Following the roman soldiers
Cohort studies
FETP India
Competency to be gained from this lecture
Design a cohort study
Key areas
• Study population• Prospective / retrospective cohorts• Measurement of outcome • Measurement of exposure• Experimental design
A cohort of Roman soldiers
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
Elements defining the study population become the recruitment
criteria • Inclusion criteria• Exclusion criteria
Same as inclusion criteria Just considered in a mirror
Population
Fixed cohorts
• Study participants are included from the beginning to the end of the cohort
• Simple• Common
Population
Dynamic cohorts
• Study participants can come in and out of the cohort
• More complex• Less common
Population
Potential objectives of a cohort study
• Descriptive Estimate incidence
• Analytic Compare the incidence of a disease in
various subgroups:• Exposed • Unexposed
Population
Ill Non-ill Total
Exposed a b a+b
Non-exposed c d c+d
Total a+c b+d a+b+c+d
Presentation of the data of an analytical study in a 2 x 2 table
Population
Ill Non-ill Total
Exposed a b a+b
Non-exposed c d c+d
Total a+c b+d a+b+c+d
Presentation of the data of an analytical cohort study in a 2 x 2
table
Population
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
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
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
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
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
Study participants observed over time in a cohort study
One year Development of illness Censored
Blue lines denote an observation
Each yellow line is a person followed
Outcome
Calculation of incidence density in a cohort study
One year Development of illness Censored
Person-year at risk:41Illness:2Incidence density:4.9 / person -year
Outcome
Calculation of cumulated incidence in a cohort study
Development of illness
?
?
?
?
Person included:8Lost to follow-up:4Illness:1Incidence:25%
Duration of the study
Outcome
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
Ill Non-ill Total
Exposed a b L1
Non-exposed c d L0
Total a+c b+d L1 + L0
Calculation of the risk for the whole population in a cohort study
R = (a+c)/(L1 + L0)
Outcome
Events Person-time Rate
Exposed a PT1 Rate1
Non-exposed c PT0 Rate0
Total a+c PT Rate
Calculation of the rate for the whole population in a cohort study
Rate = a+c/PT
Outcome
Examining one or multiple exposures
in cohort studies• One exposure • Multiple exposures
Various exposed and unexposed subgroups examined differently in the analysis
Exposure
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
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
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
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
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
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
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