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Introduction to cohort study

王齡誼lingyiwang@tzuchi.com.tw

2019/4/12

Learning objectives

• To know what is cohort

• To know the characteristics of cohort study

– Incidence

– Person-year

– Relative risk/risk ratio/rate ratio

• To know what is the ideal comparison

group

• To know the bias in cohort study

• Advantages & disadvantages

Idea

(hypothesis)

Study

design

Statistical

Analysis

Experimental design

• Randomized controlled trial

Non-experimental (observational) design

•Cohort study (世代追蹤研究)

•Case-cohort study

•Nested case-control study

•Case-control study (病例對照研究)

•Case-crossover study

•Case-time control study

•Cross sectional study (橫斷性研究)

資料收集

From idea to research

Test the hypothesis

Environmental exposure

or host characteristics

Disease or other health

outcome

1. An association is

observed2. Is the observed

association causal?

Population

Not

Exposed

Exposed

Randomly

Allocated

Population

Not

Exposed

Exposed

Self-

Selection

RCT vs. Cohort study

What is cohort?

Cohort studies:

marching towards outcomes

Cohort Study

Follow up

Exposed Not

Exposed

Disease No

disease

Disease No

disease

Defined population

Self selection

Retro.

1992

2018

Prosp.

2018

2032

Exposure Outcome

1. 有A暴露的人,未來得B疾病的發生率(incidence rate)或危險性 (risk)?

2. 有A暴露的人,未來罹患B疾病的發生率(或危險性)是沒有A暴露的人的幾倍,也就是說,有A暴露的人相對於沒有A暴露的人,其相對危險性(relative risk)為何?

HBsAg status PHC

The framingham study

Exposed Not Exposed

Disease No

diseaseDisease No

disease

Defines population

(a town in Massacusetts, 30~62 year-old)

Self selection

Prosp.

1948

Blood pressure, smoking, body

weight, diabetes, exercise, etc.

Coronary heart disease, stroke,

congestive heart failure, peripheral

arterial disease, etc.

Cohort Study

Exposed

people

Develop

DiseaseDo Not

Develop

Disease

Non-Exposed

people

Develop

DiseaseDo Not

Develop

Disease

If exposure is associated with disease:

A cohort study can provides..

• Incidence: the number of newly diagnosed cases of a disease.

• Risk is the number of new cases of a disease divided by the

number of persons at risk for the disease.

• Incidence rate is the occurrence rate of new cases of a disease

in defined population during a specific time period. (person time

at risk)

# of new eventspersons at risk at begining of study

# of new eventsperson-time at risk

Person-years (人年)

Subjects Time

at risk

A 8.3

B 11.0

C 14.0

D 14.0

E 10.2

F 3.0

G 12.0

H 7.0

I 10.0

J 3.0

K 9.0

L 6.2

81 95

Loss to f/u

disease developed

Incidence ratesubjects Time

at risk

A 8.3

B 11.0

C 14.0

D 14.0

E 10.2

F 3.0

G 12.0

H 7.0

I 10.0

J 3.0

K 9.0

L 6.2

Total time at risk =107.7 person-yrs

Incidence density (0~infinity) :

= 3/107.7

=0.028/person-yr

= 28/1000 person-yr

= 2.33/1000 person-month

= 0.54/ 1000 person-weeks

Unit depends on investigators, frequency of

event.

Cumulative incidence (risk) (0~1):

= # of new disease/ initial population

=3/12

Design of a cohort Study

Disease

developed

Disease

Not

developed

Total

Person-yr

At risk

Total

subjects

Incidence

rates of

Disease

Exposes a b T1 a+ba/(a+b) or

a/T1

Non-

exposed c d T2 c+dc/(c+d) or

c/T2

Association measure in cohort study

exp

non-exp

risk

risk

a

a bRRc

c d

當每人追蹤時間相同:

exp 1

non-exp

2

I

I

a

TRR

c

T

當每個人追蹤時間不同:

1

2

Rate difference:Iexp –Inon-expRisk difference: riskexp-risknon-exp

Interpretation RR of a Disease

RR Interpretation of RR

=1 Risk in exposed equal to risk in non-exposed

(no association)

>1 Risk in exposed greater than risk in non-

exposed (possibly causal)

<1 Risk in exposed smaller than risk in non-

exposed (possibly protective)

Incidence rate & person years

BMI #

MIs

Person-years

at risk

Rate of MI per

100,000 person-Yrs

(incidence rate)

Crude

RR

<21 41 177,356 23.1 1.0(ref)

21-23 57 194,243 29.3 1.3

23-25 56 155,717 36.0 1.6

25-29 67 148,541 45.1 2.0

> 29 85 99,573 85.4 3.7

Type of cohort• Dynamic cohort (Open cohort)

– Exposure status may change during follow up

– Subjects may enter the study at any time

– The cohort is defined by person-times rather

than on persons.

• Fixed cohort

– No new subjects enter the study after study

follow-up date

– Exposure status is consistent

– If there is no loss to follow-up: closed cohort

CHOICE OF STUDY POPULATION

CHOICE OF COMPARISON GROUP

Internal and external

The ideal comparison group

臨床角度問問題: Do patients who receive an atypical

antipsychotic drug have an increased risk of hip fracture?

Cohort study角度問問題: What would have happened to

these patients if they had not received the atypical

antipsychotic drug?

Ideally, the comparison group in the cohort study

should be identical to the intervention group, apart

from the fact that they did not receive the intervention

Internal comparison group

• That is, the experience of those members

of the cohort who are either unexposed or

exposed to low levels can be used as the

comparison group.

