Cohort StudyPresenter : Dr Himani

Moderator: Dr Subodh S Gupta

Types of Epidemiological study

1. Definition2. Study design3. Steps of study Identification of study population Measurement of exposure selection of study and comparison group Follow-up Analysis4. Advantages and disadvantages 5. Biases6. Variants of cohort study7. Cohort study and other study designs 8. Role of Cohort study in Epidemiology

Framework

The cohort study is an observational analytical epidemiological study which, after the manner of an experiment, attempts to study the relationship between a purported cause (exposure)and the subsequent risk of developing disease.

Synonyms: Incidence studies, prospective studies, follow-up studies, longitudinal studies

Definition

Study design

When there is good evidence of exposure and disease.

When exposure is rare and incidence of disease amongst exposed group is more

When follow-up is easy

When sufficient funds are available

Indication of Cohort study

Open Cohort: Subjects can leave and enter the cohort at any time

Closed Cohort : Fixed number of persons are followed over a specified time till the end point.

Types of cohort

Identification of study population

Measurement of exposure

Selection of study and comparison group

Follow-up (for outcome measurement)

Analysis

Steps of Cohort study

Free of disease of interest

Equally susceptible to development of the disease at the beginning of the study

Equivalent information (quantity and quality) should be available on exposure and disease

Both the groups should be accessible and available for follow- up.

Criteria for the selection of subjects in cohort

Internal comparison◦ Single cohort enters the study◦ Later on, classified into study and comparison

cohort based on exposure

External comparison◦ More than one cohort identified ◦ e.g. Cohort of radiologist compared with

ophthalmologists or smokers with non smokers

Comparison with general population rates◦ If no comparison group is available we can

compare the rates of study cohort with general population

◦ Frequency of cancer amongst asbestos workers compared with cancer in general population

Selection of Comparison group

Existing Records

Interviews, self administered questionnaire, mailed questionnaire

Examinations: medical and other special examinations

Measure of environment: measure of air pollution, exposure to radiation or other toxicological substances

Gathering data on exposure

Objectives of Follow up uniform and complete follow-up of all cohort groups complete ascertainment of outcome events standardized diagnosis of outcome events.

Methods: correspondence with the subject and other

informants, periodic re-examination of the subjects, and indirect surveillance of hospital records and death

certificates.

Follow up

The estimated sample size n for cohort studies is calculated as

N= [Zα √(1+1/m)p(1-p) +Zβ √ {p0(1-p0) / m} +p1(1-p1)]2

(po-p1)2

  Where

m = number of control subjects per experimental subject

po = probability of events in control

p1 =probability of events in experimental subjects

p= p1+ m po

m+1  

Sample size calculation

Sample Size calculation

n=sample size µ1= population mean in group1 µ2= population mean in group2µ1- µ2 = difference the investigator wishes to detectσ = population variance (SD)a= conventional multiplier for alpha =0.05b= conventional multiplier for power = 0.80

When mean is available

Relative risk or risk ratio

Risk difference

Attributable risk

Population Attributable Risk

Rate Ratio

Analysis of Cohort study

Table: Summary of Risk Data from a cohort study

Disease No Disease Total

Exposed a b a+b

Not exposed c d c+d

Total a+c b+d a+b+c+d

Incidence (exposed) = Exposed persons who developed ds = a/(a+b) All exposed person Incidence (Unexposed) = Unexposed persons who develop ds = c/(c+d) All unexposed persons

Relative Risk = _Incidence (exposed)__ = _a / (a+b)_ Incidence (unexposed) c / (c+d)

Risk difference = Incidence (exposed) – Incidence(nonexposed) = [a/(a+b)] – c/(c+d)]

Attributable Risk = Risk(exposed) – Risk(nonexposed) * 100 Risk (exposed) = (RR-1) * 100 RR

Population Attributable Risk= Risk(Total) – Risk(unexposed) *100 Risk (total)

Table: Summary of Risk Data from a cohort studyDeveloped

diseaseDo not develop

diseaseTotal

Exposed 200 9800 10,000Not exposed 100 9900 10,000

Total 300 19700 20,000

Incidence (exposed) = Exposed persons who develop ds = 200/10,000 = 0.02 All exposed person Incidence (Unexposed) = Unexposed persons who develop ds = 100/10,000 =0.01 All unexposed persons

Relative Risk = _Incidence (exposed)__ = _0.02 = 2 Incidence (unexposed) 0.01

Risk difference = Incidence (exposed) – Incidence(nonexposed) = 0.02 – 0.01 = 0.01

Attributable risk: {(2-1)/2}*100 = 50%

Population attributable risk= {(0.015- 0.01)/0.02}*100 = 25%

Cumulative incidence Number of new cases of disease occurring over a

specified period of time in a population at risk

Incidence density Number of new cases of disease occurring over a

specified period of time in a population at risk throughout an interval

Table: Summary format of Rate data from a cohort study

Exposed Unexposed Total

Number of outcomes

a b a+b

Person time(PT)

PT(exposed) PT(unexposed) PT(total)

Rate ratio=rate of outcome amongst exposed/ rate of outcome among unexposed

Rate ratio= [a/ PT(exposed)] / [b/PT(unexposed)]

Statistical method for analyzing longitudinal data on occurrence of events.

