Comparison of diagnostic accuracy of rapid antigen tests for COVID-19 compared to the viral genetic test in adults: a systematic review and meta-analysis

Abstract

Objective: The objective of this review was to determine the diagnostic accuracy of the currently available and upcoming point-of-care rapid antigen tests (RATs) used in primary care settings relative to the viral genetic real-time reverse transcriptase polymerase chain reaction (RT-PCR) test as a reference for diagnosing COVID-19/SARS-CoV-2 in adults.

Introduction: Accurate COVID-19 point-of-care diagnostic tests are required for real-time identification of SARS-CoV-2 infection in individuals. Real-time RT-PCR is the accepted gold standard for diagnostic testing, requiring technical expertise and expensive equipment that are unavailable in most primary care locations. RATs are immunoassays that detect the presence of a specific viral protein, which implies a current infection with SARS-CoV-2. RATs are qualitative or semi-quantitative diagnostics that lack thresholds that provide a result within a short time frame, typically within the hour following sample collection. In this systematic review, we synthesized the current evidence regarding the accuracy of RATs for detecting SARS-CoV-2 compared with RT-PCR.

Inclusion criteria: Studies that included nonpregnant adults (18 years or older) with suspected SARS-CoV-2 infection, regardless of symptomology or disease severity, were included. The index test was any available SARS-CoV-2 point-of-care RAT. The reference test was any commercially distributed RT-PCR-based test that detects the RNA genome of SARS-CoV-2 and has been validated by an independent third party. Custom or in-house RT-PCR tests were also considered, with appropriate validation documentation. The diagnosis of interest was COVID-19 disease and SARS-CoV-2 infection. This review considered cross-sectional and cohort studies that examined the diagnostic accuracy of COVID-19/SARS-CoV-2 infection where the participants had both index and reference tests performed.

Methods: The keywords and index terms contained in relevant articles were used to develop a full search strategy for PubMed and adapted for Embase, Scopus, Qinsight, and the WHO COVID-19 databases. Studies published from November 2019 to July 12, 2022, were included, as SARS-CoV-2 emerged in late 2019 and is the cause of a continuing pandemic. Studies that met the inclusion criteria were critically appraised using QUADAS-2. Using a customized tool, data were extracted from included studies and were verified prior to analysis. The pooled sensitivity, specificity, positive predictive, and negative predictive values were calculated and presented with 95% CIs. When heterogeneity was observed, outlier analysis was conducted, and the results were generated by removing outliers.

Results: Meta-analysis was performed on 91 studies of 581 full-text articles retrieved that provided true-positive, true-negative, false-positive, and false-negative values. RATs can identify individuals who have COVID-19 with high reliability (positive predictive value 97.7%; negative predictive value 95.2%) when considering overall performance. However, the lower level of sensitivity (67.1%) suggests that negative test results likely need to be retested through an additional method.

Conclusions: Most reported RAT brands had only a few studies comparing their performance with RT-PCR. Overall, a positive RAT result is an excellent predictor of a positive diagnosis of COVID-19. We recommend that Roche's SARS-CoV-2 Rapid Antigen Test and Abbott's BinaxNOW tests be used in primary care settings, with the understanding that negative results need to be confirmed through RT-PCR. We recommend adherence to the STARD guidelines when reporting on diagnostic data.

Review registration: PROSPERO CRD42020224250.

Figure 1

Search results and study selection and inclusion process

Figure 2

Summary of risk of bias assessment of included studies. The percentage of included studies where the answer to each question from the QUADAS-2 tool25 was “yes” (green, no stripes), “no” (red, diagonal stripes), or “not clear” (yellow, vertical stripes) are shown. Questions that required a “yes” answer for the study to be included in the data extraction are not shown (#2, #3, #6, and #8).

Figure 3

Maps of study locations. The heatmaps show the geography of the studies included in this review, illustrating the global nature of COVID-19 rapid antigen tests. (A) The number of included studies from each country is shown by heatmap. (B–D) The number of included studies from each country with data collected during the dominance of the Ancestral (B), Alpha (C), and Delta (D) strains of SARS-CoV-2 are shown by heatmap. Gray indicates that no included studies came from that country.

