Diagnostic Accuracy of Rapid Antigen Tests for COVID-19 Detection: A Systematic Review With Meta-analysis
Maniya Arshadi1,2 Fatemeh Fardsanei3 Behnaz Deihim4 
Zahra Farshadzadeh1,2 
Farhad Nikkhahi3 
Farima Khalili5 
Giovanni Sotgiu6 
Amir Hashem Shahidi Bonjar7 
Rosella Centis8 Giovanni Battista Migliori8* 
Mohammad Javad Nasiri5* 
Mehdi Mirsaeidi9*- 1Infectious and Tropical Diseases Research Center, Health Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- 2Department of Microbiology, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- 3Medical Microbiology Research Center, Qazvin University of Medical Sciences, Qazvin, Iran
- 4Department of Bacteriology and Virology, School of Medicine, Dezful University of Medical Sciences, Dezful, Iran
- 5Department of Microbiology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- 6Istituti Clinici Scientifici Maugeri IRCCS, Tradate, Italy
- 7Clinician Scientist of Dental Materials and Restorative Dentistry, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- 8Clinical Epidemiology and Medical Statistics Unit, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
- 9Division of Pulmonary and Critical Care, College of Medicine-Jacksonville, University of Florida, Gainesville, FL, United States
Introduction: Reverse transcription-polymerase chain reaction (RT-PCR) to detect SARS-CoV-2 is time-consuming and sometimes not feasible in developing nations. Rapid antigen test (RAT) could decrease the load of diagnosis. However, the efficacy of RAT is yet to be investigated comprehensively. Thus, the current systematic review and meta-analysis were conducted to evaluate the diagnostic accuracy of RAT against RT-PCR methods as the reference standard.
Methods: We searched the MEDLINE/Pubmed and Embase databases for the relevant records. The QUADAS-2 tool was used to assess the quality of the studies. Diagnostic accuracy measures [i.e., sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratios (PLR), negative likelihood ratios (NLR), and the area under the curve (AUC)] were pooled with a random-effects model. All statistical analyses were performed with Meta-DiSc (Version 1.4, Cochrane Colloquium, Barcelona, Spain).
Results: After reviewing retrieved records, we identified 60 studies that met the inclusion criteria. The pooled sensitivity and specificity of the rapid antigen tests against the reference test (the real-time PCR) were 69% (95% CI: 68–70) and 99% (95% CI: 99–99). The PLR, NLR, DOR and the AUC estimates were found to be 72 (95% CI: 44–119), 0.30 (95% CI: 0.26–0.36), 316 (95% CI: 167–590) and 97%, respectively.
Conclusion: The present study indicated that using RAT kits is primarily recommended for the early detection of patients suspected of having COVID-19, particularly in countries with limited resources and laboratory equipment. However, the negative RAT samples may need to be confirmed using molecular tests, mainly when the symptoms of COVID-19 are present.
Introduction
COVID-19 epidemic is caused by SARS-CoV-2 and began in December 2019 in Wuhan, Hubei, China. The virus, which has infected more than 260 million people and killed more than 4.5 million as of December 10, 2021, can cause various conditions, from asymptomatic to lightning-fast respiratory failure (1, 2). Given the rapid community and congregate setting transmission and high pathogenicity, reliable and early identification of SARS-CoV-2 are critical (3). Currently, COVID-19 diagnostic techniques are classified into two categories: (1) methods that evaluate clinical samples directly for virus particles, antigens, or nucleic acids; and (2) serological assays for anti-SARS-CoV-2 antibodies (4). For COVID-19 diagnosis, the reverse transcriptase-polymerase chain reaction (RT-PCR) is the gold standard for sputum, nasopharyngeal swabs, bronchoalveolar lavage fluid, and nasal and nasal oral fluids (5). However, its widespread use is limited by the necessity for expensive laboratory equipment and well-trained laboratory personnel (6). Furthermore, these tests are frequently challenged for being too sensitive since they do not distinguish between live infections and non-viable viral remaining genetic pieces. On the other hand, these diagnostic tests can tell if a disease is present in a person but not define its contagiousness (7).
