Diagnostic Accuracy of COVID-19 Antibody Tests Authorized by FDA Philippines: A Systematic Review and Meta-Analysis

Introduction: Coronavirus Disease (COVID-19) is a highly infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) which has infected many people all over the world. One of the best ways to lessen its spread is through early detection and diagnosis. Various serologica...

Full description

Saved in:
Bibliographic Details
Published in:SciMedicine journal Vol. 3; no. 4; pp. 283 - 301
Main Authors: Chua, Carmel Reina R., De los Santos, Esther Delle E., Escasa, Karla Veronica H., Estolas, Richmond Louis G., Feliciano, Junnealyn, Ortega, Sabrina Audrey E., Ledesma, Carlo, Leonin, Jan Ebrian D., Tesalona, Sherill D.
Format: Journal Article
Language:English
Published: Ital Publication 01-12-2021
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Introduction: Coronavirus Disease (COVID-19) is a highly infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) which has infected many people all over the world. One of the best ways to lessen its spread is through early detection and diagnosis. Various serological tests are now being used as a surveillance tool in the detection of antibodies as a response to SARS-CoV-2. The aim of this study is to evaluate the diagnostic accuracy and performance of the available COVID-19 antibody tests authorized by the Food and Drug Administration (FDA) Philippines that make use of Enzyme-Linked Immunosorbent Assay (ELISA), Chemiluminescence Immunoassay (CLIA) and Lateral Flow Immunoassay (LFIA). Method: Complete published journal articles relevant to the diagnostic accuracy of the three antibody tests were collected using trusted medical journal search engines. The quality of journals was assessed using QUADAS-2 to determine the risk of bias and assess the applicability judgments of diagnostic accuracy studies. Forest plots were used to summarize the performance of LFIA, ELISA and CLIA according to their specificity and sensitivity in detecting various antibodies. Pooled sensitivity and specificity were also done using bivariate random-effects models with its log-likelihood, a corresponding chi-square test statistic, and area under the summary Receiver-Operating Characteristic curve to see the potential heterogeneity in the data and to assess the diagnostic accuracy of the COVID-19 antibody tests. Results: Bivariate random-effects model and areas under the sROC curve were used to evaluate the diagnostic accuracy of COVID-19 antibody tests. The pooled sensitivity in detecting IgG based on CLIA, ELISA, and LFIA were 81.7%, 58.7%, and 74.3% respectively, with an overall of 72.0%. For IgM detection, LFIA has a higher pooled sensitivity of 69.6% than CLIA with 61.0%. Overall, the pooled sensitivity is 68.5%. In IgA detection, only ELISA based test was included with a pooled sensitivity of 84.8%. Lastly, pooled sensitivities for combined antibodies based on ELISA and LFIA were 89.0% and 81.6% respectively, with an overall of 82.5%. On the other hand, all tests excluding ELISA-IgA displayed high pooled specificities with a range of 94.0% to 100.0%. Diagnostic accuracies of the test in detecting IgG, IgM, and combined antibodies were found out to be almost perfect based on the computed area under the sROC with values of 0.973, 0.953, and 0.966, respectively. Conclusion: In this systematic review and meta-analysis, existing evidence on the diagnostic accuracy of antibody tests for COVID-19 were found to be characterized by high risks of bias, consistency in the heterogeneity of sensitivities, and consistency in the homogeneity of high specificities except in IgA detection using ELISA. The bivariate random-effects models showed that there are no significant differences in terms of sensitivity among CLIA, ELISA and LFIA in detecting IgG, IgM, and combined antibodies at a 95% confidence interval. Nonetheless, CLIA, ELISA and LFIA were found to have excellent diagnostic accuracies in the detection of IgG, IgM and combined antibodies as reflected by their AUC values. Doi: 10.28991/SciMedJ-2021-0304-1 Full Text: PDF
ISSN:2704-9833
2704-9833
DOI:10.28991/SciMedJ-2021-0304-1