IKM Cohort Study

7/27/2019 IKM Cohort Study

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Cohort Study

Subodh S GuptaDr. Sushila Nayar

School of Public Health

MGIMS, Sewagram


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Type of study Alternate name Unit of study

Observational studies

Descriptive studies Analytical studies

Ecological Correlational Populations

Cross-sectional Prevalence Individuals

Case-Control Case-Reference Individuals

Cohort Follow-up/ Longitudinal Individuals

Experimental/ intervention StudiesRandomized ControlledStudies

Clinical Trial Patients

Field Trial Healthy person

Community Trial Community interventionstudies

Communities


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Definition & SynonymsDefinition

The cohort study is an observationalepidemiological study which, after themanner of an experiment, attempts to

study the relationship between apurported cause (exposure) and thesubsequent risk of developing disease.

Synonyms Follow-up Longitudinal Prospective

Incidence study


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Groups are exposure based: The group or groupsof persons to be studied are defined in terms of characteristics manifest prior to the appearance of

the disease under investigation The study is conceptually longitudinal: The study

groups so defined are observed over a period of time to determine the frequency of disease amongthem

A definite beginning and end

The cohort design


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The cohort design

Efficient for examiningWhen there is good evidence of exposure anddisease.

When exposure is rare but incidence of diseaseis higher among exposedWhen follow-up is easy, cohort is stableWhen ample funds are availableCommon outcomes


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The cohort design

Many different outcomes for same exposure The dynamic nature of many risk factors

and their relations in time to diseaseoccurrence can be captured here (cannotbe done in cross-sectional study and onlywith difficulty in case-control study)

Associations (not cause and effect) Estimate incidence within risk factor groups

Cannot estimate prevalence of risk factor


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Time

Direction of enquiry

Population

Cases

(Peoplewith disease)

Exposed

Not exposed

Exposed

Not exposed

Controls(Peoplewithout disease)

Case control study


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Types of cohort study

Historical/ Retrospective/ Non-concurrent Prospective/ Concurrent

The distinction between retrospective andprospective cohort studies is important, notbecause of any conceptual difference ordifferences in interpretability of findings, butbecause of relevance to some practical issues,mostly the ability to control confounding.


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Time

Population

Peoplewithout

theoutcome

Exposed

Not Exposed

Diseased

Not diseased

Diseased

Not diseased


Point in time when enquiry begins?


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Population

Peoplewithout

theoutcome

Exposed

Not Exposed

Diseased

Not diseased

Diseased

Not diseased

Time


Both exposures and outcomesmeasured prospectively


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Population

Peoplewithout

theoutcome

Exposed

Not Exposed

Diseased

Not diseased

Diseased

Not diseased

Exposures measured retrospectivelyand outcomes prospectively

Time



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Population

Peoplewithout

theoutcome

Exposed

Not Exposed

Diseased

Not diseased

Diseased

Not diseased

Both exposures and outcomesmeasured retrospectively

Time



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Advantages Direct estimate of risk and rate of disease

occurrence over time An efficient means of studying rare exposures Assess multiple outcomes of a single exposure Establish temporal relationship between exposure

and outcome Exposure definitely precedes the outcome Avoids recall bias, survival bias Does not require strict random assignments of

subjects Can be done with original data or secondary data

Best observational design to establish

association


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Disadvantages

Very large sample sizes, especially for rareoutcomes Expensive and time-consuming Attrition problem (Loss to follow-up) Differences in the quality of measurement of exposure or disease b/w the cohorts may

introduce misclassification (information bias) Can not infer causal relation

Very specific finding Complexity of data analysis Ethical issues Study effects


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Cohort Study: Steps


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1. Identification of study population andinitial steps

2. Measurement of exposure3. Selection of study and comparison

cohorts4. Follow-up (for outcome

measurement)5. Data analysis

Steps in conducting cohort study


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Types of cohorts

Closed or fixed cohorts:Fixed group of persons followed from a certainpoint in time until a defined endpointStarting point - exposure defining event

Endpoint occurrence of the disease, loss tofollow-up, deathThe exposure is an event which occurs onlyonce

Open or dynamic cohorts: Subjects may enter or leave the study at anytime

Exposure status may change over time


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Cohorts

General population cohorts: populationgroups offering special resources for follow-up or data linkage are chosen, and the

individuals are subsequently allocatedaccording to their exposure status Special exposure cohorts: Samples chosen

on the basis of a particular exposure

Exposures may be a particular event, apermanent state or a reversible state


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General population cohorts(groups offering special resources)

Groups with readily available health records Certain professional categories

Obstetric populations Volunteer groups Geographically identified cohorts

Record linkage


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Special exposure cohorts(groups offering special resources)

