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Soni A, Herbert C, Pretz C, Stamegna P, Filippaios A, Shi Q, Suvarna T, Harman E, Schrader S, Nowak C, Schramm E, Kheterpal V, Behar S, Tarrant S, Ferranto J, Hafer N, Robinson M, Achenbach C, Murphy RL, Manabe YC, Gibson L, Barton B, O’Connor L, Fahey N, Orvek E, Lazar P, Ayturk D, Wong S, Zai A, Cashman L, Rao LV, Luzuriaga K, Lemon S, Blodgett A, Trippe E, Barcus M, Goldberg B, Roth K, Stenzel T, Heetderks W, Broach J, McManus D. Design and implementation of a digital site-less clinical study of serial rapid antigen testing to identify asymptomatic SARS-CoV-2 infection. J Clin Transl Sci 2023; 7:e120. [PMID: 37313378 PMCID: PMC10260333 DOI: 10.1017/cts.2023.540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 04/05/2023] [Accepted: 04/27/2023] [Indexed: 06/15/2023] Open
Abstract
Background Rapid antigen detection tests (Ag-RDT) for SARS-CoV-2 with emergency use authorization generally include a condition of authorization to evaluate the test's performance in asymptomatic individuals when used serially. We aim to describe a novel study design that was used to generate regulatory-quality data to evaluate the serial use of Ag-RDT in detecting SARS-CoV-2 virus among asymptomatic individuals. Methods This prospective cohort study used a siteless, digital approach to assess longitudinal performance of Ag-RDT. Individuals over 2 years old from across the USA with no reported COVID-19 symptoms in the 14 days prior to study enrollment were eligible to enroll in this study. Participants throughout the mainland USA were enrolled through a digital platform between October 18, 2021 and February 15, 2022. Participants were asked to test using Ag-RDT and molecular comparators every 48 hours for 15 days. Enrollment demographics, geographic distribution, and SARS-CoV-2 infection rates are reported. Key Results A total of 7361 participants enrolled in the study, and 492 participants tested positive for SARS-CoV-2, including 154 who were asymptomatic and tested negative to start the study. This exceeded the initial enrollment goals of 60 positive participants. We enrolled participants from 44 US states, and geographic distribution of participants shifted in accordance with the changing COVID-19 prevalence nationwide. Conclusions The digital site-less approach employed in the "Test Us At Home" study enabled rapid, efficient, and rigorous evaluation of rapid diagnostics for COVID-19 and can be adapted across research disciplines to optimize study enrollment and accessibility.
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Affiliation(s)
- Apurv Soni
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Division of Health System Science, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Carly Herbert
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Caitlin Pretz
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Pamela Stamegna
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Andreas Filippaios
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Qiming Shi
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Division of Health System Science, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | | | | | | | | | | | - Stephanie Behar
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Seanan Tarrant
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Julia Ferranto
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Nathaniel Hafer
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Matthew Robinson
- Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chad Achenbach
- Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Robert L. Murphy
- Division of Infectious Disease, Department of Medicine, Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Yukari C. Manabe
- Division of Infectious Disease, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Laura Gibson
- Division of Infectious Disease, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Bruce Barton
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Laurel O’Connor
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Nisha Fahey
- Department of Pediatrics, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elizabeth Orvek
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Peter Lazar
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Didem Ayturk
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Steven Wong
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Adrian Zai
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | | | - Katherine Luzuriaga
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Stephenie Lemon
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Allison Blodgett
- University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elizabeth Trippe
- Division of Microbiology, OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Mary Barcus
- Division of Microbiology, OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Brittany Goldberg
- Division of Microbiology, OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Kristian Roth
- Division of Microbiology, OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - Timothy Stenzel
- OHT7 Office of Product Evaluation and Quality, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
| | - William Heetderks
- National Institute of Biomedical Imaging and Bioengineering, NIH, Via Contract with Kelly Services, Bethesda, MD, USA
| | - John Broach
- Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - David McManus
- Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Division of Health System Science, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Division of Cardiology, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
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Soni A, Herbert C, Pretz C, Stamegna P, Filippaios A, Shi Q, Suvarna T, Harman E, Schrader S, Nowak C, Schramm E, Kheterpal V, Behar S, Tarrant S, Ferranto J, Hafer N, Robinson M, Achenbach C, Murphy RL, Manabe YC, Gibson L, Barton B, O'Connor L, Fahey N, Orvek E, Lazar P, Ayturk D, Wong S, Zai A, Cashman L, Rao LV, Luzuriaga K, Lemon S, Blodgett A, Trippe E, Barcus M, Goldberg B, Roth K, Stenzel T, Heetderks W, Broach J, McManus D. Finding a Needle in a Haystack: Design and Implementation of a Digital Site-less Clinical Study of Serial Rapid Antigen Testing to Identify Asymptomatic SARS-CoV-2 Infection. medRxiv 2023:2022.08.04.22278274. [PMID: 35982663 PMCID: PMC9387154 DOI: 10.1101/2022.08.04.22278274] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Background Rapid antigen tests (Ag-RDT) for SARS-CoV-2 with Emergency Use Authorization generally include a condition of authorization to evaluate the test's performance in asymptomatic individuals when used serially. Objective To describe a novel study design to generate regulatory-quality data to evaluate serial use of Ag-RDT in detecting SARS-CoV-2 virus among asymptomatic individuals. Design Prospective cohort study using a decentralized approach. Participants were asked to test using Ag-RDT and molecular comparators every 48 hours for 15 days. Setting Participants throughout the mainland United States were enrolled through a digital platform between October 18, 2021 and February 15, 2022. Ag-RDTs were completed at home, and molecular comparators were shipped to a central laboratory. Participants Individuals over 2 years old from across the U.S. with no reported COVID-19 symptoms in the 14 days prior to study enrollment were eligible to enroll in this study. Measurements Enrollment demographics, geographic distribution, and SARS-CoV-2 infection rates are reported. Key Results A total of 7,361 participants enrolled in the study, and 492 participants tested positive for SARS-CoV-2, including 154 who were asymptomatic and tested negative to start the study. This exceeded the initial enrollment goals of 60 positive participants. We enrolled participants from 44 U.S. states, and geographic distribution of participants shifted in accordance with the changing COVID-19 prevalence nationwide. Limitations New, complex workflows required significant operational and data team support. Conclusions: The digital site-less approach employed in the 'Test Us At Home' study enabled rapid, efficient, and rigorous evaluation of rapid diagnostics for COVID-19, and can be adapted across research disciplines to optimize study enrollment and accessibility.
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