COHORT STUDIES

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, 1962-1971 • 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. • Select similar groups, adjust for differences • 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 *Study starts

6. How do you choose between a retrospective vs. prospective design? Retrospective: • 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 50-54 = 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 • 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.