Abstract: Objective　The aim of this study was to observe the expression levels and clinical significance of peripheral blood interferon γ-inducible protein-10 (IP-10) and various cytokines in patients with different infection statuses of tuberculosis and to assess the efficacy of latent tuberculosis infection (LTBI) in the progression to active tuberculosis (ATB). Methods　Seventy-six outpatient and inpatient cases from the Third People's Hospital of Kunming were collected and analyzed from March 2023 to February 2024. The patients were divided into three groups: ATB group (31 cases, 17 males, median age 33 years), LTBI group (27 cases, 17 males, median age 29 years), and healthy control (HC) group (18 cases, 11 males, median age 25 years). Peripheral blood samples from the three groups were taken and the expression levels of IP-10 and cytokines IL-6, IL-4, IL-8, IL-10, IL-12, IL-2, and TNF-α were detected using enzyme-linked immunosorbent assay (ELISA) methods. The t-test was used for normally distributed samples, while the Mann-Whitney U test was used for skewed distributions. For comparisons between multiple groups, the Kruskal-Wallis H test was first employed, followed by Dunn's multiple comparison test for pairwise comparisons. Finally, the effectiveness of each cytokine in distinguishing different population groups was analyzed. Results　The expression levels of peripheral blood IP-10 were higher in the LTBI and ATB groups than in the HC group, but the area under the curve (AUC) of the receiver operating characteristic (ROC) of the subjects showed moderate sensitivity (AUC:0.7-0.9) and low specificity (AUC:0.5-0.7). The IL-6 expression levels were in the order of high to low in the ATB group, LTBI group, and HC group, where the HC group was significantly lower than the ATB and LTBI groups (F=12.15, P<0.001). The sensitivity and specificity of the ATB group were higher than those in the HC group. Conclusions　IP-10 exhibits unique advantages in distinguishing different tuberculosis statuses. The predictive efficacy of a single cytokine is limited. Combining multiple cytokines such as IL-6 with clinical manifestations, a more accurate and comprehensive prediction model can be established.