in diagnosing the condition. For COVID-19, the polymerase chain reaction (PCR) test is considered a

gold standard test because of its high level of accuracy. But gold standard diagnostic procedures (like

PCR tests) can be time-consuming and expensive, and in the case of invasive procedures like biopsies,

they may be very unpleasant for the patient. Therefore, quick, inexpensive, and relatively noninvasive

screening tests are very valuable, even if they are not perfectly accurate. They just need to be accurate

enough to help filter in the best candidates for a gold standard diagnostic test.

Most screening tests produce some false positive results, which is when the result of the test is

positive, but the patient is actually negative for the condition. Screening tests also produce some false

negative results, where the result is negative in patients where the condition is present. Because of

this, it is important to know false positive rates, false negative rates, and other features of screening

tests to consider their level of accuracy in your interpretation of their results.

You usually evaluate a new, experimental screening test for a particular medical condition by

administering the new test to a group of participants. These participants include some who have the

condition and some who do not. For all the participants in the study, their status with respect to the

particular medical condition has been determined by the gold standard method, and you are seeing how

well your new, experimental screening test compares. You can then cross-tabulate the new screening

test results against the gold standard results representing the true condition in the participants. You

would create a fourfold table in a framework as shown in Figure 13-3.

© John Wiley & Sons, Inc.

FIGURE 13-3: This is how data are summarized when evaluating a proposed new diagnostic screening test.

Imagine that you are conducting a study at a primary care clinic. In the study, you administer a newly

developed home pregnancy test to 100 women who come to a primary care appointment suspecting that

they may be pregnant. This is convenience sampling from a population defined as “all women who

think they may be pregnant,” which is the population to whom a home pregnancy test would be

marketed. At the appointment, all the participants would be given the gold standard pregnancy test, so

by the end of the appointment, you would know their true pregnancy status according to the gold

standard, as well as what your new home pregnancy test result said. Your results would next be cross-

tabulated according to the framework shown in Figure 13-4.