Exposed to certain factor or event Occupational groups

Based on qualitative characteristics


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Population-based Cohort Studies

Advantages Estimation of distributions and prevalence

rates of relevant variables Risk factor distributions Ideal setting in which to carry out unbiased

evaluation of relations


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Selection of comparison group

Internal comparisonOnly one cohort identifiedLater on, classified into study and comparison cohortbased on exposure

External comparisonMore than one cohort identifiede.g. Cohort of radiologist compared withophthalmologists

Comparison with general population ratesIf no comparison group is available we can comparethe rates of study cohort with general populationCancer rate of uranium miners with cancer in generalpopulation


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Ideal Cohort

Stable cohort Cooperative cohort Committed cohort Well informed cohort


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Exposure measurement

Exposures: exogenous and/ or endogenousReference periodFrequency of follow-up

Challenge of prospective data collectionChanges in instrument over time

Use of repeated measuresData collection costs


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Discrete events Single events

MortalityFirst occurrence of a disease or health-relatedoutcome

Multiple occurrencesDisease outcome

Transition between states of health/ diseaseTransitions between functional states

Level of a marker

Follow-up: Types of outcomes


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Exercise 1 An investigator wants to discover whether or not

being overweight in adolescence increases the risk of cardiovascular mortality in adulthood.a) Assuming historical records are available, would a

prospective or retrospective study be morepractical?

b) Who would comprise the investigator's cohortunder study?

c) Who would comprise the investigator's exposedand unexposed groups in this cohort?


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Group Exercise Design a Cohort Study

Outline the steps which you will require to do forthis study

Special efforts you may need to do for follow-up of the study subjects

What care you will need to take to reducemeasurement bias

Calculate the sample size


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Challenges in conducting

Cohort Study


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Challenge 1: multiple dimensions of time in cohort study

Age

Calendar period

Exposure 1

Exposure 2

Exposure i

Covariate 1Covariate 2

Covariate iStart of study End of study


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Effect of Nonresponse

Nonresponse: a major problem A differential nonresponse will distrorts the

true relationship b/w exposure and outcome


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Nonresponse: random or selective?

Exposure data: find out if nonrespondentsare different from the respondents

Intensive efforts within the study designFollow-up of the nonrespondents as well asrespondents


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Challenge 3:Large Modern Cohort Studies

Huge requirements of resources and manpower Management of huge database Follow-up Exposure information Data quality? Collection of biologic samples?


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Challenge 4:Long term follow-up

Operational problems Cumulative risk getting closer to one


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Cohort Study Analysis


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Standard 2 X 2 table(Relation between exposure and outcome)

DISEASE STATUS

Present Absent Total

EXPOSURE

STATUS

Present a b a + b

Absent c d c + d

Total a + c b + d N


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Two types of measures for rate

Cumulative incidence = Proportion of studysubjects getting the outcome during thestudy period

Incidence rate = New cases/ Person-timeunder observation


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Number of new cases of disease

occurring over a specified periodof time in a population at risk.

1. Cumulative incidence rate:


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EXAMPLE

A surveillance system for Hospitalacquired infection among the post-operative patients in a month.


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Example

0 5 10 15 20 25 30

9

61414

24

1914

4

5

1921

6


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Number of new cases of diseaseoccurring over a specified periodof time in a population at risk

throughout the interval .

2. Incidence density:


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Incidence density requires us to addup the period of time each individualwas present in the population, andwas at risk of becoming a new caseof disease.Incidence density characteristicallyuses as the denominator person-years at risk. (Time period can beperson-months, days, or even hours,depending on the disease processbeing studied.)


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USES OF INCIDENCE DENSITY ANDCUMULATIVE INCIDENCE

Incidence density gives the bestestimate of the true risk of acquiringdisease at any moment in time. Cumulative incidence gives the

best estimate of how many peoplewill eventually get the disease in anenumerated population.


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Standard 2 X 2 table(Relation between exposure and outcome)

Peripheral Vascular Disease


Cigarette

Smoking

Present 15 1712 1727

Absent 41 3188 3229

Total 56 4900 4956


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l X 2 table(Relation between exposure and outcome)

Disease status


Cholesterolquintiles

1st 15 798 813 2nd 20 794 814 3rd 26 791 817

4th

41 785 826 5 th 48 777 825

Total 150 3945 4095


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Comparing risks in different groups

Relative risk OR Risk ratio (RR) Attributable risk OR Risk difference (AR) Attributable risk percent (AR%) Population attributable risk (PAR) Population attributable risk percent (PAR%)

Odds Ratio (OR)


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Relative risk OR Risk ratio

Ratio of the risk among exposed to the risk among unexposed[Risk (Exp) / Risk (Unexp)]

