Multi-Platform Comparison of SARS-CoV-2 Serology Assays for the Detection of COVID-19
COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel beta-coronavirus that is responsible for the 2019 coronavirus pandemic. Acute infections should be diagnosed by polymerase chain reaction (PCR) based tests, but serology tests can demonstrate previous exp...
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Published in | The Journal of Applied Laboratory Medicine Vol. 5; no. 6; p. 1324 |
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Main Authors | , , , , , |
Format | Journal Article Web Resource |
Language | English |
Published |
England
Oxford University Press
01.11.2020
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Subjects | |
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Abstract | COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel beta-coronavirus that is responsible for the 2019 coronavirus pandemic. Acute infections should be diagnosed by polymerase chain reaction (PCR) based tests, but serology tests can demonstrate previous exposure to the virus.
We compared the performance of the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays using 179 negative participants to determine negative percentage agreement (NPA) and in 60 SARS-CoV-2 PCR-confirmed positive patients to determine positive percentage agreement (PPA) at 3 different time frames following a positive SARS-CoV-2 PCR result.
At ≥15 days, the PPA (95% CI) was 100 (86.3-100)% for the Diazyme IgM/IgG panel, 96.0 (79.7-99.9)% for the Roche total Ig assay, and 100 (86.3-100)% for the Abbott IgG assay. The NPA (95% CI) was 98.3 (95.2-99.7)% for the Diazyme IgM/IgG panel, 99.4 (96.9-100)% for the Roche total Ig assay, and 98.9 (96.0-99.9)% for the Abbott IgG assay. When the Roche total Ig assay was combined with either the Diazyme IgM/IgG panel or the Abbott IgG assay, the positive predictive value was 100% while the negative predictive value remained greater than 99%.
Our data demonstrates that the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays have similar clinical performances. We demonstrated a low false-positive rate across all 3 platforms and observed that false positives observed on the Roche platform are unique compared to those observed on the Diazyme or Abbott assays. Using multiple platforms in tandem increases the PPVs, which is important when screening populations with low disease prevalence. |
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AbstractList | COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel beta-coronavirus that is responsible for the 2019 coronavirus pandemic. Acute infections should be diagnosed by polymerase chain reaction (PCR) based tests, but serology tests can demonstrate previous exposure to the virus.
We compared the performance of the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays using 179 negative participants to determine negative percentage agreement (NPA) and in 60 SARS-CoV-2 PCR-confirmed positive patients to determine positive percentage agreement (PPA) at 3 different time frames following a positive SARS-CoV-2 PCR result.
At ≥15 days, the PPA (95% CI) was 100 (86.3-100)% for the Diazyme IgM/IgG panel, 96.0 (79.7-99.9)% for the Roche total Ig assay, and 100 (86.3-100)% for the Abbott IgG assay. The NPA (95% CI) was 98.3 (95.2-99.7)% for the Diazyme IgM/IgG panel, 99.4 (96.9-100)% for the Roche total Ig assay, and 98.9 (96.0-99.9)% for the Abbott IgG assay. When the Roche total Ig assay was combined with either the Diazyme IgM/IgG panel or the Abbott IgG assay, the positive predictive value was 100% while the negative predictive value remained greater than 99%.
Our data demonstrates that the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays have similar clinical performances. We demonstrated a low false-positive rate across all 3 platforms and observed that false positives observed on the Roche platform are unique compared to those observed on the Diazyme or Abbott assays. Using multiple platforms in tandem increases the PPVs, which is important when screening populations with low disease prevalence. |
Author | Reed, Sharon L Hoffman, Melissa A Suhandynata, Raymond T Kelner, Michael J Fitzgerald, Robert L McLawhon, Ronald W |
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Keywords | COVID-19 prevalence diagnosis SARS-CoV-2 predictive values serology |
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SubjectTerms | Antibodies, Viral - blood Antibodies, Viral - immunology Antibodies, Viral - isolation & purification Betacoronavirus - immunology Betacoronavirus - isolation & purification Clinical Laboratory Techniques - instrumentation Clinical Laboratory Techniques - statistics & numerical data Coronavirus Infections - blood Coronavirus Infections - diagnosis Coronavirus Infections - immunology Coronavirus Infections - virology COVID-19 COVID-19 Testing False Negative Reactions False Positive Reactions Humans Immunoglobulin G - blood Immunoglobulin G - immunology Immunoglobulin G - isolation & purification Longitudinal Studies Pandemics Pneumonia, Viral - blood Pneumonia, Viral - diagnosis Pneumonia, Viral - immunology Pneumonia, Viral - virology Predictive Value of Tests Reagent Kits, Diagnostic - statistics & numerical data SARS-CoV-2 Serologic Tests - instrumentation Serologic Tests - statistics & numerical data Time Factors |
Title | Multi-Platform Comparison of SARS-CoV-2 Serology Assays for the Detection of COVID-19 |
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