Evaluation of serological lateral flow assays for severe acute respiratory syndrome coronavirus-2.

Adult Aged Antibodies, Viral / blood COVID-19 / blood COVID-19 Serological Testing / methods Female Humans Immunoglobulin G / blood Immunoglobulin M / blood Limit of Detection Male Middle Aged Predictive Value of Tests Prevalence SARS-CoV-2 / immunology Sensitivity and Specificity User-Centered Design User-Computer Interface
Antibodies COVID-19 Coronavirus Lateral flow assays SARS-CoV-2

Journal

BMC infectious diseases
ISSN: 1471-2334
Titre abrégé: BMC Infect Dis
Pays: England
ID NLM: 100968551

Informations de publication

Date de publication:
16 Jun 2021
Historique:
received: 08 02 2021
accepted: 25 05 2021
entrez: 17 6 2021
pubmed: 18 6 2021
medline: 24 6 2021
Statut: epublish

Résumé

COVID-19 has resulted in significant morbidity and mortality worldwide. Lateral flow assays can detect anti-Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) antibodies to monitor transmission. However, standardized evaluation of their accuracy and tools to aid in interpreting results are needed. We evaluated 20 IgG and IgM assays selected from available tests in April 2020. We evaluated the assays' performance using 56 pre-pandemic negative and 56 SARS-CoV-2-positive plasma samples, collected 10-40 days after symptom onset, confirmed by a molecular test and analyzed by an ultra-sensitive immunoassay. Finally, we developed a user-friendly web app to extrapolate the positive predictive values based on their accuracy and local prevalence. Combined IgG + IgM sensitivities ranged from 33.9 to 94.6%, while combined specificities ranged from 92.6 to 100%. The highest sensitivities were detected in Lumiquick for IgG (98.2%), BioHit for both IgM (96.4%), and combined IgG + IgM sensitivity (94.6%). Furthermore, 11 LFAs and 8 LFAs showed perfect specificity for IgG and IgM, respectively, with 15 LFAs showing perfect combined IgG + IgM specificity. Lumiquick had the lowest estimated limit-of-detection (LOD) (0.1 μg/mL), followed by a similar LOD of 1.5 μg/mL for CareHealth, Cellex, KHB, and Vivachek. We provide a public resource of the accuracy of select lateral flow assays with potential for home testing. The cost-effectiveness, scalable manufacturing process, and suitability for self-testing makes LFAs an attractive option for monitoring disease prevalence and assessing vaccine responsiveness. Our web tool provides an easy-to-use interface to demonstrate the impact of prevalence and test accuracy on the positive predictive values.

Sections du résumé

BACKGROUND BACKGROUND
COVID-19 has resulted in significant morbidity and mortality worldwide. Lateral flow assays can detect anti-Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) antibodies to monitor transmission. However, standardized evaluation of their accuracy and tools to aid in interpreting results are needed.
METHODS METHODS
We evaluated 20 IgG and IgM assays selected from available tests in April 2020. We evaluated the assays' performance using 56 pre-pandemic negative and 56 SARS-CoV-2-positive plasma samples, collected 10-40 days after symptom onset, confirmed by a molecular test and analyzed by an ultra-sensitive immunoassay. Finally, we developed a user-friendly web app to extrapolate the positive predictive values based on their accuracy and local prevalence.
RESULTS RESULTS
Combined IgG + IgM sensitivities ranged from 33.9 to 94.6%, while combined specificities ranged from 92.6 to 100%. The highest sensitivities were detected in Lumiquick for IgG (98.2%), BioHit for both IgM (96.4%), and combined IgG + IgM sensitivity (94.6%). Furthermore, 11 LFAs and 8 LFAs showed perfect specificity for IgG and IgM, respectively, with 15 LFAs showing perfect combined IgG + IgM specificity. Lumiquick had the lowest estimated limit-of-detection (LOD) (0.1 μg/mL), followed by a similar LOD of 1.5 μg/mL for CareHealth, Cellex, KHB, and Vivachek.
CONCLUSION CONCLUSIONS
We provide a public resource of the accuracy of select lateral flow assays with potential for home testing. The cost-effectiveness, scalable manufacturing process, and suitability for self-testing makes LFAs an attractive option for monitoring disease prevalence and assessing vaccine responsiveness. Our web tool provides an easy-to-use interface to demonstrate the impact of prevalence and test accuracy on the positive predictive values.

