Multicenter comparison of the Cobas 6800 system with the RealStar RT-PCR kit for the detection of SARS-CoV-2.


Journal

Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology
ISSN: 1873-5967
Titre abrégé: J Clin Virol
Pays: Netherlands
ID NLM: 9815671

Informations de publication

Date de publication:
Sep 2020
Historique:
received: 13 07 2020
accepted: 29 07 2020
pubmed: 10 8 2020
medline: 6 10 2020
entrez: 10 8 2020
Statut: ppublish

Résumé

RT-PCR testing is crucial in the diagnostic of SARS-CoV-2 infection. The use of reliable and comparable PCR assays is a cornerstone to allow use of different PCR assays depending on the local equipment. In this work, we provide a comparison of the Cobas® (Roche) and the RealStar® assay (Altona). Assessment of the two assays was performed prospectively in three reference Parisians hospitals, using 170 clinical samples. They were tested with the Cobas® assay, selected to obtain a distribution of cycle threshold (Ct) as large as possible, and tested with the RealStar assay with three largely available extraction platforms: QIAsymphony (Qiagen), MagNAPure (Roche) and NucliSENS-easyMag (BioMérieux). Overall, the agreement (positive for at least one gene) was 76 %. This rate differed considerably depending on the Cobas Ct values for gene E: below 35 (n = 91), the concordance was 99 %. Regarding the positive Ct values, linear regression analysis showed a coefficient of determination (R In this comparison, both RealStar® and Cobas® assays provided comparable qualitative results and a high correlation when both tests were positive. Discrepancies exist after 35 Ct and varied depending on the extraction system used for the RealStar® assay, probably due to a low viral load close to the detection limit of both assays.

Sections du résumé

BACKGROUND BACKGROUND
RT-PCR testing is crucial in the diagnostic of SARS-CoV-2 infection. The use of reliable and comparable PCR assays is a cornerstone to allow use of different PCR assays depending on the local equipment. In this work, we provide a comparison of the Cobas® (Roche) and the RealStar® assay (Altona).
METHODS METHODS
Assessment of the two assays was performed prospectively in three reference Parisians hospitals, using 170 clinical samples. They were tested with the Cobas® assay, selected to obtain a distribution of cycle threshold (Ct) as large as possible, and tested with the RealStar assay with three largely available extraction platforms: QIAsymphony (Qiagen), MagNAPure (Roche) and NucliSENS-easyMag (BioMérieux).
RESULTS RESULTS
Overall, the agreement (positive for at least one gene) was 76 %. This rate differed considerably depending on the Cobas Ct values for gene E: below 35 (n = 91), the concordance was 99 %. Regarding the positive Ct values, linear regression analysis showed a coefficient of determination (R
CONCLUSIONS CONCLUSIONS
In this comparison, both RealStar® and Cobas® assays provided comparable qualitative results and a high correlation when both tests were positive. Discrepancies exist after 35 Ct and varied depending on the extraction system used for the RealStar® assay, probably due to a low viral load close to the detection limit of both assays.

Identifiants

pubmed: 32769025
pii: S1386-6532(20)30315-2
doi: 10.1016/j.jcv.2020.104573
pmc: PMC7836314
pii:
doi:

Substances chimiques

Reagent Kits, Diagnostic 0
Viral Proteins 0

Types de publication

Comparative Study Journal Article Multicenter Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

104573

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Références

N Engl J Med. 2020 Mar 26;382(13):1199-1207
pubmed: 31995857
Euro Surveill. 2020 Feb;25(6):
pubmed: 32046815
J Clin Virol. 2020 Jul;128:104390
pubmed: 32388471
J Clin Virol. 2020 Jul;128:104412
pubmed: 32416600
Euro Surveill. 2020 Jan;25(3):
pubmed: 31992387
N Engl J Med. 2020 Feb 20;382(8):727-733
pubmed: 31978945
J Clin Virol. 2020 Jun;127:104384
pubmed: 32361285
Euro Surveill. 2020 Mar;25(9):
pubmed: 32156329

Auteurs

Marc Wirden (M)

Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, AP-HP, Hôpital Pitié-Salpêtrière, Laboratoire de virologie, Paris, France.

Linda Feghoul (L)

Université de Paris, Département des Agents Infectieux, Service de Virologie, Hôpital Saint-Louis, Paris, France; INSERM UMR 976, Université de Paris, Paris, France.

Mélanie Bertine (M)

Université de Paris, Assistance Publique - Hôpitaux de Paris, Service de virologie, Hôpital Bichat, Paris, France; UMR 1137-IAME, DeSCID: Decision SCiences in Infectious Diseases control and care, INSERM, Université de Paris, Paris, France.

Marie-Laure Nere (ML)

Université de Paris, Département des Agents Infectieux, Service de Virologie, Hôpital Saint-Louis, Paris, France.

Quentin Le Hingrat (Q)

Université de Paris, Assistance Publique - Hôpitaux de Paris, Service de virologie, Hôpital Bichat, Paris, France; UMR 1137-IAME, DeSCID: Decision SCiences in Infectious Diseases control and care, INSERM, Université de Paris, Paris, France.

Basma Abdi (B)

Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, AP-HP, Hôpital Pitié-Salpêtrière, Laboratoire de virologie, Paris, France.

David Boutolleau (D)

Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, AP-HP, Hôpital Pitié-Salpêtrière, Laboratoire de virologie, Paris, France.

Valentine Marie Ferre (VM)

Université de Paris, Assistance Publique - Hôpitaux de Paris, Service de virologie, Hôpital Bichat, Paris, France; UMR 1137-IAME, DeSCID: Decision SCiences in Infectious Diseases control and care, INSERM, Université de Paris, Paris, France.

Aude Jary (A)

Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, AP-HP, Hôpital Pitié-Salpêtrière, Laboratoire de virologie, Paris, France.

Constance Delaugerre (C)

Université de Paris, Département des Agents Infectieux, Service de Virologie, Hôpital Saint-Louis, Paris, France; INSERM UMR 944, Université de Paris, Paris, France.

Anne-Genevieve Marcelin (AG)

Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, AP-HP, Hôpital Pitié-Salpêtrière, Laboratoire de virologie, Paris, France.

Diane Descamps (D)

Université de Paris, Assistance Publique - Hôpitaux de Paris, Service de virologie, Hôpital Bichat, Paris, France; UMR 1137-IAME, DeSCID: Decision SCiences in Infectious Diseases control and care, INSERM, Université de Paris, Paris, France.

Jérôme Legoff (J)

Université de Paris, Département des Agents Infectieux, Service de Virologie, Hôpital Saint-Louis, Paris, France; INSERM UMR 976, Université de Paris, Paris, France.

Benoit Visseaux (B)

Université de Paris, Assistance Publique - Hôpitaux de Paris, Service de virologie, Hôpital Bichat, Paris, France; UMR 1137-IAME, DeSCID: Decision SCiences in Infectious Diseases control and care, INSERM, Université de Paris, Paris, France.

Marie-Laure Chaix (ML)

Université de Paris, Département des Agents Infectieux, Service de Virologie, Hôpital Saint-Louis, Paris, France; INSERM UMR 944, Université de Paris, Paris, France. Electronic address: marie-laure.chaix@aphp.fr.

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Classifications MeSH