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Epidemiology – Cohort studies I
March 2010
Jan Wohlfahrt
Afdeling for Epidemiologisk Forskning
Statens Serum Institut
EPIDEMIOLOGY
COHORT STUDIES I
March 2009 (modified)
Søren Friis
Institut for Epidemiologisk Kræftforskning
Kræftens Bekæmpelse
”While the individual man is an insoluble puzzle, in the
aggregate he becomes a mathematical certainty. You
can, for example, never foretell what any one man will
do, but you can say with precision what an average
number will be up to”
Arthur Conan Doyle
Sherlock Holmes: The Sign of four
Ideal study of a causal effect
”The experience of exposed people is compared
with their experience when not exposed, while
everything else is held constant”
Kenneth Rothman, Modern Epidemiology, 1998
Analytic epidemiological studies
Assignment of exposure
Yes
No
Non-experimental
Non-experimental
studiesstudies
Experimental
studies
Random allocation
no
Community
intervention
trials
Sampling according
to exposure status
Sampling according
to outcome status
yes
Randomised/
intervention
trials
Cohort
studies
Case-control
studies
Cohort studies
Classical definition
”The delineation of a group of persons who are
distinguished in some specific way from the majority
of the population and observation of them for long
enough to allow any unusual morbidity or mortality
to be recognised”
Richard Doll 1964
Cohort studies
Recent definition
 Experiments
 Randomised clinical trials
 two (or multiple)-arm, cross-over
 Field trials
 intervention on single-person level
 Community intervention trials
 intervention on community level
 Non-experimental cohort studies
Udfald
+
Exposed
Censored
-
Population
at risk
+
Non-exposed
Censored
-
Past
Present
Identify study subjects and
assess exposure characteristics
Future
Follow-up
Population at risk
 Individuals at risk of developing the outcome(s) of interest
 Basis for computation of measures of diseases frequency and effect
measures
 Classified according to exposure characteristics
 At baseline
 During follow-up
 Censoring at





First outcome (typically)
Death
Migration
Upper age limit, if age restriction
Other criteria, e.g. exposure shift
Cohort
 ”Any designated group of individuals who are
followed or traced over a period of time”
 Kenneth Rothman, Modern Epidemiology, 1998
 Can be divided into closed and open populations
Closed and Open Populations
Closed population
 A population that adds no new members over time
Open/dynamic population
 A population that may gain members over time or
lose members who are still alive
 e.g. drug users within a specific observation period
Closed population
limitations
 Loss to follow-up (censoring)
 Decreasing cohort size
 Aging of cohort members
 Depletion of susceptibles
Selection of the exposed population
 General population
 Diet, Cancer & Health cohort, Danish Cancer Society
 Individuals aged 50 to 64 years, follow-up from 1994 (n  57,000)
 Occupational exposure groups
 Nurses Health Study, USA
 Nurses aged 30 to 55 years, follow-up from 1976 (n  120,000)
 Exposure
 ”Special exposure groups”
 Ex.: Workers at the Thule base, Epileptics at Dianalund, individuals
exposed to thorotrast
 Drug users
 Registers
 General Practice Research Database, UK
 Danish health and administrative registers
Selection of the comparison group
 Ideally identical to the exposed group with respect to all
other factors that may be related to the disease except
the outcome(s) under study
 ”Internal” comparison
 general population/large occupational cohort
 frequent exposure
 ”External” comparison
 General population (rates)
 Standardised incidence rate ratio (SIR)
 Standardised mortality rate ratio (SMR)
Data sources
Exposure
 Existing data
 registers
 medical records
 bio-banks
 Questionnaires
 interview
 self-administered
 Ad hoc measurements
 clinical parametes
 biological samples
Outcome
 Registers
 Clinical examination
 Information from study
subjects
 interview
 questionnaire
 Information from next-of-kin
 Mortality data
Cohort studies
Advantages
 Can examine
 multiple effects of a
single exposure
 rare exposures
 Exposures with certainty
precede outcomes (if
prospective)
 Can elucidate temporal
relationship between
exposure and outcome
 Allow study subjects to
contribute person-time to
multiple exposure categories
