SeriesCohort studies: marching towards outcomes
Section snippets
Data collection: forwards and backwards
A cohort study follows-up two or more groups from exposure to outcome. In its simplest form, a cohort study compares the experience of a group exposed to some factor with another group not exposed to the factor. If the former group has a higher or lower frequency of an outcome than the unexposed, then an association between exposure and outcome is evident.
The defining characteristic of all cohort studies is that they track people forward in time from exposure to outcome. Researchers doing this
Advantages of cohort studies
Cohort studies have many appealing features. They are the best way to ascertain both the incidence and natural history of a disorder.6 The temporal sequence between putative cause and outcome is usually clear: the exposed and unexposed can often be seen to be free of the outcome at the outset. By contrast, this chicken-egg question often frustrates cross-sectional and case-control studies. For example, in a case-control study, patients with chronic widespread pain were more likely to have
Disadvantages of cohort studies
Cohort studies have important limitations too. Selection bias is built into cohort studies. For example, in a cohort study investigating effects of jogging on cardiovascular disease, those who choose to jog probably differ in other important ways (such as diet and smoking) from those who do not exercise.11 In theory, both groups should be the same in all important respects, except for the exposure of interest (jogging), but this seldom occurs. The cohort design is not optimum for rare
Who is at risk?
All participants (both exposed and unexposed) in a cohort study must be at risk of developing the outcome.6 For example, since women who have had a tubal sterilisation operation have almost no risk of salpingitis,17 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
Have losses been minimised?
Although loss of participants damages the power and precision of a study, differential loss to follow-up is more sinister. Bail-outs are not random events. If the likelihood of bailing out is related both to exposure and outcome, then bias can result.25 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.26 Their disappearance from the cohort would make the new antibiotic look better
Reporting cohort studies
Many researchers who do cohort studies report their findings in an unsatisfactory way (panel 2).27 An investigator's first challenge is to convince the editor (then readers) that the exposed and unexposed groups were indeed similar in all important respects, except for the exposure. The first table in reports of cohort studies customarily provides demographic and other prognostic factors for both groups with hypothesis testing (p values) to show the likelihood that observed differences could be
Before-after studies
Before-after studies (time series) have important limitations. Here, an investigator takes a measurement, exposes participants to an intervention (often a drug), repeats the measurements, then compares them. First, regression to the mean is often ignored. If admission to the cohort includes extreme measurements,30 such as high laboratory values, then lower mean values will arise at follow-up, irrespective of treatment.31 Second, secular trends, such as seasonal changes in the frequency of
Conclusion
Cohort studies are common in medical research. Like other research designs, they entail important trade-offs. Readers should make sure that investigators provide clear, specific, and 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. Results for dichotomous outcomes should be provided as rates, relative risks, and confidence
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