1. COHORT STUDIES

2. Overview
Definition: A study in which two or more groups of people that are free of disease and that differ according to the extent of exposure (e.g. exposed and unexposed) are compared with respect to disease incidence
Cohort studies are the observational equivalent of experimental studies but the researcher cannot allocate exposure; he must locate a natural experiment to observe the relationship between the exposure and disease

3. Example: Ranch Hand Study
Exposed group: 1,264 Air Force servicemen who sprayed agent orange during Vietnam War,
Unexposed group: 1,264 Air Force servicemen who flew other missions during Vietnam War
Outcomes of interest: cancer, post traumatic stress, adverse pregnancy outcomes etc.
Principle: If Agent Orange is not associated with the outcomes under study, then the outcome rates will be the same in both groups

4. Principles of Experimental Studies Applied to Observational Cohort Studies
Randomization to ensure comparable groups
Select similar groups, adjust for differences
Use placebo in order to reduce bias.
Blinding to avoid bias in outcome ascertainment
Need comparable follow-up in both groups
Blind investigators conducting follow-up and determining out-comes

5. Timing of cohort studies
Retrospective: both exposure and disease have occurred at start of study
Exposure Disease
*Study starts
Prospective: exposure has (probably) occurred, disease has not occurred
Exposure Disease

6. How do you choose between a retrospective vs. prospective design?
Cheaper, faster
Efficient with diseases with long latent period
Exposure data may be inadequate
Outcome data may be inadequate
Prospective:
More expensive, time consuming
Not efficient for diseases with long latent periods
Better exposure, confounder and outcome data
Less vulnerable to bias

7. Issues in Design of Cohort Studies
Selection of study population
Choice depends upon hypothesis under study and feasibility considerations
Key Issue – you need enough events to make the study work. If events are rare it is not feasible.
Low statistical power – lack ability to detect a difference

8. Issues in Design of Cohort Studies
Examples of study populations:
Occupational groups
Groups with a clinical disease
Groups undergoing particular medical treatment
Groups with unusual dietary or life style factors
Professional groups (nurses, doctors)
Students or alumni of colleges
Geographically defined areas – Cardiovascular cohort studies (e.g. Framingham, ARIC, CHS)

9. Issues in Design of Cohort Studies
For rare exposures, you need to assemble special cohorts.
Occupational Exposures
Particular Diets – Mormons, don’t drink, smoke
Radiation exposure – Japan or Chernobyl
Example of special cohort study
Rubber workers in Akron, Ohio
Exposure: industrial solvent
Outcomes: cancer

10. Issues in Design of Cohort Studies
If exposure is common, you may want to use a general cohort that will facilitate accurate and complete ascertainment of data (Doctors, nurses, well-defined communities)
Example of general cohort study
Framingham Study, ARIC
Exposures: smoking, hypertension, family history
Outcomes: heart disease, stroke, gout, etc.

11. Selection of Comparison (Unexposed) Group
Principle: You want the comparison (unexposed) group to be as similar as possible to the exposed group with respect to all other factors except the exposure.
If the exposure has no effect on disease occurrence, then the rate of disease in the exposed and comparison groups will be the same.

12. Selection of Comparison (Unexposed) Group
Counterfactual ideal: The ideal comparison group consists of exactly the same individuals in the exposed group had they not been exposed.
Not Possible

13. Three possible sources of comparison group
1. Internal comparison: unexposed members of same cohort
Ex: Framingham study, Ranch Hand study
2. Comparison cohort: a cohort who is not exposed from another similar population
Ex: Asbestos textile vs. cotton textile workers
3. General population data: Use pre-existing data from the general population as the basis for comparison. General population is commonly used in occupational studies. Usually find healthy worker effect
Ex. A study of asbestos and lung cancer with U.S. male population as the comparison group
What is the health worker effect?
Which of the three comparison groups is best?

14. General population data: Standardized Mortality Ratios
SMR – Ratio of observed deaths/expected deaths
Expected Deaths Come from age-gender specific rates from the general population. Or a source population.
Death rate for age = 1/100 person years in the general population
In a town with 3000 people age 50-54
Expected number of deaths in one year: 3,000*(1/100)= 30
Observed = 40
SMR = 40/30=1.33
Ratio – so the interpretation is the same as an incident rate ratio (IRR). Mortality rate is 1.33 times higher in exposed population than in the general population.

15. Sources of exposure information
Pre-existing records
Electronic medical records; occupational records
inexpensive, data recorded before disease occurrence but level of detail may be inadequate.
records may be missing
usually don't contain information on confounders
could be systematic bias in quality of data
Certain sub-groups may be followed more closely
Mexican Americans may move back to Mexico when they become sick.
If certain groups are pre-conceived to have higher rates of disease it may be reflected at the population level.
White males  heart attacks

16. Sources of Exposure Information
Questionnaires, interviews
good for information not routinely recorded but have potential for recall bias
Do you think it is easy to collect information on basic behaviors?
Diet
Physical Activity; sedentary behavior
Alcohol consumption; smoking history
Direct physical exams, tests, environmental monitoring may be needed to ascertain certain exposures.
Blood tests
DEXA, MRI and many other tests

17. Issues in Design of Cohort Studies
Sources of outcome information
Mailed questionnaires, telephone interviews, clinical exams
Death certificates
Physician, hospital, health plan records
Questionnaires (verify by records)
Medical exams
Goal is to obtain complete follow-up information on all subjects regardless of exposure status.
You can use blinding (like an experimental study) to ensure that there is comparable ascertainment of the outcome in both groups.

18. Approaches to Follow-Up
In any cohort study, the ascertainment of outcome data involves tracing or following all subjects from exposure into the future.
Resources utilized to conduct follow-up
town lists, web-based searches
birth, death, marriage records, driver's license lists
credit card company information
physician and hospital records; relatives, friends
This is a time consuming process but high losses to follow-up raise doubts about validity of study

19. Analysis of Cohort Studies
Basic analysis involves calculation of incidence of disease among exposed and unexposed groups.
Depending on available data calculate
cumulative incidence -- risk
incidence rates -- rates
Recall set up of 2 x 2 tables.

20. Analysis of Cohort Studies
Breast Cancer Cases
Woman-Years of follow-up
Exposed 41
28,001
Unexposed 15
19,025
Total 56
47,036
IR1 = 41/28,011 = 1.5/1,000 woman-years
IR0 = 15/19,025 = 0.8/1,000 woman-years
RR = IR1/IR0 = 1.9
Interpretation: Women exposed to fluoroscopies had 1.9 times the risk of breast cancer compared to unexposed women.

21. Strengths of Cohort Studies
Efficient for rare exposures
If retrospective data is available work well for diseases with long induction and latent period
Can evaluate multiple effects of an exposure
If prospective, good information on exposures, less vulnerable to bias, and clear temporal relationship between exposure and disease

22. Weaknesses of Cohort Studies
Inefficient for rare outcomes
If retrospective, poor information on exposure and other key variables, more vulnerable to bias
If prospective, expensive and time consuming, inefficient for diseases with long induction and latent period, or low incidence rates
Keep these strengths and weaknesses in mind for comparison with case-control studies

23. Question
Is a cohort study well suited for each of the following scenarios?
When little is known about a rare exposure.
When little is known about a rare disease.
When the study population is difficult to follow.
When you want to learn about multiple effects of an exposure.