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Oxford University Press - PMC COVID-19 Collection logoLink to Oxford University Press - PMC COVID-19 Collection
. 2021 Mar 10:jfab014. doi: 10.1093/jalm/jfab014

Performance of four automated SARS-CoV-2 serology assay platforms in a large cohort including susceptible COVID-19 negative and COVID-19 positive patients

Matthew D Ward 1, Kristin E Mullins 1, Elizabeth Pickett 1, VeRonika Merrill 1, Mark Ruiz 1, Heather Rebuck 1, Show-Hong Duh 1, Robert H Christenson 1,
PMCID: PMC7989439  PMID: 33693808

Abstract

Background

Anti-SARS-CoV-2 serological responses may have a vital role in controlling the spread of the disease. However, the comparative performance of automated serological assays has not been determined in susceptible patients with significant co-morbidities.

Methods

In this study, we used a large number of COVID-19 negative patient samples (n = 2030) as well as COVID-19 positive patient samples (n = 112) to compare the performance of four serological assay platforms; Siemens Healthineers Atellica IM Analyzer, Siemens Healthineers Dimension EXL Systems, Abbott ARCHITECT, and Roche cobas.

Results

All four serology assay platforms exhibited comparable negative percent agreement with negative COVID-19 status ranging from 99.2-99.7%, and positive percent agreement from 84.8-87.5% with positive real-time reverse transcriptase polymerase chain reaction (RT-PCR) results. Of the 2142 total samples, only 38 samples (1.8%) yielded discordant results on one or more platforms. However, only 1.1% (23/2030) of COVID-19 negative cohort results was discordant whereas discordance was 10-fold higher for the COVID-19 positive cohort at 11.3% (15/112). Of the total 38 discordant results, 34 were discordant on only one platform.

Conclusion

Serology assay performance was comparable across the four platforms assessed in a large population of COVID-19 negative patients with relevant comorbidities. The pattern of discordance shows that samples were discordant on a single assay platform, and discordance rate was 10-fold higher in the COVID-19 positive population.

Impact statement

High negative percent agreement reinforces the reliability of serology testing especially in a cohort of at-risk patients. Serology platform discordance highlights the importance of a two-test strategy for properly identifying seroconverted patients.

Keywords: serology, automated platforms, COVID-19, SARS-CoV-2


Articles from The Journal of Applied Laboratory Medicine are provided here courtesy of Oxford University Press

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