Use of serology immunoassays for predicting SARS-CoV-2 infection: a serology-based diagnostic algorithm

  1. Alejandro Lazo-Langner
  2. Benjamin Chin-Yee
  3. Jaryd Tong
  4. Lori Lowes
  5. Benjamin D. Hedley
  6. Michael Silverman
  7. Johan Delport
  8. Vipin Bhayana
  9. Michael Knauer
  10. Ian Chin-Yee

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Abstract

Background

Detection of viral RNA by nucleic acid amplification testing (NAAT) remains the gold standard for diagnosis of SARS-CoV-2 infection but is limited by high cost and other factors. Whether serology-based assays can be effectively incorporated into a diagnostic algorithm remains to be determined. Herein we describe the development of a serology-based testing algorithm for SARS-CoV-2 infection.

Patients and Methods

Between July 2020 and February 2021, we included symptomatic unvaccinated patients evaluated in the Emergency Department of our institution for suspected SARS-CoV-2. All patients had testing by real-time Reverse Transcription Polymerase Chain Reaction. The performance characteristics of five commercial enzymatic serology assays testing for different antibody isotypes were evaluated in a derivation cohort and the assay with the best performance was further tested on a validation cohort. Optimal cut-off points were determined using receiver operating characteristic (ROC) curves and further tested using logistic regression.

Results

The derivation and validations cohorts included 72 and 319 patients, respectively. Based on its initial performance, the Elecsys Anti-SARS-CoV-2 assay (Roche Diagnostics) was further tested in the validation cohort. Using ROC curve analysis, we estimated the diagnostic performance for different cut-off points assuming a prevalence of positive tests of 5%. At any given cut-off point the NPV was over 97%.

Discussion

This study suggests that an initial diagnostic strategy using the Elecsys Anti-SARS-CoV-2 serology test in symptomatic unvaccinated patients could help to rule out an acute SARS-CoV2 infection and potentially lead to appropriately tailored infection control measures or rational guidance for further testing with a potential cost reduction and increased availability.

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  1. ScreenIT

    SciScore for 10.1101/2021.10.23.21265429: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: 2.1 Study Design and population: This study was conducted at a tertiary care centre in Ontario, Canada, after approval by the institutional Research Ethics Board.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    BlindingSARS-CoV-2 testing: Serology and NAAT testing were performed in independent laboratories in a blinded fashion.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses were conducted using SPSS 22.0 software (IBM Corp.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    Armonk NY, USA) and MedCalc Statistical Software version 19.2.6
    MedCalc
    suggested: (MedCalc, RRID:SCR_015044)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    These limitations are particularly important in resource-constrained settings. Over 18 months since the onset of the COVID-19 pandemic, as cases of COVID-19 continue to spread worldwide there remains a strong need for rapid, readily available diagnostic testing for SARS-CoV-2 infection. In this study, our findings suggest that by lowering the manufacturers’ recommended cut-off values for commercially available anti-SARS-CoV-2 antibodies serology we can accurately predict negative NAAT testing. In our population we would have had 77.4% (95% CI 72.5-81.7) of the samples categorized as highly likely to be negative by NAAT testing. Based on this data, we propose a ‘serology-first’ diagnostic algorithm that can be used to rule out SARS-CoV-2 infection in unvaccinated symptomatic patients presenting to the ED. This serology-based diagnostic algorithm offers a lower cost alternative to universal NAAT testing, in addition to rapid turnaround times to enable efficient triage, clinical management and infection control. Such an algorithm could be used to facilitate more judicious use of NAAT-based testing, contributing to more effective utilization of hospital resources, minimize healthcare worker exposure risk and nosocomial spread. These findings could have significant implications for the diagnosis and management of SARS-CoV-2 infection in acute care settings. The high NPV of the serologic testing would not only reduce the need for NAAT testing but could allow early identification of...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2021.10.23.21265429v1 on medRxiv