Risk of disease among exposed = [a/ [a+ b)] Risk of disease among unexposed = [c/ [c +d)]

RR = [a/ [a +b)] / [c/ [c +d)] For null hypothesis, Risk ratio will equal

one

SE=


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Risk difference vs. Relative risk

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0

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A b s o

l u t e r i s

k L u n g c a n c e r

d e a

t h s p e r

1 0 0

, 0 0 0

a d u

l t m a

l e p e r y e a r

Smokers

Non smokers

R el a t i v er i s k

1

22

A b s ol u t er i s k


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Risk difference vs. Relative risk

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l u t e r i s

k L u n g c a n c e r

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1 0 0

, 0 0 0

a d u

l t m a

l e p e r y e a r

Smokers

Non smokers

Ri s k d i f f er en c e

A b s ol u t er i s k s

( E x p & Un ex p )

Att ib t bl i k t


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Attributable risk percent amongexposed

Among exposed, what percent of the total risk for disease is due to the exposure

AR% (Exposed) = [Risk (Exp) Risk (Unexp)]/ Risk (Exp) X 100 = (RR 1)/ RR X 100

= (OR 1)/ OR X 100 (if risk is small)


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191

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A b s o

l u t e r i s k L u n g c a n c e r

d e a

t h s p e r

1 0 0 , 0 0 0 a

d u

l t m a

l e p e

r y e a r

Smokers Non smokers


% r i s k d u e

t o

ex p o s ur e

1

22

A b s ol u t er i s k s

( E x p )

% risk due tobackground

Attributable Risk Percent


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Attributable Risk Percent191

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1 0 0

, 0 0 0 a

d u

l t m a

l e p e r y e a r

Smokers Non smokers


p 0 ( RR-1 )

p 0

p0RR

p 0 RR

1

Attributable risk Percent = (RR-1)/ RR *100


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Population attributable risk

In the general population, how much of thetotal risk for disease is due to the risk factor

Risk (Total) Risk (Unexp) Risk (Total)

= [Proportion population Exp X Risk (Exp)] +[Proportion population Unexp X Risk (Unexp)]


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Population attributable risk percent

Among the general population, what percentof the total risk for disease is due to the risk factor

PAR% = [Risk (Total) Risk (Unexp)]/ Risk (Total) X 100 = [Pe (RR 1)]/ [1+ Pe (RR 1)] X 100



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0

20

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60

80

100

120

140

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A b s o

l u t e r i s k o

f l u n g c a n c e r

d e a

t h p e r

1 0 0

, 0 0 0 a

d u l t m a

l e p e r y e a

r

Smoker Nonsmoker

(RR-1)(1-P e )Pe (RR-1)

(1-P e )P e


Population Attributable risk Percent

= [Pe (RR 1)]/ [1+ Pe (RR 1)] X 100

RR

1


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Risk Reduction Risk (T/t) = a/(a+b) Risk (Exp) = c /(c+d) RR = Risk (T/t)/ Risk (Exp) ARR = Risk (Exp) Risk (T/t) RRR = [Risk (Exp) Risk (T/t)] / Risk (Exp)

= 1-Risk(T/t)/Risk(Exp)= 1-RR

NNT = 1/ARR = 1/Risk(Exp)*RRR NNH


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Analytical considerations

Concurrent follow-up Varying follow-up dates Moving baseline dates Withdrawals Competing causes of death


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Anal tical considerations


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Analytical considerations Concurrent follow-up

Simple risk-based analysesSurvival analysis

Varying follow-up dates

Simple risk analysis for all events up to, but notexceeding, the minimum elapsed timeSurvival analysis

Moving baseline dates

Ignore and measure elapsed time since recruitmentSurvival analysis

Withdrawals

Competing causes of failure


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Advanced methods

Standardization Stratification Life Tables Multivariate analysis and Cox regression

E i 2


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Exercise 2 A cohort study to explore the relationship between

visual impairment and the risk of injuries from fallsamong the elderly.

A total of 400 visually impaired (VI) persons >70yrs are compared against 400 controls without VI.

Over a 5-year follow-up period, 80 VI persons and20 non-VI persons have injuries from falls.

a) Construct a 2x2 table from the information above

b) Calculate the followings with their CI :Cumulative Incidence rate for exposed and unexposedRelative risk

Attributable risk & Attributable risk percent

E i 2


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Exercise 2 A cohort study to explore the relationship between

visual impairment and the risk of injuries from fallsamong the elderly.

A total of 400 visually impaired (VI) persons >70yrs are compared against 400 controls without VI.

