Most-used COVID-19 test may miss 1 in 5 infections

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The majority test for the novel coronavirus — a back of nose or throat swab using the RT-PCR laboratory procedure for genetic analysis — may produce 1 in 5 false negatives, according to a Johns Hopkins Medicine study.

Medical News Today reports that this common analysis uses a laboratory procedure called reverse transcriptase-polymerase chain reaction (RT-PCR), which converts genetic material from the virus (RNA) to DNA before amplifying it. It allows the detection of genetic material specific to the SARS-CoV-2 virus, confirming a diagnosis of the associated disease, COVID-19.

Although serological, or antibody, tests are also available, these typically serve to confirm a past infection in people who have since recovered from COVID-19, rather than to detect an active infection.

There has been much discussion about the accuracy of antibody tests, with manufacturers even withdrawing some such tests due to concerns about their reliability.

According to the report, a new analysis suggests that the accuracy of RT-PCR could also be under question. Scientists from Johns Hopkins Medicine in Baltimore, Maryland, have shown that as many as 1 in 5 RT-PCR tests for the coronavirus may produce false negatives, incorrectly informing a patient that they do not have a SARS-CoV-2 infection when they actually do.

Since the beginning of the coronavirus outbreak, RT-PCR has had routine use as a diagnostic tool. However, the report says, the accuracy of the technique in detecting SARS-CoV-2, and particularly how this relates to the length of time since the infection, is unclear. Understanding the accuracy of the test is vital because the results frequently contribute to important decisions, such as whether to allow healthcare workers to return to work.

Incorrectly telling a person working on the frontline that they do not have a SARS-CoV-2 infection and can return to work could lead to further spread of the virus. Additionally, the information from testing also informs the decisions of governments regarding the lifting of restrictions.

To estimate the rate of false-negative tests for the coronavirus, the researchers behind this study searched the literature on the topic. They included studies that used an RT-PCR-based test to detect SARS-CoV-2 in samples collected from the upper respiratory tract and that also reported the time since symptom onset or exposure to the virus. They identified seven studies in total, which included data from 1,330 patient samples, including inpatients (people in the hospital) and those managing their symptoms at home.

Their analysis showed that the likelihood of a false-negative result varied depending on the time since infection. It appears that the virus is not detectable immediately after infection. On the first day of infection, the probability of missing a diagnosis, i.e., a false-negative result, was 100%.

At day 4 after exposure to the virus, the probability of a false-negative result seems to reduce to 67%. By day 8, it decreases to 20%, beginning to increase again afterward. By 3 weeks post-exposure, the chance of a false negative result reaches 66%, the authors estimate.

The results indicate that the virus is difficult to detect by RT-PCR in the days immediately following infection, suggesting that this testing route offers limited value during this period (3–5 days post-infection).

The authors recommend against making major decisions, such as removing personal protective equipment (PPE) or ending quarantine, based on results obtained in this period. Similarly, the test offers limited value a long time after the initial exposure.

According to Medical News Today, they say that 8 days following exposure, which is roughly equivalent to 3 days following the onset of symptoms, is the optimal time for testing. At this time, the risk of obtaining a false-negative result is at its lowest, although there is still a 1 in 5 chance of obtaining such a result.

The authors say that the reasons for such a high rate of false negatives, beyond technique-associated error, include differences in the amount of viral genetic material in people’s samples and differences in sample collection techniques.

On the basis of their findings, the authors say that it is important to exercise caution when interpreting the results of RT-PCR tests for SARS-CoV-2, particularly if the test took place early on in the course of infection.

If an individual has symptoms consistent with COVID-19 but tests negative, the authors suggest not ruling out infection and carefully considering the “clinical and epidemiologic situation.” They also say that a combination of antibody testing and PCR-based methods could be useful for patients who no longer have symptoms. “Clinicians should consider waiting 1 to 3 days after symptom onset to minimize the probability of a false-negative result.”

The authors do note some limitations to their study, including the fact that the studies that they analysed had different designs. They say that further studies are necessary to characterize the performance of RT-PCR tests for SARS-CoV-2 better and to identify alternative, more sensitive approaches.

Abstract
Background: Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on reverse transcriptase polymerase chain reaction (RT-PCR) are being used to “rule out” infection among high-risk persons, such as exposed inpatients and health care workers. It is critical to understand how the predictive value of the test varies with time from exposure and symptom onset to avoid being falsely reassured by negative test results.
Objective: To estimate the false-negative rate by day since infection.
Design: Literature review and pooled analysis.
Setting: 7 previously published studies providing data on RT-PCR performance by time since symptom onset or SARS-CoV-2 exposure using samples from the upper respiratory tract (n = 1330).
Patients: A mix of inpatients and outpatients with SARS-CoV-2 infection.
Measurements: A Bayesian hierarchical model was fitted to estimate the false-negative rate by day since exposure and symptom onset.
Results: Over the 4 days of infection before the typical time of symptom onset (day 5), the probability of a false-negative result in an infected person decreases from 100% (95% CI, 100% to 100%) on day 1 to 67% (CI, 27% to 94%) on day 4. On the day of symptom onset, the median false-negative rate was 38% (CI, 18% to 65%). This decreased to 20% (CI, 12% to 30%) on day 8 (3 days after symptom onset) then began to increase again, from 21% (CI, 13% to 31%) on day 9 to 66% (CI, 54% to 77%) on day 21.
Limitation: Imprecise estimates due to heterogeneity in the design of studies on which results were based.
Conclusion: Care must be taken in interpreting RT-PCR tests for SARS-CoV-2 infection—particularly early in the course of infection—when using these results as a basis for removing precautions intended to prevent onward transmission. If clinical suspicion is high, infection should not be ruled out on the basis of RT-PCR alone, and the clinical and epidemiologic situation should be carefully considered.
Primary Funding Source: National Institute of Allergy and Infectious Diseases, Johns Hopkins Health System, and US Centres for Disease Control and Prevention.

Authors
Lauren M Kucirka, Stephen A Lauer, Oliver Laeyendecker, Denali Boon, Justin Lessler

 

Full Medical News Today report

 

Annals of Internal Medicine abstract

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