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Objectives: Development and implementation of SARS-CoV-2 serologic assays gained momentum. Laboratories keep on investigating the performance of these assays. In this study, we compared three fully automated SARS-CoV-2 antibody assays. Methods: A total of 186 samples from 84 PCR-positive COVID-19 patients and 120 control samples taken before the SARS-CoV-2 pandemic were analyzed using commercial serologic assays from Roche, Siemens and DiaSorin. Time after the positive COVID-19 PCR result and onset of symptoms was retrieved from the medical record. An extended golden standard, using the result of all three assays was defined, judging if antibodies are present or absent in a sample. Diagnostic and screening sensitivity/specificity and positive/negative predictive value were calculated. Results: Diagnostic sensitivity (ability to detect a COVID-19 positive patient) ≥14 days after positive PCR testing was 96.7% (95% CI 88.5–99.6%) for DiaSorin, 93.3% (95% CI 83.8–98.2%) for Roche and 100% (95% CI 94.0–100%) for Siemens. Lower diagnostic sensitivities were observed <14 days after onset of symptoms for all three assay. Diagnostic specificity (ability to detect a COVID-19 negative patient) was 95.0% (95% CI 89.4–98.1%) for DiaSorin, 99.2% (95% CI 95.4–99.9%) for Roche and 100% (95% CI 97.0–100%) for Siemens. The sensitivity/specificity for detecting antibodies (ability of detecting absence (specificity) or presence (sensitivity) of COVID-19 antibodies) was 92.4% (95% CI 86.4–96.3%)/94.9% (95% CI 90.5–97.6%) for DiaSorin, 97.7% (95% CI 93.5–99.5%)/97.1% (95% CI 93.5–99.1%) for Roche and 98.5% (95% CI 94.6–99.8)/97.1 (95% CI 93.5–99.1%) for Siemens. Conclusions: This study revealed acceptable performance for all three assays. An orthogonal testing algorithm using the Siemens and Roche assay achieved the highest positive predictive values for antibody detection in low seroprevalence settings. [ABSTRACT FROM AUTHOR]

From early 2020, a high demand for SARS-CoV-2 tests was driven by several testing indications, including asymptomatic cases, resulting in the massive roll-out of PCR assays to combat the pandemic. Considering the dynamic of viral shedding during the course of infection, the demand to report cycle threshold (Ct) values rapidly emerged. As Ct values can be affected by a number of factors, we considered that harmonization of semi-quantitative PCR results across laboratories would avoid potential divergent interpretations, particularly in the absence of clinical or serological information. A proposal to harmonize reporting of test results was drafted by the National Reference Centre (NRC) UZ/KU Leuven, distinguishing four categories of positivity based on RNA copies/mL. Pre-quantified control material was shipped to 124 laboratories with instructions to setup a standard curve to define thresholds per assay. For each assay, the mean Ct value and corresponding standard deviation was calculated per target gene, for the three concentrations (10 7 , 10 5 and 10 3 copies/mL) that determine the classification. The results of 17 assays are summarized. This harmonization effort allowed to ensure that all Belgian laboratories would report positive PCR results in the same semi-quantitative manner to clinicians and to the national database which feeds contact tracing interventions.

Objectives: Development and implementation of SARS-CoV-2 serologic assays gained momentum. Laboratories keep on investigating the performance of these assays. In this study, we compared three fully automated SARS-CoV-2 antibody assays., Methods: A total of 186 samples from 84 PCR-positive COVID-19 patients and 120 control samples taken before the SARS-CoV-2 pandemic were analyzed using commercial serologic assays from Roche, Siemens and DiaSorin. Time after the positive COVID-19 PCR result and onset of symptoms was retrieved from the medical record. An extended golden standard, using the result of all three assays was defined, judging if antibodies are present or absent in a sample. Diagnostic and screening sensitivity/specificity and positive/negative predictive value were calculated., Results: Diagnostic sensitivity (ability to detect a COVID-19 positive patient) ≥14 days after positive PCR testing was 96.7% (95% CI 88.5-99.6%) for DiaSorin, 93.3% (95% CI 83.8-98.2%) for Roche and 100% (95% CI 94.0-100%) for Siemens. Lower diagnostic sensitivities were observed <14 days after onset of symptoms for all three assay. Diagnostic specificity (ability to detect a COVID-19 negative patient) was 95.0% (95% CI 89.4-98.1%) for DiaSorin, 99.2% (95% CI 95.4-99.9%) for Roche and 100% (95% CI 97.0-100%) for Siemens. The sensitivity/specificity for detecting antibodies (ability of detecting absence (specificity) or presence (sensitivity) of COVID-19 antibodies) was 92.4% (95% CI 86.4-96.3%)/94.9% (95% CI 90.5-97.6%) for DiaSorin, 97.7% (95% CI 93.5-99.5%)/97.1% (95% CI 93.5-99.1%) for Roche and 98.5% (95% CI 94.6-99.8)/97.1 (95% CI 93.5-99.1%) for Siemens., Conclusions: This study revealed acceptable performance for all three assays. An orthogonal testing algorithm using the Siemens and Roche assay achieved the highest positive predictive values for antibody detection in low seroprevalence settings.