Multi-site clinical validation of Isothermal Amplification based SARS-COV-2 detection assays using different sampling strategies.


Journal

medRxiv : the preprint server for health sciences
Titre abrégé: medRxiv
Pays: United States
ID NLM: 101767986

Informations de publication

Date de publication:
06 Jul 2021
Historique:
entrez: 16 7 2021
pubmed: 17 7 2021
medline: 17 7 2021
Statut: epublish

Résumé

Isothermal amplification-based tests were developed as rapid, low-cost, and simple alternatives to real-time reverse transcriptase-polymerase chain reaction (RT-PCR) tests for SARS-COV-2 detection. Clinical performance of two isothermal amplification-based tests (Atila Biosystems iAMP COVID-19 detection test and OptiGene COVID-19 Direct Plus RT-LAMP test) was compared to clinical RT-PCR assays using different sampling strategies. A total of 1378 participants were tested across four study sites. Compared to standard of care RT-PCR testing, the overall sensitivity and specificity of the Atila iAMP test for detection of SARS-CoV-2 were 76.2% and 94.9%, respectively, and increased to 88.8% and 89.5%, respectively, after exclusion of an outlier study site. Sensitivity varied based on the anatomic collected site. Sensitivity for nasopharyngeal was 65.4% (range across study sites:52.8%-79.8%), mid-turbinate 88.2%, saliva 55.1% (range across study sites:42.9%-77.8%) and anterior nares 66.7% (range across study sites:63.6%-76.5%). The specificity for these anatomic collection sites ranged from 96.7% to 100%. Sensitivity improved in symptomatic patients (overall 82.7%) and those with a higher viral load (overall 92.4% for ct≤25). Sensitivity and specificity of the OptiGene Direct Plus RT-LAMP test, conducted at a single study-site, were 25.5% and 100%, respectively. The Atila iAMP COVID test with mid-turbinate sampling is a rapid, low-cost assay for detecting SARS-COV-2, especially in symptomatic patients and those with a high viral load, and could be used to reduce the risk of SARS-COV-2 transmission in clinical settings. Variation of performance between study sites highlights the need for site-specific clinical validation of these assays before clinical adoption.

Sections du résumé

BACKGROUND BACKGROUND
Isothermal amplification-based tests were developed as rapid, low-cost, and simple alternatives to real-time reverse transcriptase-polymerase chain reaction (RT-PCR) tests for SARS-COV-2 detection.
METHODS METHODS
Clinical performance of two isothermal amplification-based tests (Atila Biosystems iAMP COVID-19 detection test and OptiGene COVID-19 Direct Plus RT-LAMP test) was compared to clinical RT-PCR assays using different sampling strategies. A total of 1378 participants were tested across four study sites.
RESULTS RESULTS
Compared to standard of care RT-PCR testing, the overall sensitivity and specificity of the Atila iAMP test for detection of SARS-CoV-2 were 76.2% and 94.9%, respectively, and increased to 88.8% and 89.5%, respectively, after exclusion of an outlier study site. Sensitivity varied based on the anatomic collected site. Sensitivity for nasopharyngeal was 65.4% (range across study sites:52.8%-79.8%), mid-turbinate 88.2%, saliva 55.1% (range across study sites:42.9%-77.8%) and anterior nares 66.7% (range across study sites:63.6%-76.5%). The specificity for these anatomic collection sites ranged from 96.7% to 100%. Sensitivity improved in symptomatic patients (overall 82.7%) and those with a higher viral load (overall 92.4% for ct≤25). Sensitivity and specificity of the OptiGene Direct Plus RT-LAMP test, conducted at a single study-site, were 25.5% and 100%, respectively.
CONCLUSIONS CONCLUSIONS
The Atila iAMP COVID test with mid-turbinate sampling is a rapid, low-cost assay for detecting SARS-COV-2, especially in symptomatic patients and those with a high viral load, and could be used to reduce the risk of SARS-COV-2 transmission in clinical settings. Variation of performance between study sites highlights the need for site-specific clinical validation of these assays before clinical adoption.

Identifiants

pubmed: 34268516
doi: 10.1101/2021.07.01.21259879
pmc: PMC8282105
pii:
doi:

Types de publication

Preprint

Langues

eng

Commentaires et corrections

Type : UpdateIn

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Auteurs

Kanan T Desai (KT)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, USA.

Karla Alfaro (K)

Basic Health International, Pittsburgh, USA.

Laura Mendoza (L)

Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asunción, San Lorenzo, Paraguay.

Matthew Faron (M)

Medical College of Wisconsin, Milwaukee, USA.

Brian Mesich (B)

Medical College of Wisconsin, Milwaukee, USA.

Mauricio Maza (M)

Basic Health International, Pittsburgh, USA.

Rhina Dominguez (R)

Research Unit, El Salvador National Institute of Health (INS), El Salvador.

Adriana Valenzuela (A)

Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asunción, San Lorenzo, Paraguay.

Chyntia Díaz Acosta (CD)

Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asunción, San Lorenzo, Paraguay.

Magaly Martínez (M)

Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asunción, San Lorenzo, Paraguay.

Juan C Felix (JC)

Medical College of Wisconsin, Milwaukee, USA.

Rachel Masch (R)

Basic Health International, Pittsburgh, USA.
The Mount Sinai Hospital, New York, USA.

Sofia Gabrilovich (S)

Rutgers New Jersey Medical School, Newark, USA.

Michael Plump (M)

Rutgers New Jersey Medical School, Newark, USA.

Akiva P Novetsky (AP)

Rutgers New Jersey Medical School, Newark, USA.
Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA.

Mark H Einstein (MH)

Rutgers New Jersey Medical School, Newark, USA.
Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA.

Nataki C Douglas (NC)

Rutgers New Jersey Medical School, Newark, USA.

Miriam Cremer (M)

Basic Health International, Pittsburgh, USA.
Cleveland Clinic Lerner College of Medicine, Clevland, USA.

Nicolas Wentzensen (N)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, USA.

Classifications MeSH