participants for your statistics to work out. In the case of Figure 7-6, 210 exposed and 390 unexposed

participants were enrolled.

In cohort studies, all the participants are examined upon entering the study, and those with the outcome

are not allowed to participate. Therefore, at the beginning of the study, all 600 of the participants did

not have the outcome, which is HTN. A cohort study is essentially a series of cross-sectional studies

on the same cohort called waves. The first wave is baseline, when the participants enter the study (all

of whom do not have the outcome). Baseline values of important variables are measured (and criteria

about baseline values may be used to set inclusion criteria, such as minimum age for the study).

Subsequent waves of cross-sectional data collection take place at regular time intervals (such as every

year or every two years). Changes in measured baseline values are tracked over time, and subgroups

of the cohort are compared in terms of outcome status. Figure 7-6 shows the exposure status from

baseline, and the outcome status from the first wave.

Because the exposure is measured in a cohort study before any participants get the outcome, it

is considered the highest level of evidence among the observational study designs. It is far less

biased than the case-control study design. Several measures of relative risk can be used to

interpret a cohort study, including the OR, risk ratio, and incidence rate (see Chapter 14).

Advancing to the clinical trial stage

Higher up the pyramid of evidence shown in Figure 7-2 are experiments. Not all experiments are at

such a high level of evidence — only high-quality clinical trials. These are experiments, not

observational studies. This is where the researcher assigns the participants to engage in a particular

behavior or intervention during the study. There are different types of clinical trials as described in

Chapter 5; however, the highest-quality trials use both double-blinding and randomization. Double-

blinding is where both the researcher and the participant do not know whether the participant was

assigned to an active intervention (one being studied), or a control intervention. Randomization is

where participants are randomly assigned to groups (so there is no bias in selecting participants for

each group).

It is possible to use a 2x2 table to analyze the results of a high-quality clinical trial as long as

the rows are replaced with the intervention groups. You can report the same measure of relative

risk as for a cohort study; however, the difference is that the high-quality clinical trial would be

seen as having much less bias than the cohort study — and stronger causal evidence.

Reaching the top: Systematic reviews and meta-analyses

Imagine a scenario where a new drug for HTN was developed, and several clinical trials were

conducted to see whether this drug was better than the most popular current drug used for HTN. How

would we be able to know whether, on balance, the new drug was actually better when we have so

many different clinical trials on the same drug with different results?

We could ask a similar question about observational studies as well. Imagine that multiple case-

control studies were conducted to determine whether having liver cancer was associated with the