Journal of Clinical Virology
A nationwide analytical and clinical evaluation of 46 rapid antigen tests for SARS-CoV-2 compared to RT-qPCR
--Manuscript Draft--
Manuscript Number: JCV-D-22-00099R1
Article Type: Full length article
Keywords: rapid antigen tests; SARS-CoV-2; Analytical sensitivity and specificity; Clinicalsensitivity and specificity; point of care tests; reverse transcriptation quantitativepolymerase chain reaction
Corresponding Author: Uffe Schneider, Ph.D., M.D.Hvidovre HospitalHvidovre, DENMARK
First Author: Uffe Schneider, Ph.D., M.D.
Order of Authors: Uffe Schneider, Ph.D., M.D.
Maria Wendelboe Forsberg, MLS
Thomas Daell Leineweber, MD
Christel Barker Jensen, PhD
Khaled Ghathian, MLS,MEd
Charlotte Nielsen Agergaard, MD
Kasper Kjersgaard Mortensen, MD
Arieh Cohen, PhD
Charlotte Sværke Jørgensen, PhD
Helene Larsen, PhD
Matilde Bøgelund Hansen, MSc
Ulla Saleme, BMed
Anders Koch, PhD
Nikolai Søren Kirkby, PhD
Thomas Kallemose, MSc
Marie Louise Schaadt, MD
Frederikke Holm Jensen, MD
Rikke Lind Jørgensen, MSc
Chih Man German Ma, MLS
Nina Steenhard, PhD
Jenny Dahl Knudsen, DMSc
Jan Gorm Lisby, PhD
Abstract: Background
The SARS-CoV-2 pandemic has resulted in massive testing by Rapid Antigen Tests(RAT) without solid independent data regarding clinical performance being available.Thus, decision on purchase of a specific RAT may rely on manufacturer-provided dataand limited peer-reviewed data.
Methods
This study consists of two parts. In the retrospective analytical part, 33 RAT and a
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Strand Invasion Based Amplification (SIBA)-rt-PCR test from 26 manufacturers werecompared to RT-qPCR on 100 negative and 204 positive deep oropharyngeal cavitysamples divided into four groups based on RT-qPCR Cq levels. In the prospectiveclinical part, 200 individuals found SARS-CoV-2 positive and 200 individuals foundSARS-CoV-2 negative by routine RT-qPCR testing were tested within 72 hours with 46included RAT from 28 manufacturers applying RT-qPCR as the reference method.
Results
The overall analytical sensitivity differed significantly between the 34 included RAT;from 2.5% (95% CI 0.5-4.8) to 67% (95% CI 60-73). All RAT presented analyticalspecificities between 93-100%. Likewise, the overall clinical sensitivity variedsignificantly between the 46 included RAT; from 2.5% (95% CI 0.5-4.8) to 94 % (95%CI 91-97). All RAT presented clinical specificities between 97-100%.
Conclusion
The study presents analytical as well as clinical performance data for 46 commerciallyavailable RAT compared to the same RT-qPCR test. The study enables identificationof individual RAT that has significantly higher sensitivity than other included RAT andmay aid decision makers in selecting between the included RAT.
Funding
The study was funded by a participant fee for each test and the Danish Regions.
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Conflict of interest
Lars Østergaard has within 36 months received speaker fees from Sanofi-Pasteur and Pfizer. None of the
other authors have any personal conflict of interests to report. The project received a participation fee
from each of the participating companies to cover the cost of the project.
Conflict of Interest
A nationwide analytical and clinical evaluation of 46 rapid antigen tests for SARS-CoV-2 compared to RT-
qPCR
Uffe Vest Schneider, PhD1; Maria Wendelboe Forsberg, MLS1; Thomas Daell Leineweber, MD1; Christel
Barker Jensen PhD1; Khaled Ghathian MEd1; Charlotte Nielsen Agergaard, MD2; Kasper Kjersgaard
Mortensen, MD3; Arieh Cohen, PhD4; Charlotte Sværke Jørgensen, PhD5; Helene Larsen, PhD6; Matilde
Bøgelund Hansen, MSc7; Ulla Saleme, BMed8; Anders Koch, PhD9; Nikolai Søren Kirkby, PhD10; The National
Danish RAT testing group11; Thomas Kallemose, MSc12; Marie Louise Schaadt, MD1; Frederikke Holm Jensen,
MD1; Rikke Lind Jørgensen MSc1; Chih Man German Ma, MLS1; Nina Steenhard, PhD4; Jenny Dahl Knudsen,
DMSc10; Jan Gorm Lisby, PhD 1
1 Copenhagen University Hospital Hvidovre, Department of Clinical Microbiology, Kettegaard Alle 30, 2650
Hvidovre, Denmark
2 Odense University Hospital, Department of Clinical Microbiology, J. B. Winsløws Vej 21, 2., 5000 Odense C,
Denmark
3 Aarhus University Hospital, Department of Clinical Microbiology, Palle Juul-Jensens Boulevard 99, Skejby,
8200 Aarhus N., Denmark
4 Danish National Test Center, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
5 Statens Serum Institut, Department of Virus & Microbiological Special Diagnostics, Artillerivej 5, 2300
Copenhagen, Denmark
6 Technical University of Denmark - DTU, Centre for Diagnostics Department of Health Technology, Henrik
Dams Allé, 2800 Kgs Lyngby, Denmark
7 Copenhagen University Hospital Herlev and Gentofte, Department of Clinical Microbiology, Borgmester Ib
Juuls Vej 52, 2730 Herlev, Denmark
8 Copenhagen University Hospital Bispebjerg and Frederiksberg, Department of Clinical Biochemistry,
Nielsine Nielsens Vej 4B, 2400 Copenhagen, Denmark
9 Rigshospitalet University Hospital, Department of Infectious Diseases, Blegdamsvej 9, 2100 Copenhagen,
Denmark
10 Rigshospitalet, Department of Clinical Microbiology, Henrik Harpestrengsvej 4A, 2100 Copenhagen,
Denmark
11 The Danish National rapid antigen testing group
12 Copenhagen University Hospital Hvidovre, Department of Clinical Research, Kettegaard Alle 30, 2650
Hvidovre, Denmark
Title Page (including author details, affiliations and word count)