Identifiants

DOI: 10.1186/s12879-021-06257-7 PMID: 34134647 PMC: PMC8206878
pubmed: 34134647
doi: 10.1186/s12879-021-06257-7
pii: 10.1186/s12879-021-06257-7
pmc: PMC8206878
doi:

Substances chimiques

Antibodies, Viral 0
Immunoglobulin G 0
Immunoglobulin M 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

580

Commentaires et corrections

Type : ErratumIn

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Auteurs

Bianca A Trombetta (BA)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.

Savannah E Kandigian (SE)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.

Robert R Kitchen (RR)

Department of Medicine, Harvard Medical School, Boston, MA, USA.
Mass General Brigham Innovation, Boston, MA, USA.

Korneel Grauwet (K)

Cardiology Division, Massachusetts General Hospital, Charlestown, MA, USA.

Pia Kivisäkk Webb (PK)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.
Department of Medicine, Harvard Medical School, Boston, MA, USA.

Glenn A Miller (GA)

Mass General Brigham Innovation, Boston, MA, USA.

Charles G Jennings (CG)

Cardiology Division, Massachusetts General Hospital, Charlestown, MA, USA.
Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Sejal Jain (S)

Department of Medical Oncology and Center for Cancer-Genome Discovery, Dana-Farber Cancer Institute, Boston, MA, USA.
Department of Pathology, Harvard Medical School, Boston, MA, USA.

Samara Miller (S)

Department of Medicine, Harvard Medical School, Boston, MA, USA.
Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA.
Harvard Stem Cell Institute, Cambridge, MA, USA.
Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.

Yikai Kuo (Y)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.
Cardiology Division, Massachusetts General Hospital, Charlestown, MA, USA.

Thadryan Sweeney (T)

Cardiology Division, Massachusetts General Hospital, Charlestown, MA, USA.

Tal Gilboa (T)

Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Maia Norman (M)

Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Sackler School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA.

Daimon P Simmons (DP)

Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA.

Christopher E Ramirez (CE)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.

Melissa Bedard (M)

Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA.

Catherine Fink (C)

Medical Diagnostic Technology Evaluation, LLC, Carlisle, MA, USA.

Jina Ko (J)

Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA.

Esmarline J De León Peralta (EJ)

Department of Pathology, Massachusetts General Hospital, Boston, MA, USA.
Wellman Center for Photomedicine, Massachusetts General Research Institute, Boston, MA, USA.
Department of Dermatology, Massachusetts General Hospital, Boston, MA, USA.

Gerald Watts (G)

Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA.

Emma Gomez-Rivas (E)

Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA.

Vannessa Davis (V)

Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Rocky M Barilla (RM)

Evergrande Center for Immunologic Diseases, Brigham and Women's Hospital, Boston, MA, USA.

Jianing Wang (J)

Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.

Pierre Cunin (P)

Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA.

Samuel Bates (S)

Functional Genomics Laboratory, Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.

Chevaun Morrison-Smith (C)

Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Benjamin Nicholson (B)

Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.

Edmond Wong (E)

Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.

Leena El-Mufti (L)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.

Michael Kann (M)

Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.

Anna Bolling (A)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.

Brooke Fortin (B)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.

Hayden Ventresca (H)

Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.

Wen Zhou (W)

Division of Nephrology and Endocrine Unit Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.

Santiago Pardo (S)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.

Megan Kwock (M)

Cancer Center Protocol Office, Massachusetts General Hospital, Boston, MA, USA.

