Increasing test specificity without impairing sensitivity: lessons learned from SARS-CoV-2 serology
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Abstract
Serological tests are widely used in various medical disciplines for diagnostic and monitoring purposes. Unfortunately, the sensitivity and specificity of test systems are often poor, leaving room for false-positive and false-negative results. However, conventional methods were used to increase specificity and decrease sensitivity and vice versa. Using SARS-CoV-2 serology as an example, we propose here a novel testing strategy: the ‘sensitivity improved two-test’ or ‘SIT²’ algorithm.
Methods
SIT² involves confirmatory retesting of samples with results falling in a predefined retesting zone of an initial screening test, with adjusted cut-offs to increase sensitivity. We verified and compared the performance of SIT² to single tests and orthogonal testing (OTA) in an Austrian cohort (1117 negative, 64 post-COVID-positive samples) and validated the algorithm in an independent British cohort (976 negatives and 536 positives).
Results
The specificity of SIT² was superior to single tests and non-inferior to OTA. The sensitivity was maintained or even improved using SIT² when compared with single tests or OTA. SIT² allowed correct identification of infected individuals even when a live virus neutralisation assay could not detect antibodies. Compared with single testing or OTA, SIT² significantly reduced total test errors to 0.46% (0.24–0.65) or 1.60% (0.94–2.38) at both 5% or 20% seroprevalence.
Conclusion
For SARS-CoV-2 serology, SIT² proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases.
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SciScore for 10.1101/2020.11.05.20226449: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Consent: All included participants gave written informed consent to donate their samples for scientific purposes.
IRB: It was reviewed and approved by the ethics committee of the Medical University of Vienna (1424/2020).Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Antibodies Sentences Resources Calibrators and controls of both tests are traceable to a specific antibody against the SARS-CoV-2 receptor-binding domain (CR3022). SARS-CoV-2 receptor-binding domain (CR3022suggested: NoneSoftware and Algorithms Sentences Resources The Abbott SARS-CoV-2 assay detects IgG-antibodies against … SciScore for 10.1101/2020.11.05.20226449: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Consent: All included participants gave written informed consent to donate their samples for scientific purposes.
IRB: It was reviewed and approved by the ethics committee of the Medical University of Vienna (1424/2020).Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Antibodies Sentences Resources Calibrators and controls of both tests are traceable to a specific antibody against the SARS-CoV-2 receptor-binding domain (CR3022). SARS-CoV-2 receptor-binding domain (CR3022suggested: NoneSoftware and Algorithms Sentences Resources The Abbott SARS-CoV-2 assay detects IgG-antibodies against NC in a chemiluminescence microparticle assay (CMIA) on Abbott ARCHITECT® i2000sr platforms (Abbott Laboratories, Chicago, USA). Abbottsuggested: (Abbott, RRID:SCR_010477)Abbott Laboratoriessuggested: NoneResults 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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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.
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