Corresponding author
Uffe Vest Schneider,
Copenhagen University Hospital Hvidovre, Department of Clinical Microbiology, Kettegaard Alle 30, 2650
Hvidovre, Denmark
Email: [email protected]
Phone: +45 38622429
The National Danish RAT testing group First name Surname
John Eugenio Coia
Svend Ellermann-Eriksen
Lennart Friis-Hansen
David Fuglsang-Damgaard
Jens Otto Jarløv
Ulrich Stab Jensen
Sanne Jespersen
Ea Sofie Marmolin
Lene Nielsen
Xiaohui Chen Nielsen
Anel Ramic
Lars Jørgen Østergaard
The clinical sensitivity among 46 rapid antigen tests for SARS-CoV-2 varied from 0.03 [95% CI 0.01-0.05] to
0.94 [0.91-0.97]
29 rapid antigen tests performed significantly worse than the 17 best performing rapid antigen tests in the
study
The study demonstrates that analytical sensitivity cannot be directly translated to clinical sensitivity for
individual SARS-CoV-2 rapid antigen tests
Highlights (for review)
1
Abstract 1
Background 2
The SARS-CoV-2 pandemic has resulted in massive testing by Rapid Antigen Tests (RAT) without solid 3
independent data regarding clinical performance being available. Thus, decision on purchase of a specific 4
RAT may rely on manufacturer-provided data and limited peer-reviewed data. 5
Methods 6
This study consists of two parts. In the retrospective analytical part, 33 RAT and a Strand Invasion Based 7
Amplification (SIBA)-rt-PCR test from 26 manufacturers were compared to RT-qPCR on 100 negative and 8
204 positive deep oropharyngeal cavity samples divided into four groups based on RT-qPCR Cq levels. In the 9
prospective clinical part, 200 individuals found SARS-CoV-2 positive and 200 individuals found SARS-CoV-2 10
negative by routine RT-qPCR testing were tested within 72 hours with 46 included RAT from 28 11
manufacturers applying RT-qPCR as the reference method. 12
Results 13
The overall analytical sensitivity differed significantly between the 34 included RAT; from 2.5% (95% CI 0.5-14
4.8) to 67% (95% CI 60-73). All RAT presented analytical specificities between 93-100%. Likewise, the 15
overall clinical sensitivity varied significantly between the 46 included RAT; from 2.5% (95% CI 0.5-4.8) to 94 16
% (95% CI 91-97). All RAT presented clinical specificities between 97-100%. 17
Conclusion 18
The study presents analytical as well as clinical performance data for 46 commercially available RAT 19
compared to the same RT-qPCR test. The study enables identification of individual RAT that has significantly 20
higher sensitivity than other included RAT and may aid decision makers in selecting between the included 21
RAT. 22
Funding 23
The study was funded by a participant fee for each test and the Danish Regions. 24
Introduction 25
During the current SARS-CoV-2 pandemic, massive testing has been applied with the aim to contain the 26
spread of the virus. The test strategy was emphasized by the WHO in March, 2020 as the backbone of the 27
global pandemic response together with isolation and contact tracing that combined with social distancing 28
and hand hygiene would allow “to extinguish” the pandemic [1]. 29
Revised Manuscript (text UNmarked) Click here to view linked References
2
The unprecedented demand for testing has led to a shortage of reagents and manufactured tests for 30
reverse transcription quantitative polymerase chain reaction (RT-qPCR) and other nucleic acid amplification 31
technology (NAAT) methods including point of care testing (PoCT). Thus, lateral flow based rapid antigen 32
tests (RAT) have been deployed extensively due to delivery of results within minutes, availability, low cost 33
and the ease of use that allow non-healthcare trained individuals to perform the test outside of healthcare 34
facilities [2,3]. 35
Several approaches to evaluate real-life performance of RAT has been applied, including studies on cultured 36
virus, retrospective studies evaluating analytical performance data and clinical evaluations [4–13]. 37
Viral culture studies have shown that limit of detection (LOD) of RAT differs significantly and varies 38
depending on spike variants of SARS-CoV-2 [4,14]. SARS-CoV-2 variants contain several mutations in the 39
nucleocapsid gene together with mutations in the spike gene, which may account for the difference in LOD 40
[15]. 41
Clinical studies have shown that sensitivity of a single RAT may vary at least 20 percentage point between 42
non-symptomatic and symptomatic individuals [9,16–18]. As most clinical studies only include a single or 43
few different RAT and as the tested population varies between different clinical studies regarding SARS-44
CoV-2 prevalence, proportion of symptomatic versus non-symptomatic individuals, vaccination status and 45
demographic profile, comparing performance data between different studies is difficult [9–11,19,20]. Due 46
to the absence of clinical studies that allow for comparison of the different performances of commercially 47
available RAT and the huge amount of financial resources spent on RAT, the Danish Regions initiated a 48
nationwide clinical study comparing different RAT. This study combines a retrospective analytical sensitivity 49
and specificity study on 100 negative and 204 positive frozen samples with a prospective clinical study on 50
sensitivity and specificity, in which approximately 200 SARS-CoV-2 positive individuals and 200 SARS-CoV-2 51
negative individuals were tested by routine RT-qPCR and a number of RAT within 72 hours of the initial RT-52
qPCR test. 53