Aditi Hazra (A)

Department of Medicine, Harvard Medical School, Boston, MA, USA.
Division of Preventative Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Leo Cheng (L)

Radiology and pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Q Rushdy Ahmad (QR)

Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.

James A Toombs (JA)

Brigham Research Institute, Brigham and Women's Hospital, Boston, MA, USA.

Rebecca Larson (R)

Immunology Program, Harvard Medical School, Boston, MA, USA.
Cellular Immunotherapy Program, Cancer Center, Massachusetts General Hospital, Boston, MA, USA.

Haley Pleskow (H)

Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Nell Meosky Luo (NM)

Folia Health, Inc., Cambridge, MA, USA.

Christina Samaha (C)

Folia Health, Inc., Cambridge, MA, USA.

Unnati M Pandya (UM)

Department of Medicine, Harvard Medical School, Boston, MA, USA.
Vincent Center for Reproductive Biology, Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA.

Pushpamali De Silva (P)

Wellman Center for Photomedicine, Massachusetts General Research Institute, Boston, MA, USA.

Sally Zhou (S)

Department of Biology, Northeastern University, Boston, MA, USA.
College of Science, Northeastern University, Boston, MA, USA.

Zakary Ganhadeiro (Z)

Department of Biology, Northeastern University, Boston, MA, USA.
College of Science, Northeastern University, Boston, MA, USA.

Sara Yohannes (S)

Brigham Research Institute, Brigham and Women's Hospital, Boston, MA, USA.

Rakiesha Gay (R)

Brigham Research Institute, Brigham and Women's Hospital, Boston, MA, USA.
College of Science, Northeastern University, Boston, MA, USA.

Jacqueline Slavik (J)

Brigham Research Institute, Brigham and Women's Hospital, Boston, MA, USA.

Shibani S Mukerji (SS)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.

Petr Jarolim (P)

Department of Pathology, Harvard Medical School, Boston, MA, USA.
Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

David R Walt (DR)

Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Mass General Brigham COVID Center for Innovation, Diagnostics Accelerator, Boston, MA, USA.

Becky C Carlyle (BC)

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA, USA.
Department of Medicine, Harvard Medical School, Boston, MA, USA.

Lauren L Ritterhouse (LL)

Department of Pathology, Massachusetts General Hospital, Boston, MA, USA.
Mass General Brigham COVID Center for Innovation, Diagnostics Accelerator, Boston, MA, USA.

Sara Suliman (S)

Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA. ssuliman1@bwh.harvard.edu.
Mass General Brigham COVID Center for Innovation, Diagnostics Accelerator, Boston, MA, USA. ssuliman1@bwh.harvard.edu.

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Classifications MeSH

questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Sujet âgé › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Globulines › Sérum-globulines › Immunoglobulines › Anticorps › Anticorps antiviraux › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Maladies de l'appareil respiratoire › Infections de l'appareil respiratoire › Pneumopathie infectieuse › Pneumopathie virale › COVID-19 › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Techniques d'investigation › Techniques immunologiques › Tests immunologiques › Tests sérologiques › Dépistage sérologique de la COVID-19 › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Globulines › Sérum-globulines › Immunoglobulines › Anticorps › Isotypes des immunoglobulines › Immunoglobuline G › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Globulines › Sérum-globulines › Immunoglobulines › Anticorps › Isotypes des immunoglobulines › Immunoglobuline M › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Sensibilité et spécificité › Limite de détection › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Adulte d'âge moyen › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Méthodologie en recherche épidémiologique › Valeur prédictive des tests › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Collecte de données › Registre civil › Morbidité › Prévalence › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Virus › Virus à ARN › Virus à ARN à brin positif › Nidovirales › Coronaviridae › Coronavirus › Betacoronavirus › Virus du SRAS › SARS-CoV-2 › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Sensibilité et spécificité › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Logiciel › Conception centrée sur l'utilisateur › Evaluation of serological lateral flow assays...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Logiciel › Interface utilisateur › Evaluation of serological lateral flow assays...