Analysis of the diagnostic value of molecular diagnostic techniques combined with cytokine expression for differentiating pulmonary tuberculosis from nontuberculous mycobacterial lung infections

doi:10.19871/j.cnki.xfcrbzz.2025.05.010

Abstract

Abstract: Objective To investigate the diagnostic efficacy of integrating molecular diagnostic methods with cytokine expression for distinguishing from pulmonary tuberculosis and nontuberculous mycobacterial(NTM) lung disease. Method A study was carried out to retrospectively analyze the clinical data of 70 patients diagnosed with pulmonary tuberculosis (referred to as the observation group) and 40 patients with NTM lung disease (the control group) treated at our hospital between January 2022 and July 2024. All individuals underwent testing using Xpert MTB/RIF Ultra, and their peripheral blood serum cytokine expression profiles were assessed, including interleukin (IL)-2, IL-4, IL-5, IL-6, IL-10, IL-12/23p40, IL-17 and tumor necrosis factor α (TNF-α). Binary logistic regression analysis was performed to investigate risk factors risk factors closely associated with the accurate identification of pulmonary tuberculosis. The effectiveness of each risk factor in combination for discriminating pulmonary tuberculosis was assessed using methods such as the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Result The detection rate of Xpert MTB/RIF Ultra testing and the mean levels of IL-4, IL-6, and IL-12/23p40 in the observation group were significantly higher compared to those in the control group, whereas the mean level of TNF-α was significantly lower than that in the control group (P<0.05). Univariate and multivariate logistic regression analysis demonstrated that Xpert MTB/RIF Ultra testing, IL-6, IL-12/23p40, and TNF-α were independent factors influencing the diagnosis of pulmonary tuberculosis (P< 0.05). The ROC curve analysis revealed that the AUC (95%CI) for the combined differential diagnosis of pulmonary tuberculosis utilizing Xpert MTB/RIF Ultra testing, IL-6, IL-12/23p40, and TNF-α was 0.889 (0.821-0.957). Both the calibration curve and DCA curve confirmed that the combined diagnostic model based on these parameters exhibited high accuracy and substantial clinical returns. Conclusion The efficacy of the model utilizing the molecular diagnostic method Xpert MTB/RIF Ultra together with IL-6, IL-12/23p40, and TNF-α in discriminating between pulmonary tuberculosis and NTM lung disease is considerable.

Key words: Pulmonary tuberculosis, Nontuberculous mycobacteria, Molecular diagnostic techniques, Cytokines, Differential diagnosis

CLC Number:

R521
R517.9

Zhao Yun, Xu Fang, Wang Chen, Sheng Fang. Analysis of the diagnostic value of molecular diagnostic techniques combined with cytokine expression for differentiating pulmonary tuberculosis from nontuberculous mycobacterial lung infections[J]. Electronic Journal of Emerging Infectious Diseases, 2025, 10(5): 53-58.