Methods 54
For detailed description of protocol and methods, please refer to Supplementary data and [21]. 55
Study design 56
A total of 46 tests, 44 RAT and two SIBA-rt-PCR from 28 manufacturers, were included in the study. 57
3
Participants 58
Individuals, who tested positive for SARS-CoV-2 by routine RT-qPCR performed by a public test provider 59
were included in the study. 60
Retrospective analytical RAT testing 61
UTM samples from SARS-CoV-2 RT-qPCR positive individuals participating in the prospective arm of the 62
study were collected by out-patient testing teams. All samples were collected as deep oropharyngeal swabs 63
and immediately stored at -80 °C until further processing. In total, 50 samples with Cq <25; 54 samples with 64
Cq between 25 and 30; 50 samples with Cq between 30 and 35 and 50 samples with Cq between 35 and 40 65
were prepared. One hundred SARS-CoV-2 RT-qPCR negative samples were prepared by pooling ten routine 66
UTM samples that had tested negative for SARS-CoV-2 for each negative sample (Figure 1A). 67
Prospective clinical RAT testing 68
From each included individual, deep oropharyngeal swabs, anterior nasal cavity swabs and saliva were 69
collected for RAT testing together with a deep oropharyngeal swab for RT-qPCR testing. All tests were 70
conducted according to the IFU or according to additional instruction from the manufacturer using the 71
utensils provided for testing by the manufacturer. Samples collected from other anatomical sites than CE-72
marked were collected and handled as instructed by each manufacturer. 73
Prospective RT-qPCR 74
Deep oropharyngeal swabs for RT-qPCR were collected in a NEST disposable sampler inactivation transport 75
medium with an oropharyngeal specimen collection swab (Wuxi NEST Biotechnology Co., Ltd, Wuxi City, 76
China) and sent to RT-qPCR testing. 77
Analysis 78
Dual-target RT-qPCR was used as gold standard. In the retrospective part of the study, samples were 79
grouped into four Cq ranges based on the highest Cq level of the two E- and N-targets. In the prospective 80
part of the study, samples were grouped into three Cq ranges based on the average Cq level between the 81
two N-targets. 82
Sensitivity and specificity were calculated for each individual RAT in relation to RT-qPCR. All p-values less 83
than 0.05 were considered statistically significant. 84
Role of the funding source 85
The participating companies had no influence on study design, sample collection, analysis, interpretation, 86
drafting of manuscript, or decision on publishing. 87
4
Results 88
Participants and SARS-CoV-2 variants 89
A total of 3,797 individuals were included in the prospective part of the study between January 18th, 2021 90
and September 9th, 2021 to allow each RAT to be tested on 200 SARS-CoV-2 positive and 200 SARS-CoV-2 91
negative individuals. 2,045 individuals that had just tested positive for SARS-CoV-2 were included in the 92
study within 72 hours and 1,752 SARS-CoV-2 expected RT-qPCR negative individuals were included after 93
screening at a regional test center. Among the newly positive individuals for SARS-CoV-2, twelve individuals 94
were excluded due to missing sample for RT-qPCR (n = 3) or a negative RT-qPCR test including the human 95
control target (n = 9). Among the remaining 2,033 individuals, 140 (6.9%) were negative by the concomitant 96
RT-qPCR at the time of RAT testing (Figure 1B), resulting in inclusion of 1,893 positive individuals among the 97
previous SARS-CoV-2 positive individuals. In the screening group, forty-three individuals were excluded, 98
eight samples were missing for RT-qPCR and thirty-five samples were negative for all targets including the 99
human sampling control. Thus, a total of 1,709 SARS-CoV-2 negative or positive individuals by RT-qPCR 100
were included in the screening group. The SARS-CoV-2 prevalence in the screening group was 0.64%, as 11 101
out of 1,709 individuals were positive for SARS-CoV-2 by RT-qPCR (Figure 1B). Participating individuals were 102
predominantly between 18 and 70 years of age with few individuals above 70 years of age. Study 103
participants were mainly unvaccinated at the time of inclusion. 104
The alpha variant (B.1.1.7) was the predominating variant among SARS-CoV-2 positive individuals included 105
in the study and accounted for 90.8% (1,729 of 1,904) of all cases (Supplementary data). 106
Analytical sensitivity and specificity of RAT 107
The overall analytical sensitivity differed significantly between the 34 included tests from 26 108
manufacturers. The SIBA-rt-PCR based assay had the highest overall sensitivity of 67% (95% CI 60-73), but 109
also the lowest specificity of 93% (95% CI 88-98%). The RAT varied from 2.5% (95% CI 0.5-4.8) for the Lituo 110
saliva RAT to 42% (95% CI 35-49) for the Acro RAT. All RAT had a specificity of 100% (Figure 2). The overall 111
mean sensitivity for the tests was 26% (95% CI 21-32), which reflects that RAT detected almost none of the 112
samples with Cq >35 by RT-qPCR (n = 50). For RT-qPCR samples with Cq 30-35 (n = 50), the mean sensitivity 113
was 2.5% (95% CI 1.5-3.8) but increased at Cq 25-30 (n = 54) with a mean sensitivity of 32% (95% CI 21-42) 114
and a mean sensitivity of 71% (95% CI 61-80, range 6.2-99) for samples with RT-qPCR Cq <25 (n = 50) 115
(Supplementary data). 116
5
Clinical sensitivity and specificity of RAT 117
In the prospective part of the study, the overall clinical sensitivity varied significantly among the 46 118
