epidemiology

Cohort Studies

HESC 401 Epidemiology

� At the beginning of chapter 8, alpha and p-values are covered, but we haven’t discussed this yet. We will cover this when we review relative risk and odds ratios and other statistical concepts.

Objectives � Describe the basic design of a cohort study

� Begin to understand a 2 x 2 table (table 9-1) and 9-2.

� Identify differences and similarities between cohort studies and randomized trials

� Describe the different approaches to select groups in cohort studies and any problems associated with them

� Identify and describe prospective and retrospective cohort studies and their similarities and differences

� Describe the Framingham cohort study

� Identify and explain biases associated with cohort studies

Design of a Cohort Study

� Two groups are selected by an investigator: exposed and

non-exposed.

� The two groups are then followed up to compare the

incidence of disease.

� If a positive association exists between the exposure and

the disease, it would be expected the incidence in the

exposed group would be greater than the incidence in the

non-exposed group.

� Comparing the incidence of exposed and non-exposed

persons is the hallmark of this design.

Incidence of disease � The key aspect of a cohort study compared with a

case/control and cross-sectional study is that we can calculate the incidence of disease. Because we are following people in time, we can measure who has “newly” developed disease and hence calculate the incidence.

Then Follow to See Whether

Disease Develops

Disease Does Not Develop

Totals Incidence Rates of

Disease

a b a + b

Exposed

Not exposed d d

c + d

The 2 x 2 table shown below and in table 9-1, illustrates the important point that

cohort studies can measure/estimate the incidence of disease in the exposed and

unexposed (the last column). Later in subsequent chapters, this will be important

when calculating the “risk” of disease in those exposed compared with those

not exposed.

Then Follow to See Whether

CHD Develops CHD Develops CHD Does Not Develop

Totals

Incidence

per 1,000

per Year

84 2,916 3,000 28.0 Smoke cigarettes

Do not smoke cigarettes 87 4,913 5,000 17.4

Table 9-2 below and from the book provides an excellent example of calculating

incidence for those exposed compared with those not exposed. Incidence of

Disease in smokers is = new disease/ all those at risk in the exposed group

= 84/3000 = 28.0.

Figure 9-2: Cohort study design, including exposed and non- exposed groups. It is broken down further into groups that develop the disease and those who do not develop the disease.

Comparing Cohort Studies with

Randomized Trials

� Both studies compare exposed and non-exposed groups.

� In randomized trials, for ethical reasons, the “exposure” is

a treatment or preventive measure.

� In cohort studies, the “exposure” is often to a possibly

toxic or carcinogenic agent.

� In both studies, an exposed group is compared with a non-

exposed group or with a group with another exposure.

What is the Main Difference

Between the Two Studies?

� In a randomized trial, you are actually conducting an

“experiment” and testing whether a drug or treatment has

an effect.

� Where as in a cohort study, there is no randomization, but

instead you are following people in time to see whether if

they were exposed or not exposed to something, such as

cigarette smoke, bad diet, etc has an affect on disease.

� The following slide displays the main difference between

the two studies.

Figure 9-3: The selection of study groups in experimental and observational epidemiologic studies.

Selecting Study Populations

� There are two ways to develop exposed and non-exposed

groups in cohort studies.

� 1) Create a study population by selecting groups on the

basis of whether or not they were exposed. This design is

shown on the next slide.

Figure 9-4: Design of a cohort study beginning with exposed and non-exposed groups.

Selecting Study Populations (cont’d)

� 2) Select a defined population before any members

become exposed or before the exposure is identified.

Select on the basis of some factor not related to exposure,

and then take histories or blood tests of the entire

population.

� Use the results of the histories or tests to separate the

population into exposed and non-exposed groups.

Figure 9-5: Design of a cohort study starting with a defined population.

Issue with Using Second Selection

Approach

� Cohort studies often require a long follow-up period,

lasting until enough outcomes have occurred.

� When the second approach is used, the exposure of

interest may not occur for some time, even for many years

after the population has been identified.

Prospective Cohort Study

� Also called a concurrent cohort or longitudinal cohort.

� The study is concurrent because the investigator identifies

the original population at the beginning of the study and

follows the subjects concurrently through calendar time

until the point at which the disease does or does not

develop.

� Figure 9-6 on the next slide shows a hypothetical

prospective cohort study.

Figure 9-6: This shows the time frame for a hypothetical prospective cohort study that began in 2008. Over the course of the next 20 years, the investigator will follow the subjects in order to observe any outcomes.

Problems with Prospective Cohort

Studies � 1) This study has a long follow-up period. The study on

the previous slide shows that it will take 20 years to

complete.

� 2) Funding is generally limited to 3 to 5 years, and would

not last the entire duration of the study.

