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Development of a unit conversion tool for five quantitative anti‐spike assays and agreement analysis of three qualitative anti‐nucleocapsid assays for SARS‐CoV‐2

Serge OuobaDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanAya SugiyamaDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanKo KoDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanUlugbek Khudayberdievich MirzaevDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanKanon AbeDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanE BunthenDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanZayar PhyoDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanKobiljon Khusniddin KhalilovDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanAkemi KurisuDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanTomoyuki AkitaDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanKazuaki TakahashiDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima JapanHiroshi SasakiTadashi YamamotoJunko TanakaDepartment of Epidemiology, Infectious Disease Control and Prevention, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima Japan
ABI

Аннотация

Commercially available assays for measuring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) anti-spike (S) or anti-nucleocapsid (N) antibodies differ in units, making results comparisons challenging. This study aimed to develop conversion equations between five quantitative anti-S antibody tests and to assess the agreement over time between three qualitative anti-N antibody tests. Blood samples from 24 216 vaccinated healthcare workers in Hiroshima Prefecture, Japan, were analyzed for anti-S antibodies using five quantitative tests (Abbott, Fujirebio, Ortho, Sysmex, Roche) and for anti-N antibodies using three qualitative tests (Abbott, Sysmex, Roche). Geometric mean regression was performed to establish equations for converting measured values between the five quantitative tests. Fleiss κ statistic was used to assess the agreement between the three qualitative tests. A strong correlation (Pearson's coefficient r > 0.9) was found for each pair of the five quantitative tests measuring anti-S antibodies, enabling the development of equations to convert values between each pair. Using these equations, which are based on the original output unit of each test, values obtained from one test can be transformed to be equivalent to the corresponding values in another test. For the three tests for anti-N antibodies, the agreement was substantial in the total sample (Fleiss' κ, 0.74) and moderate among those with self-reported past coronavirus disease 2019 (COVID-19) infection (Fleiss' κ, 0.39). The agreement decreased with time after infection. Reduced agreement between anti-N antibodies tests over time suggests caution in comparing seroepidemiological studies of COVID-19 exposure based on anti-N antibodies measurement. The findings could help improve antibody measurement systems and inform public health decision-makers.

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