included tests from 28 manufacturers; from 2.5% (95% CI 0.5-4.8) for the Quidel saliva RAT to 94% (95% CI 119
91-97) for the Acon Flowflex RAT, with a mean overall sensitivity of 69% (95% CI 63-74). Specificity varied 120
among the RAT from 98% (95% CI 95-99) for the Abbott nasal RAT to 100% for 28 RAT, whereas the Qlife 121
SIBA-rt-PCR Egoo system had the lowest specificity of 97% (95% CI 95-99) for anterior nasal cavity swabs 122
(Figure 3). According to CE-mark, the sensitivities for all tests were reported to be 81% (95% CI 69-89) or 123
above and specificities were reported from 97% (95% CI 91-99) and above (Supplementary data). 124
The sensitivity of the Acon Flowflex RAT did not differ significantly from 16 of the other RAT from 14 125
manufacturers, when multiple testing was taken into account. The remaining 29 RAT (including the visual 126
and automated read-out of the BD veritor RAT) had a significantly lower overall sensitivity compared to the 127
Acon Flowflex RAT (Table 1 and Supplementary data). 128
The mean overall sensitivity was 81% (95% CI 74-87) for strong positive samples with Cq <15, which 129
decreased to 70% (95% CI 62-78) for medium positive samples with Cq 15-20 and 44% (95% CI 31-56) mean 130
sensitivity for weak positive samples with Cq >20 (Supplementary data). Three out of the four included self-131
test were among the 17 most sensitive tests in the study, whereas the Wantai saliva/buccal RAT was among 132
the five tests with the lowest sensitivity in the study. The sensitivity of RAT with automated readout was 133
distributed over the full range of sensitivities with the Lumira Dx and Quidel nasal RAT performing among 134
the 17 best tests of the study. 135
Discussion 136
In our study, we used deep oropharyngeal swabs collected for the analytical sensitivity and specificity 137
study. Thirty-four RAT were compared using the same 204 SARS-CoV-2 positive samples and we anticipated 138
that the analytical sensitivity data would correlate with the ranking in clinical sensitivity among the 46 RAT 139
in the prospective part of the study. The prospective study included a higher number of different RAT 140
compared to the retrospective study, as several manufacturers provided identical RAT to be used on 141
several anatomical sampling sites. Interestingly, we saw similarities between analytical sensitivity and 142
clinical sensitivity on SARS-CoV-2 positive individuals, but several tests performed differently between the 143
retrospective and prospective part of study. As an example, the Qlife SIBA-rt-PCR and the Acro RAT 144
presented the highest analytical sensitivity, but both tests performed significantly worse than the Acon 145
Flowflex RAT in the prospective part of the study. Our data shows that anterior nasal cavity RAT in general 146
had higher sensitivity compared to deep oropharyngeal RAT and RAT using saliva for testing performed the 147
6
worst. This may indicate that the Acro RAT using deep oropharyngeal swabs is underperforming in the 148
prospective part of the study as anterior nasal cavity swabs may be a better testing material. Surprisingly, 149
the Qlife SIBA-rt-PCR performed with an unexpected low sensitivity and specificity in the prospective part 150
of the study. This may be due to the small sample volume being used for the test. Furthermore, results 151
were reported by the automated Egoo instrument result-algorithm, which is still under development and 152
previous evaluations of the Qlife SIBA-rt-PCR have been conducted by visual inspection of results instead of 153
the automated result determination [22]. A more general concern regarding the comparison of 154
retrospective and prospective results is that the sampling step, release of material and lysis material from 155
the swab in the lysis buffer are removed from the comparison in retrospective studies, which may lead to 156
underperformance of clinically optimized RAT in analytical studies. 157
The primary strength of this study is that we can identify RAT that perform significantly better than other 158
RAT included in the study, as we report analytical as well as clinical performance data for a large number of 159
commercially available RAT and compare the RAT performance to the same RT-qPCR test on the same 160
samples. 161
This study has several limitations. First, it is important to emphasize that the study was designed to 162
compare performance differences between the included RAT. The data reported in this study cannot be 163
used to predict the sensitivity of a certain RAT in a specific clinical setting. Second, as the out-patient 164
testing teams knew the RT-qPCR result of the included individual prior to sampling and testing by RAT, and 165
as even a weak band should be regarded as a positive test result, the prospective part of the study is biased 166
towards overestimating the sensitivity of each RAT. Third, the current study is likely to overestimate the 167
clinical sensitivity of the included RAT as the study was performed prior to vaccination of the participating 168
age groups. It has previously been shown that vaccination accelerates viral clearance, which may reduce 169
the amount of viral particles released by infected individuals and thereby narrows the time period for a 170
positive RAT [23]. Finally, at the time of the study, the predominant variant of SARS-CoV-2 was the B.1.1.7 171