Figure 4

Numbers of participants/samples per included study. Studies were grouped by the number of participants. The number of studies for each group is shown.

Figure 5

Diagnostic accuracy of COVID-19/SARS-CoV-2 infection—sensitivity forest plot for the overall cohort. The forest plot shows the sensitivities and 95% CIs reported for the STANARD Q COVID-19 Ag Test (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests (point-of-care SARS-CoV-2 rapid antigen tests) after outlier studies were removed. Pooled sensitivity and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled sensitivity and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.671 represents the pooled sensitivity value for all shown tests. Boxes represent the reported sensitivity, and solid horizontal lines represent the 95% CI reported by each study.

Figure 6

Diagnostic accuracy of COVID-19/SARS-CoV-2 infection—specificity forest plot for the overall cohort. The forest plot shows the specificities and 95% CIs reported for the STANARD Q COVID-19 Ag Test (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled specificity and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled specificity and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.996 represents the pooled specificity value for all shown tests. Boxes represent the reported specificity, and solid horizontal lines represent the 95% CI reported by each study.

Figure 7

Diagnostic accuracy of COVID-19/SARS-CoV-2 infection—positive predictive values forest plot. The forest plot shows the positive predictive values (PPVs) and 95% CIs reported for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled PPV and heterogeneity value (I2) for each index test is shown at the bottom of each test section. The pooled PPV and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.962 represents the pooled PPV for all shown tests. Boxes represent the reported PPV, and solid horizontal lines represent the 95% CI reported by each study. Some studies reported multiple sites and are included as an individual row for each site.

Figure 8

Diagnostic accuracy of COVID-19/SARS-CoV-2 infection—negative predictive value forest plot. The forest plot shows the negative predictive value (NPV) and 95% CIs reported for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled NPV and heterogeneity value (I2) for each index test is shown at the bottom of each test section. The pooled NPV and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.949 represents the pooled NPV for all shown tests. Boxes represent the reported value, and solid horizontal lines represent the 95% CI reported by each study. Some studies reported multiple sites and are included as an individual row for each site.

Figure 9

Diagnostic accuracy of COVID-19/SARS-CoV-2 infection—sensitivity and specificity forest plots for symptomatic subgroup. Forest plot shows the sensitivities (A) and specificities (B) and 95% CIs reported for the symptomatic subgroup for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on each forest plot are shown at the bottom. The vertical lines at 0.804 (sensitivity) and 0.994 (specificity) represent the pooled values for all shown tests. Boxes represent the reported sensitivity and specificity, and solid horizontal lines represent the 95% CI reported by each study.

Figure 10

Diagnostic accuracy of COVID-19/SARS-CoV-2 infection–positive predictive value and negative predictive value forest plots for symptomatic subgroup. Forest plot shows the positive (A) and negative (B) predictive values (PPV/NPV) and 95% CIs reported for the symptomatic subgroups of the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity values (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical lines at 0.971 (PPV) and 0.950 (NPV) represent the pooled values for all shown tests. Boxes represent the reported values, and solid horizontal lines represent the 95% CI reported by each study.

Figure 11

Diagnostic accuracy of COVID-19/SARS-CoV-2 infection—sensitivity and specificity forest plots for asymptomatic subgroup. Forest plot shows the sensitivities (A) and specificities (B) and 95% CIs reported for the asymptomatic subgroup for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on each forest plot are shown at the bottom. The vertical lines at 0.537 (sensitivity) and 0.998 (specificity) represent the pooled values for all shown tests. Boxes represent the reported sensitivity and specificity, and solid horizontal lines represent the 95% CI reported by each study.

Figure 12

Diagnostic accuracy of COVID-19/SARS-CoV-2 infection–positive predictive value and negative predictive value forest plots for asymptomatic subgroup. Forest plot shows the positive (A) and negative (B) predictive values (PPV/NPV) and 95% CIs reported for the asymptomatic subgroups of the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity values (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical lines at 0.904 (PPV) and 0.983 (NPV) represent the pooled values for all shown tests. Boxes represent the reported values, and solid horizontal lines represent the 95% CI reported by each study.