Abstract
Background
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.
Methods
We compared the performance of the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays using 179 negative subjects to determine negative percent agreement (NPA) and in 60 SARS-CoV-2 PCR confirmed positive patients to determine positive percent agreement (PPA) at three different timeframes following a positive SARS-CoV-2 PCR result.
Results
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%.
Conclusions
Our data demonstrates that the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays have similar clinical performance. We demonstrated a low false positive rate across all three 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.
Keywords: SARS-CoV-2, predictive values, prevalence, serology, diagnosis, COVID-19