alpha variant with few cases of the delta variant (B.1.617.2). It has previously been shown that different 172
SARS-CoV-2 variants may influence the analytical sensitivity of different RAT [14], which may translate to 173
differences in clinical sensitivity of RAT if other SARS-CoV-2 variants are predominant [9]. 174
In conclusion, this study compares analytical and clinical sensitivities to RT-qPCR of 46 commercially 175
available RAT and enables identification of individual RAT that has significant higher sensitivity than other 176
included RAT. The study demonstrates significant differences in analytical as well as clinical sensitivities 177
between the included RAT but cannot be used for prediction of the clinical sensitivity in a specific clinical 178
7
setting. The results reported in this study may guide decision makers prior to purchase of RAT for 179
population screening. 180
Acknowledgments 181
All participating companies contributed with a participant’s fee to cover the costs of the study and 182
delivered all necessary RAT and additional materials free of charge. The authors thank bioinformatician 183
Jose Castruita for assisting with the variant analysis of the SARS-CoV-2 positive samples. 184
Authors' contributions 185
UVS, JGL, and JDK conceptuated the study. UVS and JGL were responsible for the funding acquisition. 186
Acquisition of data was conducted by UVS, MWF, TDL, CBJ, KG, CNA, KKM, CSJ, HL, MBJ, US, AK, NSK, The 187
National Danish RAT testing group, MLS, FHJ, RLJ, CMGM, NS, and JGL. Local supervision of research activity 188
was conducted by MWF, CNA, KKM, AC, NS, CSJ, HL, MBH, US, AK, and NSK. Overall project administration 189
was conducted by UVS, MWF, AC, CSJ, JDK, and JGL. Data was curated by CBJ, KG, MWF, CNA, KKM, CSJ, US, 190
NSK, UVS, and JGL. Data was validated by or under supervision of MWF, CBJ, CNA, KKM, CSJ, HL, US, NSK, 191
RLJ, JGL, and UVS. TK and UVS performed the formal analysis of data. 192
UVS and JGL drafted the manuscript with substantial input from JDK. All authors read and commented on 193
the manuscript and all authors approved the final manuscript prior to submission. All authors agree to be 194
held accountable for all aspects of the work. 195
Conflict of interest 196
Lars Østergaard has within 36 months received speaker fees from Sanofi-Pasteur and Pfizer. None of the 197
other authors have any personal conflict of interests to report. The project received a participation fee 198
from each of the participating companies to cover the cost of the project. 199
Ethics committee approval 200
The study was evaluated by the National Committee on Health Research Ethics in the Danish Capital Region 201
to be a method validation study without the need of approval of the committee (decision H-20068579). 202
Access to test results for research was granted by the Capital Region of Denmark – Research and Innovation 203
(R-20083753) and contact to participants without prior consent from the individual was granted by the 204
board of directors at the Hospitals at which the participating DCM are situated. 205
206
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207
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316
RAT
Aco
n (
N; 0
.94
)
Lum
iraD
x (N
; 0.9
3)
Wo
nd
fo (
N; 0
.93
)
SD B
iose
nso
r (N
; 0.9
2)
DN
A d
iagn
ost
ics
(N;
0.9
1)
Fujir
ebio
(N
; 0.9
1)
Qia
gen
(N
; 0.9
0)
Qu
idel
(N
; 0.9
0)
Siem
ens
(N; 0
.90
)
Ro
che
(N; 0
.87
)
CTK
On
site
(N
; 0.8
6)
Bio
syn
ex A
g (N
; 0.8
4)
Fujir
ebio
(O
P; 0
.84
Szyb
io (
N; 0
.84
)
Qia
gen
(O
P; 0
.83
)B
D V
erit
or
(N v
isu
al;
0.8
1)
No
vira
l (N
; 0.8
1)
AU
H T
est
(N; 0
.80
)
Qu
idel
(O
P; 0
.80
)
Wh
ole
po
wer
(N
; 0.8
0)
Acr
o (
OP
; 0.7
9)
BD
Ver
ito
r (N
; 0.7
9)
Ab
bo
tt (
N; 0
.78
)B
iosy
nex
Ag+
(O
P;
0.7
7)
Viv
aDia
g (N
; 0.7
7)
AllT
est
(OP
; 0.7
6)
Litu
o (
N; 0
.75
)
Ap
i ph
arm
a (N
; 0.7
4)
Gen
sure
(N
; 0.7
4)
SD B
iose
nso
r (O
P; 0
.73
)
Qlif
e(N
; 0.7
2)
Ab
bo
tt (
OP
; 0.6
8)
Ro
che
(OP
; 0.6
9)
Szyb
io (
OP
; 0.6
5)
Siem
ens
(OP
; 0.6
5)
Wan
tai(
OP
; 0.5
9)
Acr
o (
S; 0
.49
)
Elys
ium
(O
P; 0
.48
)
Ap
i ph
arm
a(O
P; 0
.46
)
Qlif
e (O
P; 0
.32
)
No
vira
l (S;
0.2
9)
Szyb
io(S
; 0.1
9)
Wan
tai (
S; 0
.19
)
Elys
ium
(S;
0.1
3)
Litu
o(S
; 0.1
2)
LumiraDx (N; 0.92) *
Wondfo (N; 0.93)
SD Biosensor (N; 0.92) *
DNA diagnostics (N; 0.91) * *
Fujirebio (N; 0.91)
Qiagen (N; 0.90) *
Quidel (N; 0.90) * *
Siemens (N; 0.90) * *
Roche (N; 0.87)
CTK Onsite (N; 0.86)
Biosynex Ag (N; 0.84)
Fujirebio (OP; 0.84 * * *
Szybio (N; 0.84) *
Qiagen (OP; 0.83) * * * *
BD Veritor (N visual; 0.81) * * *
Noviral (N; 0.81)
AUH Test (N; 0.80) * *
Quidel (OP; 0.80)
Wholepower (N; 0.80)
Acro (OP; 0.79)
BD Veritor (N; 0.79)
Abbott (N; 0.78)
Biosynex Ag+ (OP; 0.77)
VivaDiag (N; 0.77)
AllTest (OP; 0.76)
Lituo (N; 0.75)
Api pharma (N; 0.74)
Gensure (N; 0.74)
SD Biosensor (OP; 0.73)
Qlife (N; 0.72)
Abbott (OP; 0.68)
Roche (OP; 0.69)
Szybio (OP; 0.65)
Siemens (OP; 0.65)
Wantai (OP; 0.59)
Acro (S; 0.49)
Elysium (OP; 0.48)
Api pharma (OP; 0.46)
Qlife (OP; 0.32)
Noviral (S; 0.29)
Szybio (S; 0.19)
Wantai (S; 0.19)
Elysium (S; 0.13)
Lituo (S; 0.12)
Quidel (S; 0.025)
Table 1 Comparison of clinical sensitivity between RAT. Green fields are non-significant differences, red are significant differences in clinical sensitivity. N anterior nasal cavity swabs,OP deep oropharyngeal swabs, S saliva. Sensitivity is reported in brackets. Details for calculation are included in Supplementary data.