� 3) There is a risk that the subjects will outlive the

investigator, or the investigator may not survive to the end

of the study.

Retrospective Cohort Study

� Also called a historical cohort study or a nonconcurrent

prospective study.

� It is the same as a prospective cohort study in that it is still

comparing exposed and non-exposed groups.

� In the retrospective study, we are using historical data

from the past so that we can telescope the frame of

calendar time for the study and obtain our results sooner.

� The study is beginning with a pre-existing population to

reduce the duration of the study.

Main Similarity and Difference Between

Prospective and Retrospective Studies

� Similarity: They are identical- both are comparing exposed and non-exposed populations.

� Difference: Calendar time

Figure 9-8: Time frames for hypothetical prospective and retrospective cohort studies begun in 2008.

Example of prospective and

retrospective studies � Based on the diagram below, for a prospective study, let’s say in 2008 we

identified a group of students and followed them to 2018 where we surveyed them on their smoking (exposure) and then we followed them until 2028 to see whether those that were exposed or not exposed got lung cancer.

� In a retrospective study, we identified a group of people who had lung cancer and didn’t have lung cancer in 2008, and then also found out that they were surveyed at an earlier time (1998) on smoking exposure and began to be observed/followed in 1988.

The Framingham Study

� The Framingham Study of cardiovascular disease began in

1948.

� Residents who were considered eligible for the study were

between 30 and 62 years of age.

� There were 5,127 men and women between 30 and 62

years of age at the beginning of the study and were free of

cardiovascular disease at that time.

The Framingham Study (cont’d)

� Many “exposures” were defined for this study. They

included smoking, obesity, elevated blood pressure,

elevated cholesterol levels, low levels of physical activity,

and other factors.

� New coronary events were identified by examining the

study population every 2 years and by daily surveillance

of hospitalizations at the only hospital in Framingham.

� The second approach for selecting a study population was

used for this study.

The Framingham Study (cont’d)

� A defined population was selected on the basis of location of residence or other factors not related to exposures.

� The population of Framingham was observed over time to determine which individuals developed or already had the “exposure(s)” of interest, as well as to determine later on who developed the cardiovascular outcomes of interest.

� This approach allowed the investigators to examine the roles of multiple “exposures”, as well as the interactions among the exposures.

Potential Biases in Cohort Studies

� 1) Bias in the assessment of the outcome: According to Gordis,

“IF the person who decides whether disease has developed in

each subject also knows whether that subject was exposed, and

if that person is aware of the hypothesis being tested, that

person’s judgment as to whether the disease developed may be

biased by that knowledge.”

� 2) Information bias: If the method of collecting the data is

different for the exposed and unexposed, the information on

exposure might be different for exposed persons than for non-

exposed persons, then a significant bias can be introduced. It is

likely to occur in historical cohort studies since information is

obtained from past records.

Potential Biases in Cohort Studies � 3) Biases from non-response and losses to follow-up: non-

participation and non-response can introduce major biases that

can complicate interpretation of the study findings.

� For example, let’s say that you are studying a group of people

who worked in a factory and then followed this group to see

whether exposure to asbestos is associated with lung disease.

However, several of the workers dropped out of the study and

if the workers who dropped out were sicker and possibly

exposed to asbestos, then mostly the healthy group stayed in

the study and it may appear that there isn’t an association

between asbestos and lung disease.

� Also, if people with the disease are lost to follow-up,

incidence rates will be difficult to interpret for both groups.

� 4) Analytic bias: According to Gordis, “If the epidemiologists

and/or statisticians who analyze the data have strong

preconceptions, they may unintentionally include their biases

into the data analysis and the interpretation of the study

findings.”

� This could occur for any type of study design

When is a Cohort Study Warranted?

� Figure 9-11 on the next slide reviews the basic steps in a

cohort study.

� We begin with identifying an exposed group and an

unexposed group. (Part A)

� We then ascertain the incidence in both the exposed and

non-exposed groups. (Part B)

� If the exposure is associated with disease, we would

expect to find a greater incidence in the exposed group

than in the non-exposed group. (Part C)

Figure 9-11: The design of a cohort study. Part A starts with the exposed and non- exposed groups. In Part B, we are measuring the development of disease in both groups. Part C is the expected findings if the exposure is associated with disease.

What Can Make a Cohort Study

Impractical? � According to Gordis, “strong evidence does not exist

to justify mounting a large and expensive study for in- depth investigation of the role of a specific risk factor in the etiology of a disease.”

� There are generally no appropriate past records or other sources of data to conduct a retrospective cohort study.

� Many of the diseases that are of interest today occur at very low rates. Therefore, large cohorts must be enrolled in a study to ensure that enough cases develop by the end of the study to permit valid analysis.