Potential for False Positive Results with Antigen Tests for Rapid Detection of SARS-CoV-2
It happens that RAT’s will give a false positive result. The U.S. Food and Drug Administration
(FDA) has been alerting clinical laboratory staff and health care providers that false positive
results can occur with antigen tests, including when users do not follow the instructions for
use of antigen tests for the rapid detection of SARS-CoV-2.
In this article we will summarize the highlights of this FDA article which is related to Rapid
Antigen Tests for home use as well. Most important is to read the user manual carefully
before using a RAT.
Main reasons for false positive, or false negative are:
• For example, the package insert for tests include instructions for handling of the test
cartridge/card, such as ensuring it is not stored open prior to use. If the test components are
not stored properly, this can affect the performance of the test.
• The package insert for tests also includes instructions about reading the test results,
including the appropriate time to read the results. Reading the test before or after the
specified time could result in false positive or false negative results.
• Be aware that processing multiple specimens in batch mode may make it more challenging
to ensure the correct incubation time for each specimen.
• Be careful to minimize the risks of cross-contamination
• Prevalence is a measure of disease that allows us to determine a person’s likelihood of
having a disease. Therefore, the number of prevalent cases is the total number of cases of
disease existing in a population. Remember that positive predictive value (PPV) varies with
disease prevalence when interpreting results from diagnostic tests. PPV is the percent of
positive test results that are true positives. As disease prevalence decreases, the percent of
test results that are false positives increase.
• For example, a test with 98% specificity would have a PPV of just over 80% in a population
with 10% prevalence, meaning 20 out of 100 positive results would be false positives.
The same test would only have a PPV of approximately 30% in a population with 1%
prevalence, meaning 70 out of 100 positive results would be false positives. This means that,
in a population with 1% prevalence, only 30% of individuals with positive test results actually
have the disease.
• At 0.1% prevalence, the PPV would only be 4%, meaning that 96 out of 100 positive results
would be false positives.