Journal of Clinical Medicine (Apr 2021)

Head-to-Head Evaluation of Five Automated SARS-CoV-2 Serology Immunoassays in Various Prevalence Settings

  • Diego O. Andrey,
  • Sabine Yerly,
  • Benjamin Meyer,
  • Isabelle Arm-Vernez,
  • Pascale Roux-Lombard,
  • Giuseppe Togni,
  • Idris Guessous,
  • Hervé Spechbach,
  • Silvia Stringhini,
  • Thomas Agoritsas,
  • Jérôme Stirnemann,
  • Jean-Luc Reny,
  • Claire-Anne Siegrist,
  • Isabella Eckerle,
  • Laurent Kaiser,
  • Nicolas Vuilleumier

DOI
https://doi.org/10.3390/jcm10081605
Journal volume & issue
Vol. 10, no. 8
p. 1605

Abstract

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Purpose: To assess the diagnostic performances of five automated anti-SARS-CoV-2 immunoassays, Epitope (N), Diasorin (S1/S2), Euroimmun (S1), Roche N (N), and Roche S (S-RBD), and to provide a testing strategy based on pre-test probability. Methods: We assessed the receiver operating characteristic (ROC) areas under the curve (AUC) values, along with the sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs), of each assay using a validation sample set of 172 COVID-19 sera and 185 negative controls against a validated S1-immunofluorescence as a reference method. The three assays displaying the highest AUCs were selected for further serodetection of 2033 sera of a large population-based cohort. Results: In the validation analysis (pre-test probability: 48.1%), Roche N, Roche S and Euroimmun showed the highest discriminant accuracy (AUCs: 0.99, 0.98, and 0.98) with PPVs and NPVs above 96% and 94%, respectively. In the population-based cohort (pre-test probability: 6.2%) these three assays displayed AUCs above 0.97 and PPVs and NPVs above 90.5% and 99.4%, respectively. A sequential strategy using an anti-S assay as screening test and an anti-N as confirmatory assays resulted in a 96.7% PPV and 99.5% NPV, respectively. Conclusions: Euroimmun and both Roche assays performed equally well in high pre-test probability settings. At a lower prevalence, sequentially combining anti-S and anti-N assays resulted in the optimal trade-off between diagnostic performances and operational considerations.

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