Events can be Time to death time to onset of disease length of stay in hospital viral load measurement

Survival Analysis

Life table approach

Kaplan Mier

Cox Regression

Survival analysis

Clinically suspected casesEven

t fr

ee s

urv

ival

Direct calculation of risk ratio (relative risk)

Yield information on incidence of disease

Clear temporal relationship between exposure and disease

Particularly efficient for study of rare exposures

Can yield information on multiple outcomes of a particular exposure

Minimize bias

Strongest observational design for establishing cause and effect relationship

Advantages of cohort study

Time consuming

Often requires a large sample size

Expensive

Not efficient for study of rare diseases

Losses to follow-up may diminish validity

Changes over time in diagnostic methods may lead to biased results

Disadvantages of cohort study

Selection bias

Information bias/ Misclassification bias

Bias due to confounding

Post hoc bias. 

Biases

the group actually studied does not reflect the same distribution of factors (such as age, smoking, race, etc.) as occurs in the general population.

This is due to members refuse to participate records are not available

Particular subgroup may not be representative of general population

Resolution: by careful selection of individuals for inclusion in the study and by making every attempt to characterize differences that may exist between respondents and non-respondents.

Selection Bias

Disease No disease

Exposure +

100 900 1000

Exposure - 50 950 1000

150 1850 2000

Selection Bias in historical cohort

True RR =2.0

20% of employee heath records were lost or discarded, except in “solvent” workers who reported illness (1%loss)

Disease No disease

Exposure +

99 720 819

Exposure - 40 760 800

139 1480 1619

RR=2.42

Some members of the original cohort drop-out of the study

If the loss to follow-up occurs equally in the exposed and unexposed groups, and their characteristics are nearly similar, the internal validity should not be affected.

Resolution: by intensive follow up comparison of baseline characteristics of those who

are loss to follow up and those who are not

Follow- up Bias

Differential loss to follow up in a prospective cohort study on oral contraceptives and thromboembolism(TE)

Without losses

TE Normal Total

OC+ 20 9,980 10,000

OC- 10 9,990 10,000

RR= 2 (truth)

After 40% loss to follow up

Final sample

TE Normal Total

OC+ 8 5,980 5,988

OC- 8 5,990 5,998

RR=1

Also known as ‘misclassification bias’

result from measurement errors, imprecise measurement, and misdiagnosis for whatever reason.

Resolution: by using well-defined precise measurements and classification criteria for which the sensitivity and specificity have been determined.

Information Bias

use of data from a cohort study to make observations that were not part of the original study intent.

These findings should be treated as hypotheses that are an appropriate subject for additional studies.

Post hoc bias

When other factors that are associated with both the outcome and exposure variables do not have the same distribution in the exposed and unexposed groups.

Confounder should have 3 criterias: it should be cause of disease it is associated with risk of disease it should not be an intermediate step in causal

pathway between exposure and disease

Bias due to Confounding

During design of study randomisation restriction matching

During analysis stratification statistical modelling

Nested Case-Control study

Variant of Cohort study

Nested Case-control study

Cohort study Case control study

Study group Exposed persons Persons with disease

Comparison group Unexposed persons Persons without disease

Outcome measurements Incidence in exposed group and incidence in unexposed

Proportion of cases exposed and proportion of controls exposed

Measures of risk Relative riskAttributable risk

Odds ratio

Best when Exposure is rare Disease is rare

Multiple associations Possible to study association of an exposure with several diseases

Possible to study associations of a disease with several exposures or factors

Cohort study and other studies in epidemiology

Cohort study Randomized control trial

Exposure is natural Exposure is not natural and decided by investigator

Randomization is not there in cohort studies

Randomization if heart of RCT

Natural history of the disease: For example, cohort studies of individuals who were

infected with HIV revealed that a drop in the level of T lymphocytes having the CD4 marker was associated with being infected with HIV, and that a further decline in CD4 cells was associated with developing clinical symptoms and AIDS

  Causation of the disease: eg. role of high blood pressure as a major cause of

stroke, myocardial infarction, and chronic kidney disease.  Evaluating public health programmes: If relevant statistics are not routinely available, cohort

studies can be used to assess whether the programme has an impact by calculating the incidence of a disease.

Role of cohort study in epidemiology

1. Gordis L, Epidemiology, Third Edition(2004), Elsevier Saunders.2. Detels R, McEwen J, Beaglehole R, Tanaka H, Oxford Textbook

of Public Health, Fourth edition(2002), Oxford University Press3. Beaglehole R, Bonita R, Kjellstrom T, Basic Epidemiology, 2nd

Edition(2006)WHO.4. Hill, Mc Graw, Medical Epidemiology, 4th Edition(2007), Lange.5. Bhalwar R, Vaidya R, Tilak R, Gupta R, Kunte R, Textbook of

Public Health and Community Medicine. 1st Edition (2009).6. Kasiulevičius V, Šapoka V, Filipavičiūtė R, Sample size

calculation in epidemiological studies, Gerontologija 2006; 7(4): 225–31

7. Grimes DA, Schulz KF, Cohort studies: marching towards outcome, Lancet2002;359:341-45.

References