Lecture 8 1 and 2

•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

1. Randomization of treatment so groups are comparable on known and unknown confounders.  Can't randomize in an observational study so select a comparison group as alike as possible to the exposed group

2. Use placebo in order to reduce bias. Can’t use placebo in observational studies so you must make the groupsas comparable as possible. 

3. Blinding to avoid bias in outcome ascertainment.   

In a cohort study, it is crucial to have high follow-up rates and comparable ascertainment of outcomes in the exposed and comparison groups.     

You can  blind the investigators conducting follow up and confirming the outcomes.

•Retrospective: both exposure and disease have occurred at start of study

Exposure---------Disease                                                          *Study starts after disease

•Prospective: exposure has (probably) occurred, disease has not occurred    Exposure----------------------Disease     *Study starts at exposure

•Ambi-directional: elements of both

• Retrospective:
• •Cheaper, faster
• •Efficient with diseases with long latent period
• •Exposure data may be inadequate

• Prospective:
• •More expensive, time consuming
• •Not efficient for diseases with long latent periods
• •Better exposure and confounder data
• •Less vulnerable to bias

• Occupational groups
• 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 (e.g. Framingham)

hypothesis under study and feasibility considerations

True

• False
• 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)

Selection of comparison (unexposed) groupPrinciple:  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.

Counterfactual ideal: The ideal comparison group consists of exactly the same individuals in the exposed group had they not been exposed. Since it is impossible for the same person to be exposed and unexposed simultaneously, epidemiologists must select different sets of people who are as similar as possible.

• 1. Internal comparison: unexposed members of same cohort
• Ex. Framinghame 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

Pre-existing records - inexpensive, data recorded before disease occurrence but level of detail may be inadequate.  Also, records may be missing, usually don't contain information on confounders  

Questionnaires, interviews:  good for information not routinely recorded but have potential for recall bias

Direct physical exams, tests, environmental monitoring may be needed to ascertain certain exposures.

• •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.

In any cohort study, the ascertainment of outcome data involves tracingor following all subjects from exposure into the future

Resources utilized to conduct follow-up: town lists, Polk directories, telephone books; birth, death, marriage records; driver's license lists, physician and hospital records; relatives, friends.

This is a time consuming process but high losses to follow-up raise doubts about validity of study

•Basic analysis involves calculation of incidence of disease among exposed and unexposed groups.

•Depending on available data, you can calculate cumulative incidence or incidence rates.

•Recall set up of 2 x 2 tables.

•                       ill      well    
• exposed           A        B   
• non-exposed    C        D

• •Rate ratio = a / (a + b)        
•                     c / (c + d) 
•       
• attack rate of exposed
• attack rate of non-exposed

• Rate of illness in the exposed minus the rate of illness in the unexposed 
•    
• Ire – Irue = Rate Difference (RD)
• Ire = Incidence rate exposed
• Irue = Incident rate in Unexposed

RD also called  “Attributable Risk”

•If retrospective, efficient for rare exposures, 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 

•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

•Keep these strengths and weaknesses in mind for comparison with case-control studies

• •Selection Bias
• –“healthy Worker Effect”
• –Loss to follow up

•Confounding

•Missclassification

•Healthy Worker Effect occurs in cohort studies when workers represent the exposed group and a sample from the general population represents the unexposed group.  This is because on average workers tend to be healthier than the general population

Loss to follow up is the biggest concern in a cohort study.  This is where the researcher losses contact with study participants resulting in the loss of data from these individuals. There can be many reasons for individuals to drop out of a study.  As a prospective cohort goes on, the risk of attrition increases.

Confounding can influence associations in any study design.  It’s where another factor is associated with both the exposure and the outcome under study. If not controlled for this third confounding factor will skew the study results resulting in erroneous conclusions.

Misclassification of either the exposure or the disease can occur. If misclassification of the outcome is related to the exposure then misclassification is non-random, differential, and the strength of the rate ratio or risk ratio is distorted. If misclassification of the outcome is not related to the exposure then misclassification is non-differential, random.