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Increasing test specificity without impairing sensitivity: lessons learned from SARS-CoV-2 serology
  1. Thomas Perkmann1,
  2. Thomas Koller1,
  3. Nicole Perkmann-Nagele1,
  4. Maria Ozsvar-Kozma1,
  5. David Eyre2,
  6. Philippa Matthews3,
  7. Abbie Bown4,
  8. Nicole Stoesser3,
  9. Marie-Kathrin Breyer5,6,
  10. Robab Breyer-Kohansal5,6,
  11. Otto C Burghuber6,7,
  12. Slyvia Hartl5,6,7,
  13. Daniel Aletaha8,
  14. Daniela Sieghart8,
  15. Peter Quehenberger1,
  16. Rodrig Marculescu1,
  17. Patrick Mucher1,
  18. Astrid Radakovics1,
  19. Miriam Klausberger9,
  20. Mark Duerkop10,
  21. Barba Holzer11,
  22. Boris Hartmann11,
  23. Robert Strassl1,
  24. Gerda Leitner12,
  25. Florian Grebien13,
  26. Wilhelm Gerner14,15,16,
  27. Reingard Grabherr9,
  28. Oswald F Wagner1,
  29. Christoph J Binder1,
  30. Helmuth Haslacher1
  1. 1Department of Laboratory Medicine, Medical University of Vienna, Wien, Austria
  2. 2Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK
  3. 3Nuffield Department of Medicine, University of Oxford, Oxford, UK
  4. 4Public Health England Porton Down, Salisbury, UK
  5. 5Department of Respiratory and Critical Care Medicine, Clinic Penzing, Vienna, Austria
  6. 6Ludwig Boltzmann Institute for Lung Health, Vienna, Austria
  7. 7Sigmund Freud Private University Vienna, Vienna, Austria
  8. 8Division of Rheumatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria
  9. 9Institute of Molecular Biotechnology, Department of Biotechnology, University of Natural Resources and Life Sciences (BOKU) Vienna, Vienna, Austria
  10. 10Institute of Bioprocess Science and Engineering, Department of Biotechnology, University of Natural Resources and Life Sciences (BOKU) Vienna, Vienna, Austria
  11. 11Institute for Veterinary Disease Control, Austrian Agency for Health and Food Safety (AGES), Moedling, Austria
  12. 12Department of Blood Group Serology and Transfusion Medicine, Medical University of Vienna, Vienna, Austria
  13. 13Institute for Medical Biochemistry, University of Veterinary Medicine Vienna, Vienna, Austria
  14. 14Institute of Immunology, University of Veterinary Medicine Vienna, Vienna, Austria
  15. 15Christian Doppler Laboratory for an Optimized Prediction of Vaccination Success in Pigs, University of Veterinary Medicine Vienna, Vienna, Austria
  16. 16The Pirbright Institute, Pirbright, UK (current)
  1. Correspondence to Dr Helmuth Haslacher, Department of Laboratory Medicine, Medical University of Vienna, Wien 1090, Austria; helmuth.haslacher{at}meduniwien.ac.at

Abstract

Background 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.

  • serology
  • allergy and immunology
  • medical laboratory science

Data availability statement

Data are available upon reasonable request. Data are available to interested researchers upon request from the corresponding author.

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Data availability statement

Data are available upon reasonable request. Data are available to interested researchers upon request from the corresponding author.

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Footnotes

  • Handling editor Tahir S Pillay.

  • Contributors TP and TK contributed equally. Conceptualisation: TP, TK, OFW, HH. Methodology: TP, TK, NP-N, HH; investigation: TP, TK, NP-N, MO-K, DWE, PM, AB, NS, M-LB, RB-K, OCB, SH, DA, DS, PQ, RM, PM, AR, MK, MD, BHo, BHa, RS, GL, FG, WG, RG, HH; data curation: TP, TK, DW, PM, AB, NS, M-LB, RB-K, OCB, SH, DA, DS; project administration: PM, AR; formal analysis: HH; validation: DWE, PM, AB, NS; writing—original draft: TP, TK, NP-N, HH; visualisation: HH; supervision: OFW, CJB, HH; resources: DWE, PM, AB, NS, M-LB, RB-K, OCB, SH, DA, DS, PQ, RM, MK, MD, BHo, BHa, RS, GL, FG, WG, RG, OFW, CJB; writing—review and editing: all authors; guarantor: HH.

  • Funding The MedUni Wien Biobank is funded to participate in the biobank consortium BBMRI.at (www.bbmri.at) by the Austrian Federal Ministry of Science, Research and Technology. There was no external funding received for the work presented. However, test kits for the Technoclone ELISAs were kindly provided by the manufacturer.

  • Competing interests NP-N received a travel grant from DiaSorin. DWE reports lecture fees from Gilead outside the submitted work. OCB reports grants from GSK, grants from Menarini, grants from Boehringer Ingelheim, grants from Astra, grants from MSD, grants from Pfizer, and grants from Chiesi, outside the submitted work. SH does receive unrestricted research grants (GSK, Boehringer, Menarini, Chiesi, Astra Zeneca, MSD, Novartis, Air Liquide, Vivisol, Pfizer, TEVA) for the Ludwig Boltzmann Institute of COPD and Respiratory Epidemiology, and is on advisory boards for G. SK, Boehringer Ingelheim, Novartis, Menarini, Chiesi, Astra Zeneca, MSD, Roche, Abbvie, Takeda and TEVA for respiratory oncology and COPD. PQ is an advisory board member for Roche Austria and reports personal fees from Takeda outside the submitted work. The Dept. of Laboratory Medicine (Head: OWF) received compensations for advertisement on scientific symposia from Roche, DiaSorin, and Abbott and holds a grant for evaluating an in-vitro diagnostic device from Roche. CJB is a Board Member of Technoclone. HH receives compensations for biobank services from Glock Health Science and Research and BlueSky immunotherapies.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.