 Biological material can be
collected prior to outcome
 Allows direct measurement
of incidence (IR, IP) of
 If prospective, minimizes
outcomes
bias in the ascertainment of
exposure
Cohort studies
Disadvantages
 Is inefficient for the
evaluation of rare
diseases
 If prospective, can be
very expensive and time
consuming
 If prospective, cannot
provide quick answers
 If retrospective, precise
classification of exposure
and outcome may be
difficult
 If retrospective, requires  Validity of the results can be
the availability of
seriously affected by losses
adequate records for both
to follow-up
exposure and outcome
Cohort studies
Methods for reduction of costs and time
 Historical cohort studies
 Comparison with general population (rates)
 Nested case-control studies
 Register studies
Register studies in DK
Register studies in DK
Frank L. Science 2000;287: 2398-9
Register studies in DK
Cancer Registry
IDA Register
(socioeconomic
variables)
National Death Files
CPR Register
National Hospital
Register
Birth Register
Prescription
Databases
Register studies
 Registers are highly valuable data sources, BUT
 Difficulties in interpretation due to incomplete data
on competing risk factors
 Life-style factors, socioeconomic factors,
comorbidity, medical treatment
 Other potential biases
 Misclassification, non-compliance, etc.
Measures of disease frequency
Definitions
What is the case?
What is the study period?
What is the population at risk?
Measures of disease frequency, summary
 Incidence proportion (IP)
 Proportion of population that develops the outcome of interest during a
specified time
 Can be measured only in closed populations
 ”Average risk” for a population
 Incidence rate (IR)
 Number of new cases of the outcome of interest divided by the amount of
person-time in the base population
 Can be measured in both open and closed populations
 Most often restricted to include a maximum of one event per person
 Prevalence proportion (PP)
 Proportion of population that has the outcome of interest at given instant
Effect measures in cohort studies
Exposure
+ Outcome
- Outcome
+
-
a
c
b
d
a + b
a+c
b+d
N
c + d
IP+ = a/a+b
IP- = c/c+d
RR = IP+/IPAttributable risk (AR) = IP+ - IP-
Attributable proportion (AP) = AR/IP+ = (RR-1)/RR
Incidence proportion
Conditions
 All persons should be followed-up from start of study (t0)
until end of study with respect to the outcome(s) of
interest
 Problems:
 Open/dynamic population (t0?)
 Competing risks of death
 Censoring
 Is usually not directly observable, solution:
 Computation of incidence rates
Relation between rate (IR) og risk (IP)
IP = 1 - exp(-IR x t) (IR constant)
IP = 1 - exp(- IRí x tí ) (IR variable)
IR small and/or short t:
IP  IR x t
Time dimension
cases
Exposed
Non-exposed
cases
Person-time in study
Problem: Exposure status changes over time (episodical, sporadical)
Solution: Allow persons to contribute person-time to multiple exposure categories
Age
30-year-old man is
enrolled in a cohort
study of drug X in
relation to disease Y
in 1970 and followed
free of Y through
1995
35-year-old man is
enrolled in 1970 and
followed until
occurrence of Y in
1983
Contribution from the two study subjects
55
Exp. to drug X
50
Y
45
40
35
30
1970 1975 1980
1985
1990 1995
Calendar time
X
Non-X
Non-exp. to drug X
Age
PY
Disease Y
PY
Disease Y
30-34 y
0
0
5
0
35-39 y
5
0
5
0
40-44 y
10
0
0
0
45-49 y
8
1
0
0
50-54 y
0
0
5
0
”Crude”
23
1
15
0
Effect measures in cohort studies
Non-exposed
cases
Person-time in study
Incidence rate = cases / person-time
Incidens Rate Ratio (IRR) = IR+ / IR-
Yes
No
Exposed
Exposure
cases
Cases Person-time
A
PY
C
PY
A = Exposed cases
C = Non-exposed cases
Effect measures in cohort studies
Exposure
Outcome
Person-time
+
-
a
c
PY+
a+c
N
PY-
IR+ = a/PY+
IR- = c/PYIncidence rate ratio (IRR) = IR+/IRIncidence rate difference = IRD (≈AR) = IR+ - IRAP = IRD/IR+ = (IR+-IR-)/IR+ = (IRR-1)/IRR
”Relative risk” vs. incidence rate ratio
IP IR  t IR


IP IR  t IR
1
1
1
2
2
2
Given
IP  IR x t (IR small)
”Relative risk” is equivalent with the ratio of two incidence
rates when the disease is rare
Effect measures in cohort studies
Indirect Standardisation
 Do more outcomes occur in the studied population
than would be expected if the risk prevailing was the
same as in the general population?
