Multicenter Evaluation of the Clinical Performance and the Neutralizing Antibody Activity Prediction Properties of ten high throughput serological assays used in Clinical Laboratories

As the COVID-19 pandemic second wave is emerging, it is of the upmost importance to screen the population immunity in order to keep track of infected individuals. Consequently, SARS-CoV-2 immunoassays with high specificity and positive predictive values are needed to obtain an accurate epidemiological picture. As more data accumulate about the immune responses and the kinetics of neutralizing antibody (nAb) production in SARS-CoV-2 infected individuals, new applications are forecasted for serological assays such as nAb activity prediction in convalescent plasma from recovered patients. This multicenter study, involving six hospital centres, determined the baseline clinical performances, reproducibility and nAb level correlations of ten commercially available immunoassays. In addition, three lateral flow chromatography assays were evaluated as these devices can be used in logistically challenged area. All assays were evaluated using the same patient panels in duplicate thus enabling accurate comparison of the tests. Seven immunoassays examined in this study were shown to have excellent specificity (98 to 100%) and good to excellent positive predictive values (82 to 100%) when used in a low (5%) seroprevalence setting. We observed sensitivity values as low as 74% and as high as 95% at ≥15 days post symptom onset. The determination of optimized cut-off values through ROC curves analyses had a significant impact on the diagnostic resolution of several enzyme immunoassays by increasing the sensitivity significantly without a large trade-off in specificity. We found that Spike-based immunoassays seems to be better correlates of nAb activity. Finally, the results reported here will add up to the general knowledge of the inter-laboratory reproducibility of clinical performance parameters of immunoassays and provide new evidence about nAb activity prediction.
Auteurs (Zotero)
Therrien, C.; Serhir, B.; Bélanger-Collard, M.; Skrzypczak, J.; Shank, D. K.; Renaud, C.; Girouard, J.; Loungnarath, V.; Carrier, M.; Brochu, G.; Tourangeau, F.; Gilfix, B.; Piche, A.; Bazin, R.; Guérin, R.; Lavoie, M.; Martel-Laferrière, V.; Fortin, C.; Benoit, A.; Marcoux, D.; Gauthier, N.; Laumaea, A. M.; Gasser, R.; Finzi, A.; Roger, M.
Date de publication (Zotero)
décembre, 2020