Table 1 Click here to access/download;Table;Table 1.pptx
A Retrospective testing n=304
Cq <25, n=50 Cq 25-30, n=54 Cq 30-35, n=50 Cq >35, n=50RT-qPCR negative,
n=100
Abbott TP 22, FN 28, Inv 0 TP 12, FN 42, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Acon TP 38, FN 12, Inv 0 TP 17, FN 37, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Acro TP 50, FN 0, Inv 0 TP 33, FN 21, Inv 0 TP 3, FN 47, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 AllTest TP 47, FN 3, Inv 0 TP 35, FN 19, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Api pharma TP 38, FN 12, Inv 0 TP 13, FN 41, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 AUH Test TP 9, FN 41, Inv 0 TP 1, FN 53, Inv 0 TP 0, FN 50, Inv 0 TP 1, FN 49, Inv 0 TN 100, FP 0, Inv 0 BD Veritor TP 25, FN 25, Inv 0 TP 10, FN 44, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 BD Veritor N (visual) TP 25, FN 25, Inv 0 TP 9, FN 45, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Biosynex Ag TP 48, FN 2, Inv 0 TP 31, FN 23, Inv 0 TP 5, FN 45, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Biosynex Ag+ TP 41, FN 9, Inv 0 TP 13, FN 41, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 CTK Onsite TP 42, FN 8, Inv 0 TP 23, FN 31, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 DNA diagnostics TP 41, FN 5, Inv 4 TP 29, FN 25, Inv 0 TP 1, FN 49, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Fujirebio TP 50, FN 0, Inv 0 TP 31, FN 23, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Gensure TP 19, FN 31, Inv 0 TP 2, FN 52, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Lituo N TP 23, FN 27, Inv 0 TP 4, FN 50, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Lituo S TP 5, FN 45, Inv 0 TP 0, FN 54, Inv 0 TP 0, FN 49, Inv 1 TP 0, FN 49, Inv 1 TN 100, FP 0, Inv 0 LumiraDx TP 39, FN 11, Inv 0 TP 21, FN 33, Inv 0 TP 1, FN 49, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Noviral N TP 50, FN 0, Inv 0 TP 25, FN 29, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Noviral S TP 43, FN 7, Inv 0 TP 0, FN 54, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Qiagen TP 45, FN 5, Inv 0 TP 0, FN 54, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Qlife TP 50, FN 0, Inv 0 TP 50, FN 4, Inv 0 TP 30, FN 20, Inv 0 TP 6, FN 44, Inv 0 TN 93, FP 7, Inv 0 Quidel TP 37, FN 13, Inv 0 TP 16, FN 38, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Roche N TP 27, FN 23, Inv 0 TP 12, FN 42, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Roche OP TP 43, FN 7, Inv 0 TP 10, FN 43, Inv 1 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 SD Biosensor TP 40, FN 10, Inv 0 TP 12, FN 42, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 SD Biosensor OP TP 23, FN 27, Inv 0 TP 10, FN 44, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Siemens TP 44, FN 6, Inv 0 TP 20, FN 34, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Szybio TP 40, FN 10, Inv 0 TP 14, FN 40, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Szybio S TP 23, FN 27, Inv 0 TP 6, FN 48, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 VivaDiag TP 37, FN 13, Inv 0 TP 16, FN 38, Inv 0 TP 1 FN 49, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Wantai OP TP 40, FN 10, Inv 0 TP 23, FN 31, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Wantai S TP 42, FN 8, Inv 0 TP 21, FN 33, Inv 0 TP 1, FN 49, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Wholepower TP 14, FN 36, Inv 0 TP 7, FN 47, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0 Wondfo TP 43, FN 7, Inv 0 TP 25, FN 29, Inv 0 TP 0, FN 50, Inv 0 TP 0, FN 50, Inv 0 TN 100, FP 0, Inv 0
Figure 1A Click here to access/download;Figure;Figure 1A STARD diagram.pptx
Included patients n = 3.797
Included SARS-CoV-2 previous positive n = 2.045
Screening at regional test center n = 1.752
RT-qPCR positive n = 1.893
RT-qPCR negativen = 140
RT-qPCR Invalid n = 12- Sample missing (n = 3)- Human control
negative (n = 9)
RT-qPCR positive n = 11
RT-qPCR negativen = 1.698
RT-qPCR Invalid n = 43- Sample missing (n = 8)- Human control
negative (n = 35)
TN 7, FP 0, Inv 0 TP 143, FN 64, Inv 1 Abbott (OP) n=390 TN 171, FP 0, Inv 0 TP 0, FN 4, Inv 0TN 6, FP 1, Inv 0 TP 163, FN 44, Inv 0 Abbott (N n=390 TN 169, FP 3, Inv 0 TP 0, FN 3, Inv 1TN 5, FP 0, Inv 0 TP 187, FN 12, Inv 0 Acon (N) n=414 TN 210, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 13, FP 1, Inv 0 TP 172, FN 46, Inv 0 Acro (OP) n=429 TN 196, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 13, FP 1, Inv 0 TP 100, FN 106, Inv 12 Acro (S) n=428 TN 174, FP 1, Inv 20 TP 0, FN 1, Inv 0TN 31, FP 0, Inv 0 TP 155, FN 49, Inv 1 Alltest (OP) n=407 TN 169, FP 0, Inv 0 TP 1, FN 1, Inv 0TN 11, FP 0, Inv 0 TP 92, FN 109, Inv 4 Api pharma (OP) n=413 TN 196, FP 0, Inv 0 TP 1, FN 0, Inv 0TN 10, FP 1, Inv 0 TP 146, FN 53, Inv 6 Api pharma (N) n=412 TN 195, FP 0, Inv 0 TP 1, FN 0, Inv 0TN 7, FP 0, Inv 0 TP 145, FN 36, Inv 3 AUH Test (N) n=376 TN 184, FP 1, Inv 0 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 158, FN 41, Inv 0 BD Veritor (N) n=411 TN 207, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 165, FN 39, Inv 1 BD Veritor (N) vis n=422 TN 212, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 13, FP 1, Inv 0 TP 183, FN 35, Inv 0 Biosynex Ag (N) n=434 TN 201, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 14, FP 0, Inv 0 TP 165, FN 51, Inv 0 Biosynex Ag+ (OP) n=414 TN 183, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 