Recent studies have shown rapid antigen test (RAT) to be a more practical, less costly, and faster technique, especially in the early days following symptoms, although less sensitive (8). Antigen diagnostic assays identify proteins from a live virus in 15–30 min, such as the spike protein, nucleocapsid protein, or both (9). It is cost-effective, easy to use outside of laboratory facilities, requires no experienced workers, and may be used on a wide range of patients. Many of these tests do not need the use of analyzers or readers, making them less costly and more portable (10). Another benefit of employing an antigen test is that it may discover vast numbers of asymptomatic carriers who often migrate from one location to another. This test may also be used as a preliminary screening test before RT-PCR (11). However, despite their excellent specificity, the sensitivity of RAT kits is not as great as other molecular assays (12). Thus, the efficacy of RAT is yet to be investigated comprehensively. Therefore, the current systematic review and meta-analysis were conducted to evaluate the diagnostic accuracy of RAT against RT-PCR methods as the reference standard.
Methods
This study was conducted and reported according to the PRISMA guidelines (13).
Search Strategy and Selection Criteria
The MEDLINE/PubMed and Embase were searched for relevant studies published up to March 8 2022. The combination of the following keywords was used: (Sensitivity and Specificity) OR (predictive value) OR (accuracy) AND (COVID-19) OR (SARS-CoV-2). We used a combination of free text and MeSH terms to identify the relevant studies. Studies were included if they used commercial RAT as their index test and RT-PCR as their reference test to detect SARS-CoV-2 and provide sufficient data to compute sensitivity and specificity. Only English studies were included. Duplicate publications, protocols, reviews, conference abstracts, and in-house tests were excluded.
Extraction of Data
Two reviewers (MA and AFS) designed a data extraction form. These reviewers extracted data from all eligible studies, and consensus resolved differences. The following items were extracted from each article: the name of the first author, year of publication, study location, RT-PCR test, number of confirmed SARS-CoV-2 positive cases, cycle threshold (Ct) value, presence of symptoms, specimen types, and type of antigen tests.
Quality Assessment
The methodological quality of the studies was assessed using the QUADAS-2 checklist (14). The following items are evaluated in this checklist: Patient selection: describes methods of patient selection; index text: describes the index test and how it was conducted and interpreted; reference standard: describes the reference standard (standard gold test) and how it was conducted and interpreted; flow and timing: describes any patients who did not receive the index tests or reference standard and defines the interval and any interventions between index tests and the reference standard.
Statistical Analysis
Statistical analyses were performed with Meta-DiSc (version 1.4, Cochrane Colloquium, Barcelona, Spain) software. The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) with 95% confidence intervals between antigen rapid diagnostic tests and the reference standard were assessed. A random-effects model was used to pool the estimated effects. The random-effects model was used because of the estimated heterogeneity of the true effect sizes. Diagnostic accuracy measures [(i.e., the summary receiver operating characteristic (SROC) curve and the summary positive likelihood ratios (PLR), negative likelihood ratios (NLR), and DOR] were calculated.
Sensitivity is the proportion of positive test results among those with the target infection. Specificity is the proportion of negative test results among those without the disease. The PLR measures how frequently a positive test is found in infected vs. non-infected individuals. On the other hand, the NLR measures how likely a negative result is in infected vs. non-infected individuals. Tests with pooled PLR values >10 and a pooled NLR value of <0.1 have the greater discriminating ability (15, 16).
The DOR or the odds of a positive result in infected individuals compared to the odds of a positive result in non-infected individuals. It is calculated according to the formula: DOR = (TP/FN)/(FP/TN). DOR depends significantly on the sensitivity and specificity of a test. A high specificity and sensitivity test with a low rate of false positives and false negatives have high DOR (16).
The area under the curve (AUC) serves as a global measure of test performance; a value of 1 indicates perfect accuracy (16, 17).
Deek's test was used to identify the risk of publication bias based on parametric linear regression methods (18). Subgroup analysis was conducted using several study characteristics separately.
Results
Studies included and excluded through the review process are summarized in Figure 1. A total of 21,627 records were found in the initial search; after removing duplicate articles, titles and abstracts of 14,973 references were screened. One hundred ninety-seven articles were selected for a full-text review. Of these, 137 were excluded because they did not present primary data. Finally, 60 were chosen (Table 1) (19–78).
Figure 1. Flow chart of study selection for inclusion in the systematic review and meta-analysis.
Table 1. Characterization of included studies.
Of these, 148 were excluded because they did not present primary data (13, 19–94); or the Ag-RDT was not commercially available (16), 132–164, leaving 133 studies to be included in the systematic review.
