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. 2015 Aug:69:81-5.
doi: 10.1016/j.jcv.2015.05.022. Epub 2015 May 30.

First international external quality assessment of molecular diagnostics for Mers-CoV

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First international external quality assessment of molecular diagnostics for Mers-CoV

Suzan D Pas et al. J Clin Virol. 2015 Aug.

Abstract

Background: Since the discovery of Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012, diagnostic protocols were quickly published and deployed globally.

Objectives: We set out to assess the quality of MERS-CoV molecular diagnostics worldwide.

Study design: Both sensitivity and specificity were assessed using 12 samples containing different viral loads of MERS-CoV or common coronaviruses (OC43, 229E, NL63, HKU1).

Results: The panel was sent to more than 106 participants, of which 99 laboratories from 6 continents returned 189 panel results.Scores ranged from 100% (84 laboratories) to 33% (1 laboratory). 15% of respondents reported quantitative results, 61% semi-quantitative (Ct-values or time to positivity) and 24% reported qualitative results. The major specific technique used was real-time RT-PCR using the WHO recommended targets upE, ORF1a and ORF1b. The evaluation confirmed that RT-PCRs targeting the ORF1b are less sensitive, and therefore not advised for primary diagnostics.

Conclusions: The first external quality assessment MERS-CoV panel gives a good insight in molecular diagnostic techniques and their performances for sensitive and specific detection of MERS-CoV RNA globally. Overall, all laboratories were capable of detecting MERS-CoV with some differences in sensitivity. The observation that 8% of laboratories reported false MERS-CoV positive single assay results shows room for improvement, and the importance of using confirmatory targets.

Keywords: Diagnosis; EQA; MERS-CoV; Molecular; QPCR; Quality control; Real-time RT-PCR; Viral load.

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Figures

Fig. 1
Fig. 1
World map of MERS-CoV EQA participants per country. formula imagen = 1; formula imagen = 2; formula imagen = 3; formula imagen = 5; formula imagen = 12.

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