Dataset Information

Clinical evaluation of five different automated SARS-CoV-2 serology assays in a cohort of hospitalized COVID-19 patients.

ABSTRACT: BACKGROUND:The global market for SARS-CoV-2-immunoassays is becoming ever more crowded with antibody-tests of various formats, targets and technologies, careful evaluation is crucial for understanding the implications of individual test results. Here, we evaluate the clinical performance of five automated immunoassays on a set of clinical samples. METHODS:Serum/plasma samples of 75 confirmed COVID-19 patients and 320 pre-pandemic serum samples of healthy blood donors were subjected to two IgG and three total antibody SARS-CoV-2-immunoassays. All test setups were automated workflows. RESULTS:Positivity of assays (onset of symptoms > 10 days) ranged between 68.4 % and 81.6 % (Diasorin 68.4 %, Euroimmun 70.3 %, Siemens 73.7 %, Roche 79.0 % and Wantai 81.6 %). All examined assays demonstrated high specificity of >99 % (Euroimmun, Diasorin: 99.1 %, Wantai: 99.4 %) but only two reached levels above 99.5 % (Roche: 99.7 %, Siemens 100 %). Interestingly, there was no overlap in false positive results between the assays. The strongest correlation of quantitative results was observed between the Diasorin and Euroimmun IgG tests (r2?=?0.76). Overall, we observed no difference in the distribution of test results between female and male patients (p-values: 0.18-0.87). A significant difference between severely versus critically ill patients was demonstrated for the Euroimmun, Diasorin, Wantai and Siemens assays (p-values:0.041). CONCLUSION:All assays showed good clinical performance. Our data confirm that orthogonal test strategies as recommended by the CDC can enhance clinical specificity. However, the suboptimal rates of test positivity found at time of hospitalization in this cohort underline the importance of molecular diagnostics to rule out/confirm active infection with SARS-CoV-2.

SUBMITTER: Pfluger LS

PROVIDER: S-EPMC7367003 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Clinical evaluation of five different automated SARS-CoV-2 serology assays in a cohort of hospitalized COVID-19 patients.

Pflüger Lisa Sophie LS Bannasch Johannes H JH Brehm Thomas Theo TT Pfefferle Susanne S Hoffmann Armin A Nörz Dominik D van der Meirschen Marc M Kluge Stefan S Haddad Munif M Pischke Sven S Hiller Jens J Addo Marylyn M MM Lohse Ansgar W AW Schulze Zur Wiesch Julian J Peine Sven S Aepfelbacher Martin M Lütgehetmann Marc M

Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology 20200717

<h4>Background</h4>The global market for SARS-CoV-2-immunoassays is becoming ever more crowded with antibody-tests of various formats, targets and technologies, careful evaluation is crucial for understanding the implications of individual test results. Here, we evaluate the clinical performance of five automated immunoassays on a set of clinical samples.<h4>Methods</h4>Serum/plasma samples of 75 confirmed COVID-19 patients and 320 pre-pandemic serum samples of healthy blood donors were subjecte ...[more]

PMID: 32763809

Similar Datasets

Project description:BackgroundSerological testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) complements nucleic acid tests for patient diagnosis and enables monitoring of population susceptibility to inform the coronavirus disease 2019 (COVID-19) pandemic response. It is important to understand the reliability of assays with different antigen or antibody targets to detect humoral immunity after SARS-CoV-2 infection and to understand how antibody (Ab) binding assays compare to those detecting neutralizing antibody (nAb), particularly as we move into the era of vaccines.MethodsWe evaluated the performance of 6 commercially available enzyme-linked immunosorbent assays (ELISAs), including a surrogate virus neutralization test (sVNT), for detection of SARS-CoV-2 immunoglobulins (IgA, IgM, IgG), total or nAb. A result subset was compared with a cell culture-based microneutralization (MN) assay. We tested sera from patients with prior reverse transcription polymerase chain reaction-confirmed SARS-CoV-2 infection, prepandemic sera, and potential cross-reactive sera from patients with other non-COVID-19 acute infections.ResultsFor sera collected >14 days post-symptom onset, the assay achieving the highest sensitivity was the Wantai total Ab at 100% (95% CI, 94.6%-100%), followed by 93.1% for Euroimmun NCP-IgG, 93.1% for GenScript sVNT, 90.3% for Euroimmun S1-IgG, 88.9% for Euroimmun S1-IgA, and 83.3% for Wantai IgM. Specificity for the best-performing assay was 99.5% for the Wantai total Ab, and for the lowest-performing assay it was 97.1% for sVNT (as per the Instructions for Use [IFU]). The Wantai Total Ab had the best agreement with MN at 98% followed by Euroimmun S1-IgA, Euro NCP-IgG, and sVNT (as per IFU) with 97%, 97% and 95%, respectively; Wantai IgM had the poorest agreement at 93%.ConclusionsPerformance characteristics of the SARS-CoV-2 serology assays detecting different antibody types are consistent with those found in previously published reports. Evaluation of the surrogate virus neutralization test in comparison to the Ab binding assays and a cell culture-based neutralization assay showed good result correlation between all assays. However, correlation between the cell-based neutralization test and some assays detecting Ab's not specifically involved in neutralization was higher than with the sVNT. This study demonstrates the reliability of different assays to detect the humoral immune response following SARS-CoV-2 infection, which can be used to optimize serological test algorithms for assessing antibody responses post-SARS-CoV-2 infection or vaccination.

Dataset Information

Clinical evaluation of five different automated SARS-CoV-2 serology assays in a cohort of hospitalized COVID-19 patients.

Publications

Clinical evaluation of five different automated SARS-CoV-2 serology assays in a cohort of hospitalized COVID-19 patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets