 x 2 table 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 unexposed f 1 = f 0 = Population base

20 Case ControlTotal Exposed1x1=12x0.5=1N/A Non exposed1x1=14x0.5=2N/A Total2x1=26x0.5=3N/A Calculation of the odds ratio in a case control study 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 Exposure Outcomes (e.g., Disease) Time Referent exposure period (Time during which exposure occurs) Time at risk for exposure effects 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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