 Estimation of expected number of outcomes
 Number of person-years at risk x incidence rate
 PYage,period,sex x incidenceage,period,sex
 Observed number/expected number ≈ RR
 Standardised incidence ratio (SIR)
SIR = Observed number of outcomes/
expected number of outcomes
= Obs/IRpop x PYexp
= (Obs/PYexp) / IRpop
= IRexp / IRpop
≈ IRexp / IR0
= IRR (RR)
Calendar time
Risk window
Exposure
Often unknown
Relevant exposure?
Ex Ex Ex
Ex Ex Ex
Ex Ex Ex
Ex Ex Ex
1-3 days?
10-15 days?
100-150 days?
years?
Hazard function
Outcome
Theoretical association
Exposure
Hazard functions
Outcome
Exposure
NSAID cohort study
 Population: Saskatchewan – province in Canada with appr. 1.1 mill.
inhabitants
 A study of the association between use of NSAIDs and risk of
gastrointestinal (GI) bleeding included all 228,392 individuals who
had redeemed one og more prescriptions for NSAIDs. The study
subjects were followed during the period 1982-1986 for
hospitalization due to upper GI bleeding
 From the paper: .. Entered our cohort upon the first receipt of a
prescription for diclofenac, indomethacin, naproxen, piroxicam or
sulindac. Person-time contributed by this person continued until
the earliest of: 1) hospitalization due to UGB, 2) death, 3)
departure from Saskatchewan or 4) end of study
 Note!: No control group of ’non-exposed’
Garcia Rodriguez et al. NSAIDs and GI-hospitalizations in Saskatchewan: A cohort study.
Epidemiology 1992;3:337-42
The person time of the study subjects was categorized
according to time since last prescription
1. Rx
Current user Recent past user
Non-user
Old past user
#1
Day
0
30
Current user
60
Current user
150
Current user
Current user
Recent past user
#2
Day
0
1.Rx
Person 1
Person 2
30
2.Rx
Current user
30
120
30
3.Rx
30
30
60
4.Rx
Recent past user Old past user
30
90
30
-
Nonuser
>90
-
Incidence rate ratios of GI-hospitalisations of NSAID users
Current users
Recent past users
Old past users
(0-30 days)
(30-60 days)
(60-150 days)
Diclofenac
3.9
2.2
1.3
Indomethacin
4.0
1.7
1.4
Naproxen
3.8
2.3
1.4
Nonusers
1.0
Modified from Garcia Rodriguez et al. NSAIDS and GI-hospitalizations in
Saskatchewan: A cohort study. Epidemiology 1992;3:337-42
Absolute vs. relative disease measures
 Avoid confusing measures of frequency with
measures of association (effect measures)
Ex:
 A RR=10 is described as a high risk, or a population for
whom RR=10 is said to be at higher risk than a
population in which RR=5
 A RR=10 may be described as a high relative risk
Risk of deep vein thrombosis (DVT)
Third vs. second generation oral contraceptives
 RR  1.7 (1.4-1.7)
