The estimation of diagnostic accuracy of tests for COVID-19: A scoping review
- PMID: 32882315
- PMCID: PMC7457918
- DOI: 10.1016/j.jinf.2020.08.043
The estimation of diagnostic accuracy of tests for COVID-19: A scoping review
Abstract
Objectives: To assess the methodologies used in the estimation of diagnostic accuracy of SARS-CoV-2 real-time reverse transcription polymerase chain reaction (rRT-PCR) and other nucleic acid amplification tests (NAATs) and to evaluate the quality and reliability of the studies employing those methods.
Methods: We conducted a systematic search of English-language articles published December 31, 2019-June 19, 2020. Studies of any design that performed tests on ≥10 patients and reported or inferred correlative statistics were included. Studies were evaluated using elements of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) guidelines.
Results: We conducted a narrative and tabular synthesis of studies organized by their reference standard strategy or comparative agreement method, resulting in six categorizations. Critical study details were frequently unreported, including the mechanism for patient/sample selection and researcher blinding to results, which lead to concern for bias.
Conclusions: Current studies estimating test performance characteristics have imperfect study design and statistical methods for the estimation of test performance characteristics of SARS-CoV-2 tests. The included studies employ heterogeneous methods and overall have an increased risk of bias. Employing standardized guidelines for study designs and statistical methods will improve the process for developing and validating rRT-PCR and NAAT for the diagnosis of COVID-19.
Keywords: COVID-19; Diagnostic accuracy; QUADAS-2; SARS-CoV-2; Sensitivity; Specificity.
Copyright © 2020. Published by Elsevier Ltd.
Conflict of interest statement
Declaration of Competing Interest None
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Comment in
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SARS-CoV-2 detection by nasal strips: A superior tool for surveillance of paediatric population.J Infect. 2021 Apr;82(4):84-123. doi: 10.1016/j.jinf.2020.11.009. Epub 2020 Nov 12. J Infect. 2021. PMID: 33189771 Free PMC article. No abstract available.
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