External comparison group

• When the cohort is essentially homogeneous in

terms of exposure to the suspected factor, a similar

but unexposed cohort, or some other standard of

comparison, is required to evaluate the experience

of the exposed group.

– People in employment from the same geographical area .

– General population of the geographical area in which the

exposed individuals reside.

Multiple comparison groups• When we can’t be sure that any single group

will be sufficiently similar to the exposed

group in terms of the distribution of potential

confounding variables.

• The study results may be more convincing if

a similar association were observed for a

number of different comparison groups.– an internal comparison groups (same factory but having different

job) and the experience of general population (national and local

rates) may be used.

Possible types of comparisons in

cohort study

Ex: association between antipsychotic drugs and hip

fracture.

General population (all elderly)

- intervention vs. alternative intervention

- intervention vs. no intervention

Restricted population (elderly people with dementia)

- intervention vs. alternative intervention

- intervention vs. no intervention

BIAS

Reliable (precise)

Lack of random error

Valid

Lack of systematic errorReliable

& valid

Bias is a systemic error, rather than the random variation or

lack of precision.

Bias occurs in the recruitment of participants, the measurement

of their risk factors and outcomes.

Bias threatens study validity

Internal validity

The internal validity of a study is defined as the

extent to which the observed difference in

outcomes between the two comparison groups can

be attributed to the intervention rather than other

factors.

Bias of Cohort Study

• Selection Bias

– Attrition bias

– Healthy entrant effect

– non-response bias

• Information Bias

– Response bias

– Acertainment bias (detection bias)

• Confounding

– The effect or association between an exposure

and outcome is distorted by the presence of

another variable

Selection bias

• Selection bias occurs when there is

something inherently different between the

groups being compared that could explain

differences in the observed outcomes.

• Loss to follow-up differs between exposed

and not exposed (or between disease and

no disease).

• Follow up is usually easier in people who

have been exposed to the exposure of

interest.

Information bias• Collect different quality of information from

exposed and not exposed groups

(from participants or investigators).

– Exposure ascertainment (response bias)

under-reported the exposure behavior because

they are aware that it can affect their health.

– Diseases ascertainment (ascertainment bias,

detection bias)

diagnosis could have been influenced by

knowledge of the study research hypothesis.

Confounding

Exposure

Confounder

Disease

The effect or association between an exposure and

outcome is distorted by the presence of another variable

ex: asthma and lung cancer (smoking is the confounder)

Confounding

• Features of medical history—for example,

stroke, osteoporosis

• Exposure to drugs—for example,

benzodiazepines,oestrogens

• Demographics—for example, age and sex

• Social and behavioural factors—for example,

exercise and diet.atypical

antipsychotic

C

Hip fracture

Differences in distribution of potential

confounders

To deal with confounding

Idea

(hypothesis)

Study

design

Statistical

Analysis

Matching

RestrictionRandomization

Stratification

Regression

Matching & Restriction

a 45-yr-old women with atypical antipsychotic

a 45-yr-old woman with no intervention

Matching

Restriction

ex: Only the elder are recruited

ex: Only the older with dementia are recruited

E

C

D

Patients taking atypical antipsychotics were over

12 times more likely (63.1% vs. 4.7%) to have

dementia.

Restriction

Regression &

stratification

ANALYSIS METHODS

Data preparation

Analysis methods• Cox proportional hazard regression (HR)

– Time to an event (ex. time to hip fracture)

– person-time information

– time-varying covariates

• Poisson regression

– Count data

• Logistic regression (RR)

– Binary outcome (ex. occurrence of hip fracture)

– No loss to follow up

– Rare outcome

– Person-time information not required

Interpretation of Hazard Ratio

• HR = 0.5: at any particular time, half as many

patients in the treatment group are

experiencing an event compared to the control

group.

• HR = 1: at any particular time, event rates are

the same in both groups,

HR = 2: at any particular time, twice as many

patients in the treatment group are experiencing

an event compared to the control group.

Examples

Exposed Not Exposed

Disease No

diseaseDisease No

disease

Defines population

(40 clinical centers in USA,

50-79 yr-old postmenopausal women)

Self selection

Prosp.

1993~

1998

Active or passive smoking

Invasive breast cancer

2009/8/14

Inclusion:

93679 women

aged 50~79 yr-

old were

recruited

Exclusion:

Had conditions

that were

predictive of

survival less

than 3 years

Final subjects

for analysis:

93676 -> 79990

1

2

Which bias might the above cohort

study have been prone to?

(a) Non-response bias

(b) Healthy entrant effect

(c) Attrition bias

(d) Response bias

(e) Confounding

(f) Allocation bias

93 676

12075 Cancer Hx.

(12.9 %).

(healthy entrant

effect)

443 loss to f/u

(0.5 %).

(attrition bias)

1168 smoking status

missing (1.25%).

Under-report the

exposure

(response bias)

79 990

Non-response bias

(a) Non-response bias

(b) Healthy entrant effect

(c) Attrition bias

(d) Response bias

(e) Confounding

(f) Allocation bias

Exposure

(smoking)

Confounder

(Alcohol intake)

Disease

(breast cancer)

Allocation bias is mainly of concern in clinical trials.

(to allocate people who they think would show the greatest

benefit to a particular intervention)

Which bias might the above cohort

study have been prone to?

Advantages

•Measure the effect of each variable on

the probability of developing the outcome

of interest (RR or HR).

• A single study can examine various

outcomes.

Example: smoking vs. lung, cardiovascular, and

cerebrovascular diseases.

Disadvantages

• Expensive and time-consuming.

• Inefficient when outcome is rare.

• Loss to follow up can be a serious

problem. The rarer the outcome the more

significant the effect. (Attrition bias)

Thank you

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