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Meta-Analysis
. 2022 Nov:28 Suppl 2:2347-2361.
doi: 10.1111/odi.13934. Epub 2021 Jun 21.

The diagnostic accuracy of saliva testing for SARS-CoV-2: A systematic review and meta-analysis

Momen A Atieh  1   2 , Marina Guirguis  1 , Nabeel H M Alsabeeha  3 , Richard D Cannon  2
Affiliations
Meta-Analysis

The diagnostic accuracy of saliva testing for SARS-CoV-2: A systematic review and meta-analysis

Momen A Atieh et al. Oral Dis. 2022 Nov.

Abstract

Introduction: Early detection of coronavirus disease 2019 (COVID-19) is paramount for controlling the progression and spread of the disease. Currently, nasopharyngeal swabbing (NPS) is the standard method for collecting specimens. Saliva was recently proposed as an easy and safe option with many authorities adopting the methodology despite the limited evidence of efficacy.

Objectives: The aim of this review was to systematically evaluate the current literature on the use of saliva test for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and carry out a meta-analysis to determine its diagnostic accuracy.

Materials and methods: Prospective studies were searched for in electronic databases, complemented by hand-searching relevant journals. The risk of bias and applicability were assessed using the revised Quality Assessment of Studies of Diagnostic Accuracy Studies (QUADAS-2) tool. Meta-analyses and meta-regression modeling were performed to calculate the diagnostic accuracy and examine sources of heterogeneity.

Results: A total of 16 studies were included with 2928 paired samples. The overall meta-analysis showed a high sensitivity and specificity for saliva test at 0.88 (95% CI 0.82-0.92) and 0.92 (95% CI 0.75-0.98), respectively. The diagnostic odds ratio was calculated at 87 (95% CI 19-395) and area under the curve was calculated as 0.92 (95% CI 0.90-0.94) suggesting very good performance of the saliva tests in detecting SARS-CoV-2.

Conclusion: Saliva testing has a very good discriminative and diagnostic ability to detect of SARS-CoV-2. Additional large and well-designed prospective studies are needed to further validate the diagnostic accuracy and determine a safe sample collection method prior to its recommendation for mass application.

Clinical relevance: Saliva demonstrated high sensitivity and specificity. The use of saliva will allow for self-collection of specimens and specimen collection in outpatient and community clinics.

Keywords: coronavirus disease; detection; review; saliva; severe acute respiratory syndrome coronavirus 2.

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Conflict of interest statement

Momen Atieh declares that he has no conflict of interest. Marina Guirguis declares that she has no conflict of interest. Nabeel Alsabeeha declares that he has no conflict of interest. Richard Cannon declares that he has no conflict of interest.

Figures

FIGURE 1
FIGURE 1
Sensitivity and specificity of saliva tests for detecting SARS‐CoV‐2. Forest plots of individual/pooled sensitivity and specificity of the included studies (CI: confidence interval; Q: Cochran chi‐square test)
FIGURE 2
FIGURE 2
Diagnostic test accuracy of saliva test for detecting SARS‐CoV‐2 (SROC: summary receiver operating characteristic; SENS: sensitivity; SPEC: specificity; AUC: area under the curve; O: observed data; ♦: Summary Oberating Point; ➖: SORC curve; ‐‐‐: 95% confidence contour; …… 95% prediction contour; 1: Aita et al., ; 2: Altawalah et al., ; 3: Binder et al., ; 4: Chen et al., ; 5: Guclu et al., ; 6: Hanson et al., ; 7: Jamal et al., ; 8: Landry et al., ; 9: Moreno‐Contreras et al., ; 10: Pasomsub et al., ; 11: Procop et al., ; 12: Rao et al., ; 13: Sakanashi et al., ; 14: Senok et al., ; 15: Vaz et al., ; 16: Williams et al., 2020).
FIGURE 3
FIGURE 3
Fagan nomogram (LR: likelihood ratio)
FIGURE A1
FIGURE A1
Flowchart of the search process
FIGURE A2
FIGURE A2
Assessment of applicability concerns and risk of bias of the included studies presented with low (green), unclear (yellow) and high (red) risk of bias
FIGURE A3
FIGURE A3
Funnel plot for estimating publication bias (ESS: effective sample size; 1: Aita et al., ; 2: Altawalah et al., ; 3: Binder et al., ; 4: Chen et al., ; 5: Guclu et al., ; 6: Hanson et al., ; 7: Jamal et al., ; 8: Landry et al., ; 9: Moreno‐Contreras et al., ; 10: Pasomsub et al., ; 11: Procop et al., ; 12: Rao et al., ; 13: Sakanashi et al., ; 14: Senok et al., ; 15: Vaz et al., ; 16: Williams et al., 2020)
FIGURE A4
FIGURE A4
Meta‐regression and subgroup analyses (SS100: sample size ≥100; Inpats: in‐patients; CoughSal: coughed out saliva)
See this image and copyright information in PMC

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