9, FP 0, Inv 0 TP 184, FN 30, Inv 1 CTK onsite (N) n=420 TN 193, FP 0, Inv 2 TP 0, FN 1, Inv 0TN 23, FP 1, Inv 0 TP 202, FN 18, Inv 1 DNA diagnostic (N) n=418 TN 169, FP 0, Inv 0 TP 1, FN 1, Inv 2TN 7, FP 0, Inv 0 TP 101, FN 107, Inv 1 Elysium (OP) n=391 TN 171, FP 0, Inv 0 TP 1, FN 3, Inv 0TN 7, FP 0, Inv 0 TP 27, FN 179, Inv 3 Elysium (S) n=388 TN 167, FP 1, Inv 0 TP 0, FN 4, Inv 0TN 22, FP 0, Inv 0 TP 172, FN 30, Inv 0 Fujirebio (OP) n=465 TN 229, FP 0, Inv 10 TP 0, FN 2, Inv 0TN 22, FP 0, Inv 0 TP 183, FN 18, Inv 1 Fujirebio (N) n=441 TN 196, FP 0, Inv 19 TP 0, FN 1, Inv 1TN 13, FP 4, Inv 0 TP 150, FN 54, Inv 1 Gensure (N) n=424 TN 200, FP 0, Inv 1 TP 0, FN 1, Inv 0TN 13, FP 1, Inv 0 TP 160, FN 54, Inv 4 Lituo (N) n=450 TN 216, FP 0, Inv 2 TP 0, FN 0, Inv 0TN 13, FP 0, Inv 1 TP 26, FN 184, Inv 8 Lituo (S) n=447 TN 206, FP 2, Inv 7 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 193, FN 15, Inv 0 Lumiradx (N) n=416 TN 202, FP 0, Inv 0 TP 1, FN 0, Inv 0TN 6, FP 1, Inv 0 TP 169, FN 39, Inv 1 Noviral (N) n=389 TN 168, FP 1, Inv 0 TP 1, FN 1, Inv 2TN 7, FP 0, Inv 0 TP 59, FN 147, Inv 3 Noviral (S) n=384 TN 162, FP 1, Inv 1 TP 1, FN 3, Inv 0TN 21, FP 0, Inv 1 TP 167, FN 35, Inv 0 Qiagen (OP) n=430 TN 206, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 22, FP 0, Inv 0 TP 180, FN 21, Inv 1 Qiagen (N) n=430 TN 206, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 16, FP 1, Inv 0 TP 66, FN 142, Inv 0 Qlife (OP) n=389 TN 162, FP 2, Inv 0 TP 0, FN 0, Inv 0TN 11, FP 6, Inv 0 TP 150, FN 59, Inv 0 Qlife (N) n=447 TN 220, FP 1, Inv 0 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 160, FN 40, Inv 7 Quidel (OP) n=392 TN 176, FP 0, Inv 4 TP 0, FN 0, Inv 0TN 5, FP 0, Inv 0 TP 185, FN 20, Inv 3 Quidel (N) n=368 TN 145, FP 0, Inv 10 TP 0, FN 0, Inv 0TN 4, FP 1, Inv 0 TP 5, FN 199, Inv 3 Quidel (S) n=366 TN 146, FP 0, Inv 8 TP 0, FN 0, Inv 0TN 11, FP 0, Inv 0 TP 140, FN 65, Inv 0 Roche (OP) n=406 TN 190, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 10, FP 1, Inv 0 TP 177, FN 28, Inv 0 Roche (N) n=403 TN 187, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 24, FP 0, Inv 0 TP 162, FN 60, Inv 0 SD Biosensor (OP) n=441 TN 194, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 22, FP 2, Inv 0 TP 204, FN 17, Inv 0 SD Biosensor (N) n=440 TN 194, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 31, FP 0, Inv 0 TP 132, FN 72, Inv 1 Siemens (OP) n=407 TN 169, FP 0, Inv 0 TP 1, FN 1, Inv 0TN 22, FP 0, Inv 0 TP 182, FN 20, Inv 0 Siemens (N) n= 450 TN 225, FP 0, Inv 0 TP 0, FN 1, Inv 0TN 9, FP 0, Inv 0 TP 140, FN 75, Inv 0 Szybio (OP) n=411 TN 187, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 9, FP 0, Inv 0 TP 178, FN 34, Inv 3 Szybio (N) n=411 TN 187, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 9, FP 0, Inv 0 TP 40, FN 170, Inv 5 Szybio (S) n=396 TN 172, FP 0, Inv 0 TP 0, FN 0, Inv 0TN 30, FP 0, Inv 0 TP 158, FN 47, Inv 0 VivaDiag (N) n=406 TN 166, FP 0, Inv 3 TP 1, FN 1, Inv 0TN 23, FP 1, Inv 0 TP 130, FN 91, Inv 1 Wantai (OP) n=469 TN 214, FP 3, Inv 4 TP 0, FN 2, Inv 0TN 23, FP 0, Inv 0 TP 39, FN 170, Inv 0 Wantai (S) n=449 TN 206, FP 2, Inv 7 TP 0, FN 2, Inv 0TN 6, FP 1, Inv 0 TP 166, FN 41, Inv 1 Wholepower (N) n=417 TN 200, FP 0, Inv 1 TP 0, FN 1, Inv 0TN 21, FP 2, Inv 1 TP 204, FN 14, Inv 3 Wondfo (N) n=468 TN 217, FP 0, Inv 4 TP 0, FN 2, Inv 0
B
Figure 1 STARD diagram. A, retrospective study part reporting RAT results compared to RT-qPCR stratified into Cq ranges. B, pro-spective clinical study part reporting data from individuals, who were either included due to a positive RT-qPCR test for SARS-CoV-2 or being tested as part of screening for SARS-CoV-2. For each RAT the total number of tests is reported together with the distribution compared to RT-qPCR. FN false negative, FP false positive, Inv invalid RAT, TN true negative, TP true positive. N anterior nasal cavity sampling, OP deep oropharyngeal sampling, S saliva.
Figure 1B Click here to access/download;Figure;Figure 1B STARD diagram.pptx
Qlife Acro
Biosynex Ag AllTest
FujirebioNoviral N
DNA diagnosticsWondfo
CTK OnsiteWantai OP
Wantai SSiemens
QiagenLumiraDx
Acon Biosynex Ag+
Noviral SRoche OPVivaDiag
Szybio Quidel
SD BiosensorApi pharma
Roche NAbbott
BD Veritor BD Veritor N (vis)SD Biosensor OP
Szybio SLituo N
Gensure Wholepower
AUH Test Lituo S
RAT0.67 [0.60-0.73]0.42 [0.35-0.49]0.41 [0.34-0.48]0.40 [0.34-0.47]0.40 [0.33-0.46]0.37 [0.30-0.44]0.35 [0.29-0.42]0.33 [0.27-0.40]0.32 [0.26-0.38]0.31 [0.25-0.37]0.31 [0.25-0.38]0.31 [0.25-0.38]0.30 [0.23-0.36]0.30 [0.24-0.36]0.27 [0.21-0.33]0.26 [0.20-0.33]0.26 [0.21-0.33]0.26 [0.20-0.33]0.26 [0.21-0.33]0.26 [0.20-0.33]0.26 [0.20-0.32]0.25 [0.20-0.32]0.25 [0.19-0.31]0.19 [0.14-0.24]0.17 [0.11-0.22]0.17 [0.12-0.22]0.17 [0.11-0.22]0.16 [0.11-0.21]0.14 [0.10-0.19]0.13 [0.09-0.18]0.10 [0.06-0.15]0.10 [0.06-0.15]0.05 [0.03-0.09]0.03 [0.01-0.05]
Sensitivity [95%CI]
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
Sensitivity
Overall analytical sensitivity, n = 204
Figure 2 Click here to access/download;Figure;Figure 2 JCV.docx
Figure 2 Overall analytical sensitivity and specificity of 33 RAT and one SIBA-rt-PCR test. Sensitivity and specificity are reported as mean with 95% CI
and is based on 50 samples with Cq <25, 54 samples with Cq between 25 to 30, 50 samples with Cq between 30 to 35 and 50 samples with Cq >35 by
RT-qPCR.