References

[1] 吕恒梁, 张馨, 张文义, 等. 肺结核流行病学特征及影响因素研究进展[J]. 疾病监测, 2024, 39(2): 207-214.
[2] 何翼君, 成君, 高磊. 循序渐进:系统性开展结核分枝杆菌潜伏感染流行病学调查[J]. 中国防痨杂志, 2024, 46(1):1-7.
[3] 许金卫, 张鑫, 陈震. 非结核分枝杆菌肺病与继发性肺结核的CT表现分析[J].新发传染病电子杂志, 2020, 5(02):113-117.
[4] 赵俊鹏, 刘海涛, 石凤玲, 等. 结核分枝杆菌临床实验室诊断及耐药检测技术研究进展[J].新发传染病电子杂志, 2022, 7(03):78-83.
[5] 丁彩红, 王余余, 王庆, 等. Xpert MTB/RIF Ultra快速诊断涂阴肺结核的临床价值[J]. 解放军医学杂志, 2023, 48(7): 761-767.
[6] PARK M, KON OM.Use of Xpert MTB/RIF and Xpert Ultra in extrapulmonary tuberculosis[J]. Expert Rev Anti Infect Ther, 2021, 19(1):65-77.
[7] 来元春. 结核病实验室检测技术研究进展[J].中国防痨杂志, 2024,46(S1):322-324.
[8] 中华医学会结核病学分会. 肺结核诊断和治疗指南[J]. 中国实用乡村医生杂志, 2013, 20(2): 7-11.
[9] GILLER DB, SHCHERBAKOVA GV, GERASIMOV AN, et al.Surgical Treatment of Nontuberculous Mycobacterial Pulmonary Disease and a Combination of Nontuberculous Mycobacterium Pulmonary Disease and Pulmonary Tuberculosis[J]. Int J Infect Dis, 2022, 120:12-21.
[10] 周冬梅, 王洲. 荧光定量聚合酶链反应检测脑脊液中结核分枝杆菌DNA对鉴别诊断结核性脑膜炎的应用价值分析[J].基层医学论坛, 2024, 28(4):127-129.
[11] 王桂荣,姜广路,魏国梅,等. 对硝基苯甲酸鉴别结核分枝杆菌复合群与非结核分枝杆菌的机制研究[J]. 临床肺科杂志,2016,21(10):1747-1750.
[12] 贾红彦, 董静, 张宗德, 等.结核分枝杆菌感染的免疫学检测技术研究进展及临床应用现状[J].中国防痨杂志, 2022, 44(7):720-726.
[13] 方梓昊, 赵文丽, 徐雁南, 等.基因分型方法在结核分枝杆菌分型中的应用进展[J].山东医药, 2024, 64(15):103-107.
[14] LI W D, JING S, GUO J W, et al.Performance of Xpert MTB/RIF Ultra and Xpert MTB/RIF for the Diagnosis of Tuberculosis through Testing of Formalin-fixed Paraffin-embedded Tissues[J].Biomedical and Environmental Sciences, 2019, 32(12):922-925.
[15] YU X, ZHANG T, KONG Y, et al.Xpert MTB/RIF Ultra outperformed the Xpert assay in tuberculosis lymphadenitis diagnosis: a prospective head-to-head cohort study[J]. Int J Infect Dis, 2022, 122:741-746.
[16] ZHANG P, LIU H, WANG H, et al.Performance of Xpert MTB/RIF Ultra for the Diagnosis of Pulmonary Tuberculosis Using Bronchoalveolar Lavage Samples in People Living with HIV/AIDS (PLWHA) in China: A Prospective Study[J]. HIV AIDS (Auckl). 2021, 13:905-916.
[17] HEIDARI L, RAFIEI DEHBIDI G, FARHADI A, et al.Simultaneous detection and differentiation of Mycobacterium tuberculosis and nontuberculous mycobacteria coexisting in patients with pulmonary tuberculosis by single-tube multiplex PCR[J]. Iran J Microbiol, 2023, 15(3):401-407.
[18] HAMILTON F, SCHURZ H, YATES TA, et al.Altered IL-6 signalling and risk of tuberculosis disease: a meta-analysis and Mendelian randomisation study. Preprint[J]. medRxiv, 2023, 2(7):23285472.
[19] 薛冰, 徐笛, 张峰波, 等. 血清IFN-γ、IL-4、IL-12、IL-23对肺结核免疫的作用研究[J].新疆医科大学学报, 2017,40(3):341-344.
[20] FENG Z, BAI X, WANG T, et al.Differential Responses by Human Macrophages to Infection With Mycobacterium tuberculosis and Nontuberculous Mycobacteria[J]. Front Microbiol, 2020,11:116.
[21] WANG H, RUAN G, LI Y, et al.The Role and Potential Application of IL-12 in the Immune Regulation of Tuberculosis[J]. Int J Mol Sci, 2025, 26(7):3106.
[22] KIREEV FD, LOPATNIKOVA JA, ALSHEVSKAYA AA, et al.Role of Tumor Necrosis Factor in Tuberculosis[J]. Biomolecules, 2025, 15(5):709.
[23] YUK JM, KIM JK, KIM IS, et al.TNF in Human Tuberculosis: A Double-Edged Sword[J]. Immune Netw, 2024, 24(1):e4.
[24] GIDON A, LOUET C, RØST LM, et al. The Tumor Necrosis Factor Alpha and Interleukin 6 Auto-paracrine Signaling Loop Controls Mycobacterium avium Infection via Induction of IRF1/IRG1 in Human Primary Macrophages[J]. mBio, 2021, 12(5):e0212121.