RACE 622 :Study Designs & Measurements in Clinical Epidemiology

Dr.Pawin Numthavaj

Semester 1 Academic year 2017

Doctor of Philosophy Program in Clinical Epidemiology, Master of Science Program in Medical Epidemiology Section for Clinical Epidemiology & Biostatistics

Faculty of Medicine Ramathibodi Hospital, Mahidol University

CONTENTS

Cohort studies ..................................................................................................... 3

Cohort population ................................................................................................ 3

When should we use cohort design? .................................................................. 5

Type of cohort studies ......................................................................................... 6

Advantages and disadvantages of cohort studies ............................................. 8

What to look for in cohort studies? ...................................................................... 9

Way to express and compare risk .................................................................... 11

How to calculate the risks? ............................................................................... 12

Confounding ...................................................................................................... 13

Summary ........................................................................................................... 14

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OBJECTIVES

1) Able to describe definition of cohorts and studies of risk

2) Able to discuss definition, classification advantages and disadvantages of cohortstudies

3) Able express and compare risk

4) Able to discuss and control confounding factors

REFERENCE

1. Fletcher RH. Clinical Epidemiology the Essentials 5th Edition: Chapter 5 Risk

: Exposure to Disease. Lippincott Williams & Wilkins. 2014; 61-77

2. Rothman K. Modern epidemiology. Section II, Chapter 7: Cohort Studies 3rd ed.

Lippincott Williams & Wilkins. 2008;100-110

SUGGESTED READING

Appendix I: Grimes DA, Schulz KF. Cohort studies: marching towards outcomes. Lancet. 2002;359(9303):341-5.

Appendix II: Song JW, Chung KC. Observational studies: cohort and case-control studies. Plastic and reconstructive surgery. 2010;126(6):2234-42.

Appendix III: Winner B, Peipert JF, Zhao Q, Buckel C, Madden T, Allsworth JE, et al. Effectiveness of long-acting reversible contraception. The New England journal of medicine. 2012;366(21):1998-2007.

ASSIGNMENT III: Cohort study (15%) Due date: September 11, 2017

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COHORT STUDIES

Cohort study is an analytical type of observational study, based on usually primary data,

from a follow-up period of a group in which some have had, have or may have the

exposure of interest, to determine the association between that exposure and an outcome.

It is the highest in hierarchy of evidence in terms of observational studies, but it cannot

provide empirical evidence that is as strong as that provided by properly executed

randomized controlled clinical trials.

COHORT POPULATION

The term “cohort” is derived from the Roman word cohort. During battle each cohort, or

military unit, consisted of a specific number of soldiers and were traceable. The word

“cohort” has been adopted into epidemiology to define a set of people followed over a

period of time. W.H. Frost, an epidemiologist, was the first to use the word “cohort” in his

1935 publication assessing age-specific mortality rates and tuberculosis. The modern

epidemiological definition of the word now means a “group of people with defined

characteristics who are followed up to determine incidence of, or mortality from, some

specific disease, all causes of death, or some other outcome.

Focusing on follow-up period or person-time, we can categorize a cohort population into

2 groups based on the movement of individuals in a cohort.

First, fixed or closed cohort is determined when there is no movement of individuals

between exposure groups during the follow-up. Second, opened or dynamic cohort

describes a population which can be assembled from a changing registration of

individuals.

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The main key element of cohort study is to track two or more groups forward from exposure

to outcome. Figure 2 illustrates the study design. Researchers select subjects at the onset

of the study and then determine whether they have the risk factor or have been exposed.

Then all subjects are followed up over a certain period of time to observe the outcome or

the effect of the risk factor or exposure. Most importantly, all subjects must not have the

outcome of interest at the origin.

Figure 1. Diagram of cohort study design

Exposed

Non-exposed

With outcome

Without outcome

With outcome

Without outcome

Time

Direction of study

Cohort study

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WHEN SHOULD WE USE COHORT DESIGN?

Many research questions can be answered by observational studies especially the risk

question which cannot be studied with experimental studies. It is usually not possible to

conduct an experiment because it would be unethical to introduce possible risk factors

on a group of healthy people.

Research questions which cohort studies can be used for have been demonstrated in

Table 1.

