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Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry

BACKGROUND: The global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across...

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Autores principales: Spick, Matt, Lewis, Holly M., Wilde, Michael J., Hopley, Christopher, Huggett, Jim, Bailey, Melanie J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: W.B. Saunders 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548837/
https://www.ncbi.nlm.nih.gov/pubmed/34715115
http://dx.doi.org/10.1016/j.metabol.2021.154922
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author Spick, Matt
Lewis, Holly M.
Wilde, Michael J.
Hopley, Christopher
Huggett, Jim
Bailey, Melanie J.
author_facet Spick, Matt
Lewis, Holly M.
Wilde, Michael J.
Hopley, Christopher
Huggett, Jim
Bailey, Melanie J.
author_sort Spick, Matt
collection PubMed
description BACKGROUND: The global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across a wide range of biological matrices, and additionally to assess risks of bias and applicability in studies published to date. METHOD: 23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2858 COVID-19 positive participants and 2544 controls. Risks of bias and applicability were assessed via a QUADAS-2 questionnaire. A meta-analysis was also performed focusing on sensitivity, specificity, diagnostic accuracy and Youden's Index, in addition to assessing heterogeneity. FINDINGS: Sensitivity averaged 0.87 in the studies reviewed herein (interquartile range 0.81–0.96) and specificity 0.88 (interquartile range 0.82–0.98), with an area under the receiver operating characteristic summary curve of 0.93. By subgroup, the best diagnostic results were achieved by viral proteomic analyses of nasopharyngeal swabs and metabolomic analyses of plasma and serum. The performance of other sampling matrices (breath, sebum, saliva) was less good, indicating that these protocols are currently insufficiently mature for clinical application. CONCLUSIONS: This systematic review and meta-analysis demonstrates the potential for mass spectrometry and ‘omics in achieving accurate test results for COVID-19 diagnosis, but also highlights the need for further work to optimize and harmonize practice across laboratories before these methods can be translated to clinical applications.
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spelling pubmed-85488372021-10-27 Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry Spick, Matt Lewis, Holly M. Wilde, Michael J. Hopley, Christopher Huggett, Jim Bailey, Melanie J. Metabolism COVID-19 in Metabolism BACKGROUND: The global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across a wide range of biological matrices, and additionally to assess risks of bias and applicability in studies published to date. METHOD: 23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2858 COVID-19 positive participants and 2544 controls. Risks of bias and applicability were assessed via a QUADAS-2 questionnaire. A meta-analysis was also performed focusing on sensitivity, specificity, diagnostic accuracy and Youden's Index, in addition to assessing heterogeneity. FINDINGS: Sensitivity averaged 0.87 in the studies reviewed herein (interquartile range 0.81–0.96) and specificity 0.88 (interquartile range 0.82–0.98), with an area under the receiver operating characteristic summary curve of 0.93. By subgroup, the best diagnostic results were achieved by viral proteomic analyses of nasopharyngeal swabs and metabolomic analyses of plasma and serum. The performance of other sampling matrices (breath, sebum, saliva) was less good, indicating that these protocols are currently insufficiently mature for clinical application. CONCLUSIONS: This systematic review and meta-analysis demonstrates the potential for mass spectrometry and ‘omics in achieving accurate test results for COVID-19 diagnosis, but also highlights the need for further work to optimize and harmonize practice across laboratories before these methods can be translated to clinical applications. W.B. Saunders 2022-01 /pmc/articles/PMC8548837/ /pubmed/34715115 http://dx.doi.org/10.1016/j.metabol.2021.154922 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle COVID-19 in Metabolism
Spick, Matt
Lewis, Holly M.
Wilde, Michael J.
Hopley, Christopher
Huggett, Jim
Bailey, Melanie J.
Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry
title Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry
title_full Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry
title_fullStr Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry
title_full_unstemmed Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry
title_short Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry
title_sort systematic review with meta-analysis of diagnostic test accuracy for covid-19 by mass spectrometry
topic COVID-19 in Metabolism
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548837/
https://www.ncbi.nlm.nih.gov/pubmed/34715115
http://dx.doi.org/10.1016/j.metabol.2021.154922
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