A total of 43,034 samples (8,360 with and 34,674 without COVID-19) were investigated. The included studies came from different countries, with the majority from Germany (n = 9), followed by Spain and Italy (n = 8). Participants in the included studies varied from being either symptomatic only (n = 13), asymptomatic only (n = 9), or a mix of both (n = 24). The included studies had either adults only or participants of all ages. Three studies evaluated the diagnostic performance of antigen tests with nasal/oral swab specimens, and 52 the accuracy of antigen tests with nasopharyngeal swab specimens. Twenty-seven studies provided Ct values of positive RT-PCRs. The investigated commercial RAT was Panbio, SD Biosensor, Roche, COVID-19 Ag Respi-Strip, LUMIPULSE, and BinaxNOW. All RAT detected nucleocapsid or spike proteins.
Quality of Including Studies
Forty-five studies were judged to have a high risk of bias in the patient selection domain. Based on the QUADAS 2 tool, in these studies, patient selection methods were not fully described. Furthermore, a high risk of bias was found in the domain of the index tests in 27 studies. In thesis studies, it was not clear whether the index test results were interpreted without knowledge of the results of the reference standard. All studies underwent a reference standard and were judged to have a low risk of bias in the flow and timing domains (Table 2).
Table 2. Quality assessment of included studies.
Diagnostic Accuracy of Rapid Antigen Tests Against Reference Test
The pooled sensitivity and specificity of the RAT were 69% (95% CI: 68–70) and 99% (95% CI: 99–99) (Figures 2, 3). The PLR, NLR, DOR, and the AUC estimates were found to be 72 (95% CI: 44–119), 0.30 (95% CI: 0.26–0.36), 316 (95% CI: 167–590), and 97%, respectively. The AUC estimates in this report also represented a high level of test accuracy (Figure 4). Deek's test result indicated no likelihood for publication bias (P > 0.05).
Figure 2. Forest plot of pooled sensitivity of rapid antigen tests for the diagnosis of COVID-19. The point estimates of sensitivity from each study are indicated as a circle and a 95% confidence interval is shown with a horizontal line.
Figure 3. Forest plot of pooled specificity of rapid antigen tests for the diagnosis of COVID-19. The point estimates of specificity from each study are indicated as a circle and a 95% confidence interval is shown with a horizontal line.
Figure 4. Summary receiver operating characteristic (SROC) plot. The area under the curve (AUC), acts as an overall measure for test performance. Particularly, when AUC would be between 0.9 and 1, the accuracy is high. AUC was 0.98 in this report which represented a high level of accuracy.
Subgroup Analyses
The sensitivity for each subgroup was lower than the specificity (Table 3). The sensitivity of RAT was slightly higher in symptomatic (65%) than asymptomatic patients (64%). Kits from different manufacturers exhibited various sensitivity. Lumipulse showed the highest sensitivity (87%) followed by SD Biosensor (76%), Panbio (75%), Roche (60%), BinaxNOW (57%) and Respi-Strip (39%). The sensitivity of the nasopharyngeal swab was higher (70%) than that where throat or saliva swabs were used (52%). The sensitivity of RAT kits ranged from 65 to 71% when Ct values were 20–31. The RAT kits had a similar sensitivity based on the antigen detection technology (i.e., immunochromatography and chemiluminescent immunoassay). The pooled sensitivity for Ct value ≤ 25 was markedly better, at 71.0%, compared to the group with Ct value >26, at 67.0%.
Table 3. Pooled sensitivity and specificity among subgroups of studies.
Discussion
Diagnostic testing for SARS-CoV-2 is essential for the overall COVID-19 preventive and control plan. With the number of COVID-19 cases and mortalities increasing worldwide, it is more important than ever to look into the usefulness of existing diagnostic tests and the optimal settings to achieve the most accuracy and consistency (4).
RT-PCR has been accepted as the gold standard for SARS-CoV-2 infection diagnosis. Despite its high sensitivity and specificity, this method is expensive and needs well-equipped facilities (79). Moreover, the reporting of RT-PCR data may take longer than expected in many cases owing to large sample numbers and a lack of technical assistance, resulting in delayed patient care and outbreak control (80). Consequently, a focus on using RAT kits was required to bridge diagnostic gaps. RAT available on the market is steadily rising (81).
RATs are straightforward to conduct and interpret at the point of care by minimally educated health professionals (82, 83).
We summarized the data from 60 studies evaluating the accuracy of RAT. The sensitivity and specificity were assessed using a reliable reference standard test. The pooled estimates of sensitivity and specificity of the RAT against RT-PCR were 69 and 99%, respectively.
