Diagnostic Accuracy of Mycobacterium tuberculosis Antigen-Based Skin Tests (TBSTs) for Tuberculosis Infection Compared with TST and IGRA: A Network Meta-Analysis

Abstract

The aim of this study was to evaluate the diagnostic accuracy of the IGRA, TST, and TBST by combining diagnostic test accuracy (DTA) analysis and network meta-analysis (NMA) to increase the reliability and accuracy of diagnostic methods and promote the eradication of TB. An electronic search of the PubMed, Embase, and Cochrane databases was conducted, from the date of establishment to September 30, 2024. Data were synthesized with frequentist random-effects network meta-analyses, a single-group rate meta-analysis algorithm, and a bivariate mixed-effects logistic regression model. Summarized receiver operating characteristic curves and Fagan nomograms were used to assess diagnostic accuracy and clinical utility. Deeks' funnel plots and the Quality Assessment of Diagnostic Accuracy Studies 2 tools were used to assess publication bias and risk of bias. Sources of heterogeneity were investigated using subgroup analyses. Forty-nine studies were identified. The diagnostic performance of the three diagnostic methods for TB infection is summarized as follows: the pooled sensitivity was 77.9% (95% confidence interval [CI], 0.69-0.856), and the pooled specificity was 80.3% (95% CI, 0.75-0.86). The sensitivity and specificity of the IGRA were 82.1% (95% CI, 0.78-0.86) and 81.1% (95% CI, 0.75-0.86), respectively, both higher than the TST. However, the TBST exhibited the highest specificity, at 98.5% (95% CI, 0.96-1.00), with a sensitivity of 78.7% (95% CI, 0.68-0.88), which was between that of the IGRA and TST. Subgroup analysis found that population categories and reference standards, among other factors, may be attributed to heterogeneity. In addition, the TST and IGRA add-on TBST can significantly improve diagnostic accuracy. In our study, the IGRA showed higher sensitivity, whereas the TBST showed higher specificity. Interestingly, under certain conditions, TST add-on TBST and IGRA add-on TBST showed better accuracy than TST and IGRA alone and could provide more effective guidance for clinical practice (PROSPERO CRD42023420136).

Keywords: IGRA; TST; diagnosis; diagnostic test accuracy; meta-analysis; the Mycobacterium tuberculosis antigen-based skin test; tuberculosis.

Figure 1

PRISMA flow diagram.

Figure 2

NMA graphs of sensitivity (A) and specificity (B). Nodes represent different diagnostic methods and sample sources, and connecting lines represent head-to-head comparisons. The size of the node is related to the number of studies. The thickness of the connecting lines indicates a greater number of comparisons between the two tests.

Figure 3

Forest plots of pooled sensitivity for all included studies. TP, true positive; FN, false negative [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68].

Figure 4

Forest plots of pooled specificity for all included studies. TN, true negative; FP, false positive [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68].

Figure 5

SROC curves and Deeks’ funnel plots for different populations. The total population (A), the BCG-vaccinated population (B), and the Deeks’ funnel plots for the total population (C) and the BCG-vaccinated population (D). Curves are shown as straight lines; each study is shown as a circle; summary operating point estimates corresponding to total sensitivity and specificity are shown as red squares; the 95% confidence intervals are shown as dotted lines. SENS: sensitivity; SPEC: specificity.

Figure 6

Fagan nomograms for different populations. The total population (A) and the BCG-vaccinated population (B).