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Selecting COVID-19 Convalescent Plasma for Neutralizing Antibody Potency Using a High-capacity SARS-CoV-2 Antibody Assay (preprint)
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.08.31.20184895
ABSTRACT
BACKGROUNDEfficacy of COVID-19 convalescent plasma (CCP) to treat COVID-19 is hypothesized to be associated with the concentration of neutralizing antibodies (nAb) to SARS-CoV-2. High capacity serologic assays detecting binding antibodies (bAb) have been developed, nAb assays are not adaptable to high-throughput testing. We sought to determine the effectiveness of using surrogate bAb signal-to-cutoff ratios (S/CO) in predicting nAb titers using a pseudovirus reporter viral particle neutralization (RVPN) assay. METHODSCCP donor serum collected by 3 US blood collectors was tested with a bAb assay (Ortho Clinical Diagnostics VITROS Anti-SARS-CoV-2 Total, CoV2T) and a nAb RVPN assay. CoV2T prediction effectiveness at S/CO thresholds was evaluated for RVPN nAb NT50 titers using receiver operating characteristic analysis. RESULTS753 CCPs were tested with median CoV2T S/CO of 71.2 and median NT50 of 527.5. Proportions of CCP donors with NT50 over various target nAb titers were 86% [≥]180, 76% [≥]1160, and 62%[≥]1320. Increasing CoV2Ts reduced the sensitivity to predict NT50 titers, while specificity to identify those below thresholds increased. As the targeted NT50 increased, the positive predictive value fell with reciprocal increase in negative predictive value. S/CO thresholds were thus less able to predict target NT50 titers. CONCLUSIONSelection of a clinically effective nAb titer will impact availability of CCP. Product release with CoV2T assay S/CO thresholds must balance the risk of releasing products below target nAb titers with the cost of false negatives. A two-step testing scheme may be optimal, with nAb testing on CoV2T samples with S/COs below thresholds.
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Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2020 Document Type: Preprint

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Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2020 Document Type: Preprint