Table 1. Cohorts and their purposes

Characteristic in common To assess effect of Example

Exposure Risk factor Lung cancer in people who smoke

Disease Prognosis Survival rate for patients with breast cancer

Preventive intervention Prevention Reduction in incidence of pneumonia after pneumococcal vaccination

Therapeutic intervention Treatment Improvement in survival for patients with Hodgkin’s disease given chemotherapy

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TYPE OF COHORT STUDIES

Cohort studies can be conducted in 2 types

1. Prospective cohort studies or concurrent cohort studies

This cohort can be assembled in the present and followed into the future. When the study

is planned before collecting data, researchers can be sure to collect all variables

including possible confounders. In a prospective study, the investigator begins the study

at the same time as the first determination of exposure status of the cohort. When

proposing a prospective cohort study, the investigator first identifies the characteristics of

the group of people he/she wishes to study. The investigator then determines the present

case status of individuals, selecting only non-cases to follow forward in time. Exposure

status is determined at the beginning of the study. All information in a prospective cohort

study can be collected in a standardized method that reduces measurement bias.

2. Retrospective cohort studies or historical cohort studies

This cohort can be identified from past records and followed from that time up to the

present. It takes advantage of well-designed medical databases. It can take less time to

outcome development. However, some factors may not have been recorded, so they

cannot be included in the analysis, which means confounders may not be controlled.

Doing a retrospective cohort study requires sound data on exposure status for both cases

and noncases at a designated earlier time point.

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Quiz: How does a retrospective cohort study differ from a case-

control study? Suppose you are investigating the association of

caffeine consumption and bone loss among lecturers at a

university. How would the sample selected for a case-control study differ from those

included in a retrospective cohort study?

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ADVANTAGES AND DISADVANTAGES OF COHORT STUDIES

The strengths and limitations of different types of cohort studies have been summarized

in Table 2.

Table 2. Advantages and disadvantages of cohort studies

Advantages Disadvantages

All cohort study types

The only way to estimate incidence

Follows the same logic as the clinical question

Demonstrates temporal relationship

Exposure can be identified without bias of knowing the outcome

Can assess the relationship between exposure and many disease

o Susceptible to confounding and

other biases

Prospective cohort studies

Can collect lifestyle and demographic data not available in most medical records

Can set up standardized methods of measuring exposure and outcomes

o Expensive and inefficient

because many subjects must be enrolled and follow-up over time

o Cannot be used for rare disease

Retrospective cohort studies

More efficient; faster, cheaper, less

man power needed because data has

already been collected

o Range of possible risk factors is

narrower than prospective

design

o Cannot examine patient

characteristics not available in

the data set used

o Measurement may not be

standardized

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WHAT TO LOOK FOR IN COHORT STUDIES?

Who is at risk?

All participants (both exposed and unexposed) in a cohort study must be at risk of

developing the outcome. For example, since women who have had a tubal sterilization

operation have almost no risk of salpingitis, they should not be included in cohort studies

of pelvic inflammatory disease.

Who is exposed?

Cohort studies need a clear, unambiguous definition of the exposure at the outset. This

definition sometimes involves quantifying the exposure by degree, rather than just yes or

no. For example, the minimum exposure might have to be 14 cigarettes per day or less,

or 3–6 months of steroid use.

Who is an appropriate control?

The key notion is that controls (the unexposed) should be similar to the exposed in all

important respects, except for the lack of exposure. If so, the unexposed group will reveal

the background rate of the outcome in the community. The unexposed group can come

from either internal (persons from the same time and place, such as a hospital ward) or

external sources. Internal comparisons are most desirable.

Have outcomes been assessed equally?

Outcomes must be defined in advance, and they should be clear, specific, and

measurable. Identification of outcomes should be comparable in every way for the

exposed and unexposed to avoid information bias. Keeping those who judge outcomes

unaware of the exposure status of participants (blinding) in a cohort study is important for

subjective outcomes, such as pain or erythema.

By contrast, with objective outcome measures, such as death, blinding the exposure

status is less important.

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Have losses been minimized?

Although loss of participants damages the power and precision of a study, differential loss

to follow-up is more threatening. If the likelihood of drop out is related both to exposure

and outcome, then bias can result. For example, some participants given a new antibiotic

might have such poor outcomes that they are unable to complete questionnaires or to

return for examination. Their disappearance from the cohort would make the new antibiotic

look better than it is. The best way of dealing with loss to follow-up is to avoid it. For

example, restrict participation to only those judged likely to complete the study.