 AR  1.5 per 10 000 person-years
 Mortality of DVT  3%
Kemmeren et al. BMJ 2001; 323: 131-4
Vioxx (rofecoxib) and cardiovascular disease
APPROVe trial
 2,586 patients randomised to rofecoxib (Vioxx) (25
mg daily; n=1287) or placebo (n=1299) during a 3year study period
 1.50 CVE per 100 py (46 events; 3,059 py) vs.
 0.78 CVE per 100 py (26 events; 3,327 py)
 RR = 1.92 (1.19-3.11)
 AR  72 pr. 10 000 py
Bresalier et al. N Engl J Med 2005; 352: 1092-1102
Attributable proportions
 What proportion of the disease among the exposed is
attributable to the exposure (APexp)?
APexp = IR+-IR0 / IR+ = AR / IR+ = (RR-1)/RR
 What proportion of the disease in the total study population of
exposed and non-exposed individuals is attributable to the
exposure (APpop)?
APpop = IRpop-IR0 / IRpop
= AR x pe / IRpop
(pe = exp. prevalence in population)
= APexp x pc
(pc = exp. prevalence among cases)
= [(RR-1) x pe] / [(RR-1) x pe - 1]
Attributable proportion
Incidence rates of head and neck cancer per 100,000 py
”Non-drinker”
”Drinker”
”Non-smoker”
”Smoker”
1
4
3
12
 Among drinking smokers, what proportion of head and
neck cancer is caused by smoking?
 Among drinking smokers, what proportion of head and
neck cancer is caused by drinking?
Attributable proportion
Incidence rates of head and neck cancer per 100,000 py
”Non-smoker”
”Non-drinker” 1
”Drinker”
3
”Smoker”
4
12
 Among drinking smokers, what proportion of HNC is caused
by smoking?
 AP = IRD/IR+S+A = (IR+S+A-IR-S+A)/IR+S+A = (12-3)/12 = 75%
Attributable proportion
Incidence rates of head and neck cancer per 100,000 py
”Non-smoker”
”Non-drinker” 1
”Drinker”
3
”Smoker”
4
12
 Among drinking smokers, what proportion of HNC is caused by
drinking?
 AP = IRD/IR+S+A = (IR+S+A-IR+S-A)/IR+S+A = (12-4)/12 ≈ 67%
A hypothetical population consists of 20.000 users of non-steroid
anti-inflammatory drugs (NSAIDs) og 100.000 non-users of
NSAID. The study subjects are followed for one year for the
occurrence of upper gastrointestinal (GI) bleeding
Study population
NSAID users
N
GI bleeding
20,000
100
Non-users of NSAID
100,000
100
In total
120,000
200
Please calculate the following measures of frequency and risk:
1. Incidence rate (IR) for GI bleeding in each exposure group
2. Incidence rate ratio (IRR) for the association between NSAID and upper GI
bleeding
3. Incidence rate difference (IRD≈AR) between NSAID users and non-users
4. Attributable proportion (APexp) among users of NSAIDs
5. Attributable proportion (APpop) in the total population
(Censoring in the risk population should be ignored)
Study population
NSAID users
N
GI bleeding
20,000
100
Non-users of NSAID
100,000
100
In total
120,000
200
IRNSAID = 100/20000 = 0.005 = 5 per 1000 person-years
IRo =
100/100000 = 0.001 = 1 per 1000 person-years
IRpop =
200/120000 = 0.00167 = 1.67 per 1000 person-years
IRR = IRNSAID/IRo = 5/1 = 5
AR = IRD = IRNSAID–IRo = 5-1 = 4 per 1000 person-years
APexp = AR/IRNSAID = 4 per 1000/5 per 1000 = 0.80 or 80%
ARpop = IRpop–IRo = 1.67 – 1 = 0.67 per 1000 person-years
APpop = ARpop /IRpop = 0.67/1.67  0.40 or 40%