Transcript Getting to the essential

Following the roman soldiers
Cohort studies
FETP India
Competency to be gained
from this lecture
Design a cohort study
Key areas
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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
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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
Presentation of the data of an analytical
study in a 2 x 2 table
Ill
Non-ill
Total
Exposed
a
b
a+b
Non-exposed
c
d
c+d
a+c
b+d
a+b+c+d
Total
Population
Presentation of the data of an analytical
cohort study in a 2 x 2 table
Ill
Non-ill
Total
Exposed
a
b
a+b
Non-exposed
c
d
c+d
a+c
b+d
a+b+c+d
Total
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
Blue lines denote an
observation
Study participants observed over time in
a cohort study
One year
Development of illness
Censored
Each yellow line is a
person followed
Outcome
Calculation of incidence density in a
cohort study
Person-year at risk:
41
Illness:
2
Incidence density:
4.9 / person -year
One year
Development of illness
Censored
Outcome
Calculation of cumulated incidence
in a cohort study
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Duration of the study
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Person included:
8
Lost to follow-up:
4
Illness:
1
Incidence:
25%
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Development of illness
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
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Regular assessment
More difficult
Measures observation
time
Less subject to bias
because of loss to
follow-up
Allows calculation of
incidence density
Outcome
Calculation of the risk for the whole
population in a cohort study
Ill
Non-ill
Total
Exposed
a
b
L1
Non-exposed
c
d
L0
a+c
b+d
L1 + L0
Total
R = (a+c)/(L1 + L0)
Outcome
Calculation of the rate for the whole
population in a cohort study
Events
Person-time
Rate
Exposed
a
PT1
Rate1
Non-exposed
c
PT0
Rate0
a+c
PT
Rate
Total
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
Understand that dynamic when designing the cohort
Referent
exposure
period
(Time during which
exposure occurs)
Time at risk for
exposure effects
Time
Exposure
Outcomes
(e.g., Disease)
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