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Measurement uncertainty as a tool for evaluating the ‘grey zone’ to reduce the false negatives in immunochemical screening of blood donors for infectious diseases
RISE, SP – Sveriges Tekniska Forskningsinstitut, SP Kemi Material och Ytor, Kemi.
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2016 (English)In: Accreditation and Quality Assurance, ISSN 0949-1775, E-ISSN 1432-0517, Vol. 21, no 1, 25-32 p.Article in journal (Refereed) Published
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Abstract [en]

The risk of misclassifying infected individuals as healthy constitutes a crucial challenge when screening blood donors by means of immunoassays. This risk is especially challenging when the numerical results are close to the clinical decision level, i.e. in the ‘grey zone’. The concept of using measurement uncertainty for evaluating the ‘grey zone’ has previously not been systematically applied in this context. This article explains methods, models and empirical (top-down) approaches for the calculation of measurement uncertainty using results from a blood bank according to the internationally accepted GUM principles, focusing on uncertainty sources in the analytical phase. Of the different approaches available, the intralaboratory empirical approaches are emphasised since modelling (bottom-up) approaches are impracticable due to the lack of reliable model equations for immunoassays. Different methods are applied to estimate the measurement uncertainty for the Abbott Prism® HCV immunoassay. The expanded uncertainty obtained at the clinical decision level from the intralaboratory empirical approach was 36 %. The estimated uncertainty was used to set acceptance and rejection zones following the procedure set in the Eurachem guideline, emphasising the need to minimise the occurrence of false negatives.

Place, publisher, year, edition, pages
Springer-Verlag New York, 2016. Vol. 21, no 1, 25-32 p.
Keyword [en]
blood bank, clinical decision level, cut-off value, GUM, immunoassay, measurement uncertainty, screening test, ‘grey zone’
National Category
Medical Laboratory and Measurements Technologies Probability Theory and Statistics Analytical Chemistry
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URN: urn:nbn:se:ri:diva-96DOI: 10.1007/s00769-015-1180-xScopus ID: 2-s2.0-84957938245OAI: oai:DiVA.org:ri-96DiVA: diva2:932132
Available from: 2016-05-31 Created: 2016-04-28 Last updated: 2017-11-30Bibliographically approved

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CiteExportLink to record
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  • apa
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  • de-DE
  • en-GB
  • en-US
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