Comparison of Rapid Antigen Tests' Performance Between Delta and Omicron Variants of SARS-CoV-2 : A Secondary Analysis From a Serial Home Self-testing Study.


Journal

Annals of internal medicine
ISSN: 1539-3704
Titre abrégé: Ann Intern Med
Pays: United States
ID NLM: 0372351

Informations de publication

Date de publication:
12 2022
Historique:
pubmed: 11 10 2022
medline: 22 12 2022
entrez: 10 10 2022
Statut: ppublish

Résumé

It is important to document the performance of rapid antigen tests (Ag-RDTs) in detecting SARS-CoV-2 variants. To compare the performance of Ag-RDTs in detecting the Delta (B.1.617.2) and Omicron (B.1.1.529) variants of SARS-CoV-2. Secondary analysis of a prospective cohort study that enrolled participants between 18 October 2021 and 24 January 2022. Participants did Ag-RDTs and collected samples for reverse transcriptase polymerase chain reaction (RT-PCR) testing every 48 hours for 15 days. The parent study enrolled participants throughout the mainland United States through a digital platform. All participants self-collected anterior nasal swabs for rapid antigen testing and RT-PCR testing. All Ag-RDTs were completed at home, whereas nasal swabs for RT-PCR were shipped to a central laboratory. Of 7349 participants enrolled in the parent study, 5779 asymptomatic persons who tested negative for SARS-CoV-2 on day 1 of the study were eligible for this substudy. Sensitivity of Ag-RDTs on the same day as the first positive (index) RT-PCR result and 48 hours after the first positive RT-PCR result. A total of 207 participants were positive on RT-PCR (58 Delta, 149 Omicron). Differences in sensitivity between variants were not statistically significant (same day: Delta, 15.5% [95% CI, 6.2% to 24.8%] vs. Omicron, 22.1% [CI, 15.5% to 28.8%]; at 48 hours: Delta, 44.8% [CI, 32.0% to 57.6%] vs. Omicron, 49.7% [CI, 41.6% to 57.6%]). Among 109 participants who had RT-PCR-positive results for 48 hours, rapid antigen sensitivity did not differ significantly between Delta- and Omicron-infected participants (48-hour sensitivity: Delta, 81.5% [CI, 66.8% to 96.1%] vs. Omicron, 78.0% [CI, 69.1% to 87.0%]). Only 7.2% of the 69 participants with RT-PCR-positive results for shorter than 48 hours tested positive by Ag-RDT within 1 week; those with Delta infections remained consistently negative on Ag-RDTs. A testing frequency of 48 hours does not allow a finer temporal resolution of the analysis of test performance, and the results of Ag-RDTs are based on self-report. The performance of Ag-RDTs in persons infected with the SARS-CoV-2 Omicron variant is not inferior to that in persons with Delta infections. Serial testing improved the sensitivity of Ag-RDTs for both variants. The performance of rapid antigen testing varies on the basis of duration of RT-PCR positivity. National Heart, Lung, and Blood Institute of the National Institutes of Health.