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WAY TO EXPRESS AND COMPARE RISK

A cohort study is useful for estimating the risk of disease. Absolute risk is the probability

that people who are exposed to certain “risk factors” will subsequently develop a

particular disease more often than similar people who are not exposed. Its value is the

same as that for incidence and the terms are often used interchangeably. Table 3

demonstrates ways to express and compare risk in a cohort study.

Table 3. Ways to express and compare risk

Expression Question Definition

Absolute risk What is the incidence of disease in a

group initially free of the condition?

I = #new case

#People in group

Attributable risk

(Risk difference)

What is the incidence of disease

attributable to exposure?

AR = IE+-IE-

Relative risk

(Risk ratio)

How many times more likely are exposed

persons to become diseased, relative to

nonexposed persons?

RR = IE+/ IE-

Population-

attributable risk

What is the incidence of disease in a

population, associated with the

prevalence of a risk factor?

ARp = AR x P

(P=prevalence of

exposure)

Population-

attributable fraction

What fraction of the disease in a

population is attributable to exposure to a

risk a risk factor?

AFp = ARp/IT

(IT = Total incidence of

disease in a population)

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HOW TO CALCULATE THE RISKS?

Formulas and examples for calculating risks in cohort studies have been demonstrated in

Figure 2.

Figure 2. Example for risk calculation 1

Exposure

Disease No disease

Total Stone CKD No CKD

Total

+ a b a+b Yes 80 10 90

- c d c+d NO 20 90 110

a+c b+d n 100 100 200

Term General Example Question?

Risk a/(a+b)

Or

c/(c+d)

80/90

Or

20/110

What is the incidence

of disease in a group

initially free of the condition?

Relative risk a/(a+b) c/(c+d)

80/90 20/110

= 5

How many times more

likely are exposed

persons to become

disease, relative to nonexposed persons?

Way to express and compare risk

Figure 3. Example for risk calculation 2

Exposure

Disease No disease

Total Stone CKD No CKD

Total

+ a b a+b Yes 80 10 90

- c d c+d NO 20 90 110

a+c b+d n 100 100 200

Term General Example Definition

Attributable risk (AR)

a/(a+b) –c/(c+d)

80/90 – 20/110

= 0.7

The incidence of

disease attributable to exposure

Population

attributable

risk

PAR= ARxPEX

AR x (a+b)/n

0.7 x 90/200

= 0.32

The incidence of

disease in a population

is associated with the

occurrence of a risk factor

Way to express and compare risk

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CONFOUNDING

A confounding factor is one that is:

1. Associated with exposure and its distribution between exposure and nonexposure

is not similar

2. Associated with disease

3. Not part of the causal chain from exposure to disease

Mostly risk studies are conducted by observational studies which cannot threaten the

internal validity by confounding factors. To determine whether a factor is independently

related to risk, we have to control the potential confounders. There are several possible

ways of controlling for the different confounders between groups.

Table 4. Methods for controlling confounding

Method Description Phase of study

Design Analysis

Randomization Assign patients to groups in a way that

gives each patient an equal chance of

allocating into one or the other group

+

Restriction Limit the range of characteristics of

patients in the study

+

Matching

e.g. propensity

score matching

For each patients in one group, select

one or more patients with the same

characteristics for a comparison group

+ +

Stratification Compare rates within subgroups (strata)

with otherwise similar probability of the

outcome

+

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Simple adjustment

(Standardization)

Mathematically adjust crude rates for one

or a few characteristics, so that equal

weight is given to strata of similar risk

(commonly used for a single variable

adjustment)

+

Multivariable

adjustment

Adjust for differences in a large number

of factors related to outcome, using

mathematical modeling technique

+

SUMMARY

Cohort studies are common in medical research. Like other research designs, they have

both advantages and disadvantages. Readers should make sure that investigators

provide clear, measurable definitions of exposures and outcomes. The unexposed group

should resemble the exposed group in all important respects, and determination of

outcomes should be objective and, whenever possible, blinded. The ways to express risk

is usually provided as rates, or relative risks. Reports of cohort studies should identify and

describe the potential effect of biases. Importantly, investigators should measure and

control for potential confounding factors.