94 PART 2 Examining Tools and Processes

discordant cells, where the exposure and outcome do not agree, is b, which repre-

sents the count of those positive for the exposure but negative for the outcome,

and c, which represents the count of those negative for the exposure but positive

for the outcome.

The 2x2 table shown in Figure 7-4 is generic — meaning it can be filled in with

data from a cross-sectional study, a case-control study, a cohort study, or even a

clinical trial (if you replace the E+ and E– entries with intervention group assign-

ment). How the results are interpreted from the 2x2 table depend upon the under-

lying study design. In the case of a cross-sectional study, an odds ratio (OR) could

be calculated to quantify the strength of association between the exposure and

outcome (see Chapter 14). However, any results coming from a 2x2 table do not

control for confounding, which is a bias introduced by a nuisance variable associ-

ated with the exposure and the outcome, but not on the causal pathway between

the exposure and outcome (more on confounding in Chapter 20).

Imagine that you were examining the cross-sectional association between having

the exposure of obesity (yes/no), and having the outcome of HTN (yes/no). House-

hold income may be a confounding variable, because lower income levels are

associated with barriers to access to high-quality nutrition that could prevent

both obesity and HTN. However, in a bivariate analysis like is done in a 2x2 table,

there is no ability to control for confounding. To do that, you need to use a regres-

sion model like the ones described in Chapters 15 through 23.

So how would you use a 2x2 table for a case-control study on a statistically rare

condition like liver cancer? Suppose that patients thought to have liver cancer are

referred to a cancer center to undergo biopsies. Those with biopsies that are posi-

tive for liver cancer are placed in a registry. Suppose that in 2023 there were

30 cases of liver cancer found at this center that were placed in the registry. This

would be a case series. Imagine that you had a hypothesis — that high levels of

alcohol intake may have caused the liver cancer. You could interview the cases to

determine their exposure status, or level of alcohol intake before they were diag-

nosed with liver cancer. Imagine that 10 of the 30 reported high alcohol intake.

You will see that as some evidence for your hypothesis.

FIGURE 7-4:

2x2 table cells.

© John Wiley & Sons, Inc.