Sections du résumé

BACKGROUND
It is important to document the performance of rapid antigen tests (Ag-RDTs) in detecting SARS-CoV-2 variants.
OBJECTIVE
To compare the performance of Ag-RDTs in detecting the Delta (B.1.617.2) and Omicron (B.1.1.529) variants of SARS-CoV-2.
DESIGN
Secondary analysis of a prospective cohort study that enrolled participants between 18 October 2021 and 24 January 2022. Participants did Ag-RDTs and collected samples for reverse transcriptase polymerase chain reaction (RT-PCR) testing every 48 hours for 15 days.
SETTING
The parent study enrolled participants throughout the mainland United States through a digital platform. All participants self-collected anterior nasal swabs for rapid antigen testing and RT-PCR testing. All Ag-RDTs were completed at home, whereas nasal swabs for RT-PCR were shipped to a central laboratory.
PARTICIPANTS
Of 7349 participants enrolled in the parent study, 5779 asymptomatic persons who tested negative for SARS-CoV-2 on day 1 of the study were eligible for this substudy.
MEASUREMENTS
Sensitivity of Ag-RDTs on the same day as the first positive (index) RT-PCR result and 48 hours after the first positive RT-PCR result.
RESULTS
A total of 207 participants were positive on RT-PCR (58 Delta, 149 Omicron). Differences in sensitivity between variants were not statistically significant (same day: Delta, 15.5% [95% CI, 6.2% to 24.8%] vs. Omicron, 22.1% [CI, 15.5% to 28.8%]; at 48 hours: Delta, 44.8% [CI, 32.0% to 57.6%] vs. Omicron, 49.7% [CI, 41.6% to 57.6%]). Among 109 participants who had RT-PCR-positive results for 48 hours, rapid antigen sensitivity did not differ significantly between Delta- and Omicron-infected participants (48-hour sensitivity: Delta, 81.5% [CI, 66.8% to 96.1%] vs. Omicron, 78.0% [CI, 69.1% to 87.0%]). Only 7.2% of the 69 participants with RT-PCR-positive results for shorter than 48 hours tested positive by Ag-RDT within 1 week; those with Delta infections remained consistently negative on Ag-RDTs.
LIMITATION
A testing frequency of 48 hours does not allow a finer temporal resolution of the analysis of test performance, and the results of Ag-RDTs are based on self-report.
CONCLUSION
The performance of Ag-RDTs in persons infected with the SARS-CoV-2 Omicron variant is not inferior to that in persons with Delta infections. Serial testing improved the sensitivity of Ag-RDTs for both variants. The performance of rapid antigen testing varies on the basis of duration of RT-PCR positivity.
PRIMARY FUNDING SOURCE
National Heart, Lung, and Blood Institute of the National Institutes of Health.

Identifiants

pubmed: 36215709
doi: 10.7326/M22-0760
pmc: PMC9578286
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1685-1692

Subventions

Organisme : NHLBI NIH HHS
ID : U54 HL143541
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001453
Pays : United States
Organisme : NCATS NIH HHS
ID : TL1 TR001454
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL137734
Pays : United States
Organisme : NHLBI NIH HHS
ID : U01 HL146382
Pays : United States

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Auteurs

Apurv Soni (A)

Program in Digital Medicine and Division of Clinical Informatics, Department of Medicine, and Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (A.S.).

Carly Herbert (C)

Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).

Andreas Filippaios (A)

Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).

John Broach (J)

Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (J.B., L.O.).

Andres Colubri (A)

Department of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School, Worcester, Massachusetts (A.C.).

Nisha Fahey (N)

Program in Digital Medicine, Department of Medicine, Department of Population and Quantitative Health Sciences, and Department of Pediatrics, University of Massachusetts Chan Medical School, Worcester, Massachusetts (N.F.).

Kelsey Woods (K)

Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).

Janvi Nanavati (J)

Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).

Colton Wright (C)

Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).

Taylor Orwig (T)

Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).

Karen Gilliam (K)

Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).

Vik Kheterpal (V)

CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.).

Thejas Suvarna (T)

CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.).

Chris Nowak (C)

CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.).

Summer Schrader (S)

CareEvolution, Ann Arbor, Michigan (V.K., T.S., C.N., S.S.).

Honghuang Lin (H)

Program in Digital Medicine and Division of Clinical Informatics, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (H.L.).

Laurel O'Connor (L)

Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (J.B., L.O.).

Caitlin Pretz (C)

Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (C.H., A.F., K.W., J.N., C.W., T.O., K.G., C.P.).

Didem Ayturk (D)

Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).

Elizabeth Orvek (E)

Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).

Julie Flahive (J)

Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).

Peter Lazar (P)

Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).

Qiming Shi (Q)

Program in Digital Medicine, Department of Medicine, Department of Population and Quantitative Health Sciences, and University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts (Q.S.).

Chad Achenbach (C)

Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, Illinois (C.A., R.M.).

Robert Murphy (R)

Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, Illinois (C.A., R.M.).

Matthew Robinson (M)

Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.R., Y.C.M.).

Laura Gibson (L)

Department of Pediatrics and Division of Infectious Disease, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (L.G.).

Pamela Stamegna (P)

University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts (P.S., N.H.).

Nathaniel Hafer (N)

University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, Massachusetts (P.S., N.H.).

Katherine Luzuriaga (K)

University of Massachusetts Center for Clinical and Translational Science and Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts (K.L.).

Bruce Barton (B)

Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.A., E.O., J.F., P.L., B.B.).

William Heetderks (W)

National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland (W.H.).

Yukari C Manabe (YC)

Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.R., Y.C.M.).

David McManus (D)

Program in Digital Medicine and Division of Cardiology, Department of Medicine, and Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts (D.M.).

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