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Following the roman soldiers Cohort studies FETP India.

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Presentation on theme: "Following the roman soldiers Cohort studies FETP India."— Presentation transcript:

1 Following the roman soldiers Cohort studies FETP India

2 Competency to be gained from this lecture Design a cohort study

3 Key areas Study population Prospective / retrospective cohorts Measurement of outcome Measurement of exposure Experimental design

4 A cohort of Roman soldiers

5 Elements that may define a study population for a cohort Residence Demographic characteristics Cultural background Socio-economic group Employment Sharing a common experience or condition Population

6 Elements defining the study population become the recruitment criteria Inclusion criteria Exclusion criteria  Same as inclusion criteria  Just considered in a mirror Population

7 Fixed cohorts Study participants are included from the beginning to the end of the cohort Simple Common Population

8 Dynamic cohorts Study participants can come in and out of the cohort More complex Less common Population

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

10 IllNon-illTotal Exposedaba+b Non-exposedcdc+d Totala+cb+da+b+c+d Presentation of the data of an analytical study in a 2 x 2 table Population

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 Population

12 The unexposed group in a cohort study Unexposed subjects must belong to the same population Unexposed subjects must have the same theoretical risk to develop the disease if they are exposed to the risk factor Population

13 Prospective cohorts studies Recruitment of study participants at the beginning of the observation period Initial observation  Baseline collection of information about exposure  Verification of “non-ill” status Follow-up over time to identify persons who develop an illness Key issue:  Not missing persons who develop the illness  Loss to follow-up Prospective and retrospective cohorts

14 Retrospective cohorts studies Recruitment of study participants at the end of the observation period Retrospective assessment  Collection of information about exposure  Collection of information about illness Key issue:  Identify ill subjects appropriately-retrospectively Prospective and retrospective cohorts

15 Collecting data about outcome in cohort studies Baseline and end of the observation period  Cumulated incidence  Attack rate Regular intervals  Incidence rate  Incidence density rate Outcome

16 Calculation of incidence density: Status of study participants at a given point in time At risk  The subject is being observed Censored  The subject is lost to follow-up  The subject had not developed the illness when he was lost to follow-up Illness  The subject has developed the illness (He is not followed-up after) Outcome

17 Study participants observed over time in a cohort study One yearDevelopment of illnessCensored Blue lines denote an observation Each yellow line is a person followed Outcome

18 Calculation of incidence density in a cohort study One yearDevelopment of illnessCensored Person-year at risk: 41 Illness: 2 Incidence density: 4.9 / person -year Outcome

19 Calculation of cumulated incidence in a cohort study Development of illness ? ? ? ? Person included: 8 Lost to follow-up: 4 Illness: 1 Incidence: 25% Duration of the study Outcome

20 Outcome assessment in cohort studies: Summary Single assessment Easier Does not measure observation time Subject to bias because of loss to follow-up Does not allow calculation of incidence density Regular assessment More difficult Measures observation time Less subject to bias because of loss to follow-up Allows calculation of incidence density Outcome

21 IllNon-illTotal ExposedabL 1 Non-exposedcd L 0 Totala+cb+d L 1 + L 0 Calculation of the risk for the whole population in a cohort study R = (a+c)/(L 1 + L 0 ) Outcome

22 EventsPerson-timeRate ExposedaPT 1 Rate 1 Non-exposedcPT 0 Rate 0 Totala+cPTRate Calculation of the rate for the whole population in a cohort study Rate = a+c/PT Outcome

23 Examining one or multiple exposures in cohort studies One exposure Multiple exposures  Various exposed and unexposed subgroups examined differently in the analysis Exposure

24 Collecting good data on exposure Objectively  Reproducibility of exposure measurement Accurately  Information reflecting as closely as possible the effect of exposure Precisely  Total quality management in exposure measurement Exposure

25 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

26 Basic relation between exposure, time and outcome Exposure Outcomes (e.g., Disease) Time Referent exposure period (Time during which exposure occurs) Time at risk for exposure effects Understand that dynamic when designing the cohort Exposure

27 Considering how the exposure played over time Duration of exposure  Brief (e.g., exposure to an atomic bomb)  Chronic (e.g., smoking) Induction (“incubation”) period  Short (e.g., infectious diseases)  Long (e.g., chronic diseases) Exposure

28 Collecting exposure data over time in cohort studies Examining average exposure  One measurement  Regular measurements Examining changes of exposure over time  Regular measurements of exposures  Sub analyses examining the association between exposure and outcome in specific windows of time Exposure

29 Experimental component in a cohort study Intervention at the individual level  Clinical trial e.g., South India BCG trial Intervention at the population level  Community intervention study e.g., Mwanza trial, Tanzania Experimental design

30 Take-home messages Cohorts bring together persons sharing a common experience to follow them over time The logistics of cohorts may be prospective or retrospective Cohorts allow person-time denominators Cohorts allow precise assessment of exposure over time Cohorts allow experimental designs


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