Over a 5-year follow-up period, 80 VI persons and20 non-VI persons have injuries from falls.

a) Construct a 2x2 table from the information above

b) Calculate the followings with their CI :Cumulative Incidence rate for exposed and unexposedRelative risk

Attributable risk & Attributable risk percent

Exercise 3


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Exercise 3

A retrospective cohort study to explore therelationship between perimenopausalexogenous estrogen use and the risk of coronary heart disease (CHD).

A total of 5000 exposed and 5000unexposed women are enrolled andfollowed for 15 years for the developmentof myocardial infarction (MI).

A total of 200 estrogen users and 300nonusers had MIs.

Exercise 3 (Contd )


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a) The risk (CI) of a MI among estrogen usersb) The risk (CI) of a MI among nonusers of

estrogenc) The relative risk (CIR) for MId) Based on the results of this study is

estrogen use a causative or protectivefactor for MI?

Exercise 3 (Contd.)

Exercise 4


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Exercise 4Shaper et. al. (1988) A random sample of 7729 middle-aged British men Each man asked, at baseline, his alcohol

consumption Next 7.5 years, death certificates collected for any

subject who died

Alcohol consumption group ( Unit/wk )

None Occasional(42)

Subjects 466 1845 2544 2042 832Deaths 41 142 143 116 62


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a) Calculate the risk and the relative risk foreach alcohol consumption group.

b) Why might the conclusion based on theabove table may be misleading? Givenadequate funding, describe how?

Exercise 4 (Contd.)

Exercise 5


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Exercise 5 In a cohort study of 34387 menopausal women in Iowa,

intakes of certain vitamins were assessed in 1986. In theperiod up to the end of 1992, 879 of these women werenewly diagnosed with breast cancer. The table belowshows data for two vitamins, classified according to rankedcategories of intake.

Vitamin C Vitamin EEvents PY Events PY

1 (low) 507 124,373 570 143,117

2 217 57,268 129 33,9503 76 19,357 71 19,536

4 55 17,013 28 6,942

5 (high) 24 7,711 81 22,176

Exercise 5 (Contd )


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a) For each vitamin, calculate the relativerates (with 95% confidence intervals)taking the low-consumption group as thebase. Do your results suggest any

beneficial (or otherwise) effect of additional vitamin C or E intake?

Exercise 5 (Contd.)


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Types of bias

Selection bias Follow-up bias Information bias Confounding bias Post hoc bias


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Selection bias

Group studied does not reflect the samedistribution of factors (such as age, sex,SES, behavior etc.) as occurs in the generalpopulation

Effect of volunteeringWhole spectrum of independent variables notrepresented in the study group

Presence of incipient diseaseDistribution of covariatesSurvival cohorts: cohorts ascertained long afterexposure

Follow up bias


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Also known as

Migration Bias

In nearly all large studies some members

of the original cohort drop out of the study

If drop-outs occur randomly, such thatcharacteristics of lost subjects in onegroup are on an average similar to thosewho remain in the group, no bias isintroduced

But ordinarily the characteristics of thelost subjects are not the same

Follow-up bias


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Example of

lost to follow-up

+ - Total

+ 50 100 150-

10000 20000 30000

EXPOSURE

irradiation

+ - Total

+ 60-

4000 8000 12000

30 30

EXPOSURE

irradiation

RR= 50/10000100/20000

= 1

RR= 30/400030/8000

= 2

Example

healthy worker


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Example. healthy workereffect

Question: association b/w formaldehydeexposure and eye irritation

Subjects: factory workers exposed toformaldehyde

Bias: those who suffer most from eyeirritation are likely to leave the job attheir own request or on medical advice

Result: remaining workers are lessaffected; association effect is diluted


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Measurement / (Mis) classification

Exposure misclassification occurs whenexposed subjects are incorrectly classifiedas unexposed, or vice versa

Disease misclassification occurs whendiseased subjects are incorrectly classifiedas non-diseased, or vice versa


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Reassignment to exposure category


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eass g e t to e posu e catego y Changes in dichotomous exposure, if not taken

into consideration will tend to make the strengthof an observed association lower than that whichactually existed

Latency is likely to be short

Exposure accumulates over time during the study Very accurate results desirable

Reassignment may not be possible

Close cohort as a ruleLatency is very longDuration of follow-up is very long

Separate examination of outcome in those whochanged exposure status during the study

C f di bi


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Confounding bias

Other factors which are associated withboth outcome and exposure variables donot have the same distribution in theexposed and unexposed group

E l f di


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Examples confounding

COFFEE DRINKING HEART DISEASE

SMOKING

(Coffee drinkers are

more likely to smoke)

(Smoking increasesthe risk of heart ds)

R l i C f di Bi


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Resolving Confounding Bias

Standardization Stratification Multivariate adjustment


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Th k


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Thank you

I t l & E t l lidit


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Internal & External validity

Documents

IKM Cohort Study