Diagnostic Accuracy of a Simplified Interferon-Gamma Composite Index for Tuberculosis.

Abstract

Background: Tuberculosis (TB) is one of the most severe infectious diseases worldwide, making early and accurate diagnosis critical for improving patient outcomes. The interferon-gamma release assay (IGRA) is a commonly used diagnostic tool for TB. This study aimed to develop a simplified composite index to enhance the diagnostic accuracy and performance for TB.

Methods: This study included patients with suspected TB who visited our hospital between January 2022 and December 2023. The patients were categorized into three groups: pulmonary tuberculosis (PTB), extrapulmonary tuberculosis (EPTB), and non-tuberculosis (non-TB). A retrospective analysis of their clinical data and laboratory test results was conducted. We developed a Simplified Interferon-Gamma Composite Index (SIGCI) by integrating the IGRA, lymphocyte count, and adenosine deaminase (ADA). The diagnostic performance of SIGCI for PTB and EPTB was assessed using receiver operating characteristic (ROC) curve analysis.

Results: Among the 355 suspected TB patients, 84 were diagnosed with PTB, 68 with EPTB, and 203 with non-TB, resulting in a TB confirmation rate of 42.82%. In the PTB group, the proportion of male patients was significantly higher than in the EPTB and non-TB groups (73.81% vs. 52.94% vs. 56.59%, p < 0.05). Compared to the non-TB group, lymphocyte counts were significantly lower, while ADA levels were significantly higher in both the PTB and EPTB groups (p < 0.05). Spearman correlation analysis revealed a positive correlation between the IFN-γ release response value and lymphocyte count in both the PTB and EPTB groups (p < 0.05), However, there was no correlation between the IFN-γ release response value and lymphocyte count in the non-TB group (p > 0.05). The ROC curve analysis of the SIGCI for PTB diagnosis showed an area under the curve (AUC) of 0.854, with an optimal cutoff value of 200.7, sensitivity of 84.34%, and specificity of 80.79%. For EPTB diagnosis, the AUC of SIGCI was 0.909, with an optimal cutoff value of 159.2, sensitivity of 94.03%, and specificity of 79.19%. Compared to the use of IFN-γ release values and ADA alone, SIGCI demonstrated a significant advantage in the diagnosis of both PTB and EPTB.

Conclusions: The SIGCI developed in this study demonstrated excellent diagnostic performance for both PTB and EPTB, showing significant potential to improve the accuracy of early TB diagnosis.