Qlife Acro
Biosynex Ag AllTest
FujirebioNoviral N
DNA diagnosticsWondfo
CTK OnsiteWantai OP
Wantai SSiemens
QiagenLumiraDx
Acon Biosynex Ag+
Noviral SRoche OPVivaDiag
Szybio Quidel
SD BiosensorApi pharma
Roche NAbbott
BD Veritor BD Veritor N (vis)SD Biosensor OP
Szybio SLituo N
Gensure Wholepower
AUH Test Lituo S
RAT0.93 [0.88-0.98]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]
Specificity [95%CI]
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Specificity
Overall analytical specificity, n = 100
Acon N (ST)LumiraDx N (I)
Wondfo NSD Biosensor N
DNA diagnostics N (ST)Fujirebio N
Qiagen N Quidel N (I)Siemens N
Roche NCTK Onsite N
Biosynex Ag NFujirebio OP
Szybio NQiagen OP
BD Veritor N (visual)Noviral N
AUH Test N (ST)Quidel OP (I)
Wholepower NAcro OP
BD Veritor N (I)Abbott N
Biosynex Ag+ OPVivaDiag NAllTest OP
Lituo NApi pharma N
Gensure NSD Biosensor OP
Qlife N (I)Abbott OPRoche OPSzybio OP
Siemens OPWantai OP
Acro SElysium OP
Api pharma OPQlife OP (I)
Noviral SSzybio S
Wantai S (ST)Elysium S
Lituo SQuidel S (I)
RAT0.94 [0.91-0.97]0.93 [0.89-0.96]0.93 [0.89-0.96]0.92 [0.88-0.95]0.91 [0.88-0.95]0.91 [0.86-0.94]0.90 [0.85-0.94]0.90 [0.86-0.94]0.90 [0.85-0.94]0.87 [0.82-0.91]0.86 [0.81-0.90]0.84 [0.79-0.88]0.84 [0.79-0.89]0.84 [0.79-0.89]0.83 [0.78-0.88]0.81 [0.75-0.86]0.81 [0.76-0.86]0.80 [0.74-0.85]0.80 [0.75-0.86]0.80 [0.74-0.85]0.79 [0.74-0.85]0.79 [0.74-0.85]0.78 [0.72-0.83]0.77 [0.71-0.82]0.77 [0.71-0.82]0.76 [0.70-0.81]0.75 [0.70-0.81]0.74 [0.68-0.80]0.74 [0.67-0.79]0.73 [0.67-0.79]0.72 [0.66-0.78]0.68 [0.61-0.74]0.68 [0.62-0.75]0.65 [0.59-0.71]0.64 [0.58-0.71]0.59 [0.52-0.65]0.49 [0.42-0.55]0.48 [0.41-0.55]0.46 [0.39-0.53]0.32 [0.26-0.38]0.29 [0.23-0.34]0.19 [0.14-0.24]0.19 [0.14-0.24]0.13 [0.08-0.18]0.12 [0.08-0.17]0.03 [0.01-0.05]
Sensitivity [95%CI]
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Sensitivity
Overall clinical sensitivity
Figure 3 Click here to access/download;Figure;Figure 3 JCV.docx
Figure 3 Overall clinical sensitivity and specificity of 44 RAT and two SIBA-rt-PCR tests. Sensitivity and specificity are reported as mean with 95% CI. N
are anterior nasal cavity swabs, OP are deep oropharyngeal swabs and S are saliva based RAT. ST are self-test, I are instrument read-out tests and
visual means that the RAT was evaluated visually instead of by instrumental read-out.
Acon N (ST)LumiraDx N (I)
Wondfo NSD Biosensor N
DNA diagnostics N (ST)Fujirebio N
Qiagen N Quidel N (I)Siemens N
Roche NCTK Onsite N
Biosynex Ag NFujirebio OP
Szybio NQiagen OP
BD Veritor N (visual)Noviral N
AUH Test N (ST)Quidel OP (I)
Wholepower NAcro OP
BD Veritor N (I)Abbott N
Biosynex Ag+ OPVivaDiag NAllTest OP
Lituo NApi pharma N
Gensure NSD Biosensor OP
Qlife N (I)Abbott OPRoche OPSzybio OP
Siemens OPWantai OP
Acro SElysium OP
Api pharma OPQlife OP (I)
Noviral SSzybio S
Wantai S (ST)Elysium S
Lituo SQuidel S (I)
RAT1.00 [1.00-1.00]1.00 [1.00-1.00]0.99 [0.97-1.00]0.99 [0.97-1.00]0.99 [0.97-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]0.99 [0.98-1.00]1.00 [1.00-1.00]0.99 [0.98-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]0.99 [0.97-1.00]0.99 [0.98-1.00]1.00 [1.00-1.00]1.00 [0.98-1.00]1.00 [0.99-1.00]1.00 [1.00-1.00]0.98 [0.95-0.99]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [0.99-1.00]1.00 [0.98-1.00]0.98 [0.96-1.00]1.00 [1.00-1.00]0.97 [0.95-0.99]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]0.98 [0.97-1.00]0.99 [0.97-1.00]1.00 [1.00-1.00]1.00 [1.00-1.00]0.98 [0.96-1.00]0.99 [0.98-1.00]1.00 [1.00-1.00]0.99 [0.98-1.00]0.99 [0.98-1.00]0.99 [0.98-1.00]0.99 [0.98-1.00]
Specificity [95%CI]
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Specificity
Overall clinical specificity
Supplementary Data
Click here to access/downloadSupplementary Data
Supplementary data 20220211.docx
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