Similarly, Lee et al. (84) computed a sensitivity of 68% and a specificity of 99% for 24 studies focused on RAT (84). The meta-analysis of Wang et al. (85) showed a sensitivity of 79% and a specificity of 100%, pooling 14 studies (85). Likewise, according to the meta-analysis performed by Brummer et al., the sensitivity and specificity of RAT were 71.2 and 98.9%, respectively (81). In a study by Chen et al., the diagnostic accuracy of RAT for SARS-CoV-2 in community participants was assessed. The overall sensitivity and specificity were 82 and 100%, respectively (86).
The World Health Organization (WHO) recommends that a RAT kit reach a minimum performance criterion of at least 80% sensitivity and 97% specificity (87). Furthermore, RAT findings will be most acceptable in places where community transmission is continuous (5% test positive rate), according to WHO standards (87). RAT positive predictive value is poor when there is no or low transmission (many false positives). RT-PCR is better as a first-line diagnostic tool than confirming positive RAT (88).
In our meta-analysis, sensitivity below 80% and high specificity were found. Sensitivity differences of the mentioned meta-analyses may be related to the characteristics of study participants, including whether patients are symptomatic or asymptomatic and the time of sampling after the onset of symptoms. The results of the current meta-analysis support the statement of the Infectious Diseases Society of America (IDSA) guidelines on the correlation between RAT sensitivity and viral load, symptoms, and the timing of the test (89).
Similar to a previous study, low Ct values, the RT-PCR correlate for high virus concentration, resulted in significantly higher RAT sensitivity (90, 91).
RAT also showed higher sensitivity in symptomatic patients than asymptomatic patients (pooled sensitivity 65 vs. 64%), which is to be expected given that samples from patients with symptoms have been shown to contain the highest virus concentrations (90). similarly, studies that enrolled symptomatic patients showed a lower range of Ct values than studies enrolling asymptomatic patients (90–93).
Considering the epidemiological context, clinical history, and available testing funds, clinical decision-making should be used to determine whether negative RAT results necessitate confirmatory testing with RT-PCR or repeat testing with RAT (within 48 h) if RT-PCR assay is not available (94). Owing to the RAT sensitivity (69%), these tests should be used in the initial screening, contact tracing, and monitoring of the outbreak in different countries (87).
There are some limitations. First, we could not assess the correlation between sample conditions (such as storage or transportation) and the sensitivity of RAT. Second, the potential influence of different genetic and structural mutations of SARS-CoV-2 could not be evaluated because of the limited available information. Variants of SARS-CoV-2 may be differently detected by RAT. Finally, the sensitivity of RAT may differ depending on the manufacturer and the country where the kits are produced.
In conclusion, the present study showed that RAT is recommended mainly for the early detection of patients with presumed COVID-19, especially in countries with limited resources and laboratory equipment. However, negative RAT samples should be confirmed by molecular tests, mainly in the presence of COVID-19 symptoms.
Data Availability Statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.
Author Contributions
All authors participated in the drafting and revision of the manuscript, as well as in the approval of the final version.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Acknowledgments
This study was supported by Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Keywords: COVID-19, SARS-CoV-2, rapid antigen test, specificity, sensitivity, meta-analysis
Citation: Arshadi M, Fardsanei F, Deihim B, Farshadzadeh Z, Nikkhahi F, Khalili F, Sotgiu G, Shahidi Bonjar AH, Centis R, Migliori GB, Nasiri MJ and Mirsaeidi M (2022) Diagnostic Accuracy of Rapid Antigen Tests for COVID-19 Detection: A Systematic Review With Meta-analysis. Front. Med. 9:870738. doi: 10.3389/fmed.2022.870738
Received: 07 February 2022; Accepted: 18 March 2022;
Published: 07 April 2022.
Edited by:
Uwe Groß, University Medical Center Göttingen, GermanyReviewed by:
Manish Kumar Verma, Ganesh Shankar Vidyarthi Memorial Medical College, IndiaClaudia Zemmrich, Institute of Pharmacology and Preventive Medicine GmbH, Germany
Copyright © 2022 Arshadi, Fardsanei, Deihim, Farshadzadeh, Nikkhahi, Khalili, Sotgiu, Shahidi Bonjar, Centis, Migliori, Nasiri and Mirsaeidi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Mehdi Mirsaeidi, m.mirsaeidi@ufl.edu; Giovanni Battista Migliori, gbmigliori@fsm.it; Mohammad Javad Nasiri, mj.nasiri@hotmail.com