A systematic and meta-analysis review on the diagnostic accuracy of antibodies in the serological diagnosis of COVID-19

Abstract

Background: Serological testing based on different antibody types are an alternative method being used to diagnose SARS-CoV-2 and has the potential of having higher diagnostic accuracy compared to the current gold standard rRT-PCR. Therefore, the objective of this review was to evaluate the diagnostic accuracy of IgG and IgM based point-of-care (POC) lateral flow immunoassay (LFIA), chemiluminescence enzyme immunoassay (CLIA), fluorescence enzyme-linked immunoassay (FIA) and ELISA systems that detect SARS-CoV-2 antigens.

Method: A systematic literature search was carried out in PubMed, Medline complete and MedRxiv. Studies evaluating the diagnostic accuracy of serological assays for SARS-CoV-2 were eligible. Study selection and data-extraction were performed by two authors independently. QUADAS-2 checklist tool was used to assess the quality of the studies. The bivariate model and the hierarchical summary receiver operating characteristic curve model were performed to evaluate the diagnostic accuracy of the serological tests. Subgroup meta-analysis was performed to explore the heterogeneity.

Results: The pooled sensitivity for IgG (n = 17), IgM (n = 16) and IgG-IgM (n = 24) based LFIA tests were 0.5856, 0.4637 and 0.6886, respectively compared to rRT-PCR method. The pooled sensitivity for IgG (n = 9) and IgM (n = 10) based CLIA tests were 0.9311 and 0.8516, respectively compared to rRT-PCR. The pooled sensitivity the IgG (n = 10), IgM (n = 11) and IgG-IgM (n = 5) based ELISA tests were 0.8292, 0.8388 and 0.8531 respectively compared to rRT-PCR. All tests displayed high specificities ranging from 0.9693 to 0.9991. Amongst the evaluated tests, IgG based CLIA expressed the highest sensitivity signifying its accurate detection of the largest proportion of infections identified by rRT-PCR. ELISA and CLIA tests performed better in terms of sensitivity compared to LFIA. IgG based tests performed better compared to IgM except for the ELISA.

Conclusions: We report that IgG-IgM based ELISA tests have the best overall diagnostic test accuracy. Moreover, irrespective of the method, a combined IgG/IgM test seems to be a better choice in terms of sensitivity than measuring either antibody type independently. Given the poor performances of the current LFIA devices, there is a need for more research on the development of highly sensitivity and specific POC LFIA that are adequate for most individual patient applications and attractive for large sero-prevalence studies.

Systematic review registration: PROSPERO CRD42020179112.

Keywords: COVID-19; IgG; IgM; SARS-CoV2; Sensitivity; Serology; Specificity; rRT-PCR.

Fig. 1

PRISMA flow diagram for selection of articles for meta-analysis

Fig. 2

LFIA methodological quality summary table and graph. a Risk of bias and applicability concerns summary: review authors’ judgements about each domain for each included study. b QUADAS-2 bias assessment and QUADAS-2 applicability assessment item presented as percentages across all included studies. On the left, risk of bias graph and on the right applicability concerns graph. c Risk of bias and applicability concerns summary: review authors. Low, low risk of bias; high, high risk of bias; unclear, bias is unclear

Fig. 3

CLIA methodological quality summary table and graph. a Risk of bias and applicability concerns summary: review authors’ judgements about each domain for each included study. b QUADAS-2 bias assessment and QUADAS-2 applicability assessment item presented as percentages across all included studies. On the left, risk of bias graph and on the right applicability concerns graph. c Risk of bias and applicability concerns summary: review authors. Low, low risk of bias; high, high risk of bias; unclear, bias is unclear

Fig. 4

ELISA methodological quality summary table and graph. a Risk of bias and applicability concerns summary: review authors’ judgements about each domain for each included study. b QUADAS-2 bias assessment and QUADAS-2 applicability assessment item presented as percentages across all included studies. On the left, risk of bias graph and on the right applicability concerns graph. c Risk of bias and applicability concerns summary: review authors. Low, low risk of bias; high, high risk of bias; unclear, bias is unclear

Fig. 5

Forest plot of sensitivity, specificity and heterogeneity of serological LFIA diagnosis of COVID-19. a Forest plot for the IgG LFIA. b Forest plot for the IgM based LFIA. c Forest plot for the IgG-IgM based LFIA

Fig. 6

Forest plot of sensitivity, specificity and heterogeneity of serological CLIA diagnosis of COVID-19. a Forest plot for the IgG CLIA. b Forest plot for the IgM based CLIA. c Forest plot for the IgG-IgM based CLIA

Fig. 7

Forest plot of sensitivity, specificity and heterogeneity of serological ELISA diagnosis of COVID-19. a Forest plot for the IgG ELISA. b Forest plot for the IgM based ELISA. c Forest plot for the IgG-IgM based ELISA

Fig. 8

Summary ROC curves for the three antibody serological test groups. Every symbol reflects a 2 × 2 table, one for each test. One study may have contributed more than one 2 × 2 table. The curves are shown for the different test types

Fig. 9

Hierarchical summary receiver operating characteristic (HSROC) curve obtained using OpenMeta-Analyst. Every circle represents the sensitivity and specificity estimates of individual studies in the meta-analysis, and the size of the circle reflects the sample size. The black dots indicate summary points of sensitivity and specificity; HSROC curve is the line passing through summary point. The curve is the regression line that summarises the overall diagnostic accuracy. a HSROC for IgG serological tests. b HSROC for IgM serological tests. c HSROC IgG-IgM serological tests. 1, LFIA HSROC; 2, CLIA HSROC and 3, ELISA HSROC

Fig. 10

Forest plot of studies evaluating tests for detection of IgG, IgM and IgG-IgM according to days since COVID-19 symptom onset to specimen collection. In brackets () are the number of days since symptom onset to specimen collection. Artron, Auto Bio CTK Biotech CTK Biotech are test names all reported in a study by Lassaunire et al