合并活动性肺结核的2型糖尿病患者炎性细胞因子表达谱与抗结核治疗失败的相关性研究

doi:10.19871/j.cnki.xfcrbzz.2025.02.009

摘要/Abstract

摘要： 目的探究合并活动性肺结核（active tuberculosis,ATB）的2型糖尿病（type 2 diabetes mellitus,T2DM）患者（以下简称ATB-T2DM）炎性细胞因子表达谱与抗结核化学治疗失败的相关性。方法选取2020年12月至2023年9月于新疆维吾尔自治区人民医院接受治疗的294例ATB-T2DM患者作为研究对象,所有患者均接受6个月的正规抗结核治疗,根据启动抗结核治疗后12个月内治疗结局划分为抗结核治疗失败组（73例）和抗结核治疗成功组（221例）。对比两组患者基础临床资料、血清炎性细胞因子[白介素（interleukins,ILs）、CXC趋化因子配体（CXC chemokine ligands,CXCLs）]表达谱,通过二元Logistic回归分析评价抗结核治疗失败相关的危险因素,通过受试者操作特征曲线（receiver operating characteristic curve,ROC曲线）及曲线下面积（area under curve,AUC）评价各危险因素独立及联合预测患者抗结核治疗失败的效能,通过校准曲线及决策曲线评价各危险因素联合预测的准确性。结果入组患者中抗结核治疗失败73例,抗结核治疗失败率为24.83%。抗结核治疗成功组和抗结核治疗失败组间合并肺空洞患者比例存在差异（P<0.05）;抗结核治疗失败组患者IL-1β、IL-6、IL-10、CXCL2、CXCL5、CXCL8、CXCL10水平均显著高于抗结核治疗成功组患者（P<0.05）;二元Logistic回归分析表明血清IL-1β、IL-6、IL-10、CXCL5、CXCL8、CXCL10水平较高均为抗结核治疗失败的危险因素（P<0.05）;ROC曲线分析表明IL-1β、IL-6、IL-10、CXCL5、CXCL8、CXCL10独立及联合预测ATB-T2DM患者抗结核治疗失败的AUC分别为0.649、0.665、0.617、0.643、0.626、0.650、0.819,其中联合预测效能显著高于各因素独立预测效能（P<0.05）;校准曲线提示基于ILs、CXCLs的联合预测模型拟合度较好（Hosmer-Lemeshow χ²=10.068,P=0.260）,决策曲线提示该模型在风险阈值0~0.9范围内均具有较高的使用净收益。结论 ATB-T2DM患者抗结核化学治疗结局与IL-1β、IL-6、IL-10、CXCL5、CXCL8、CXCL10水平密切相关,基于上述指标构建的抗结核治疗失败风险模型具有较高的预测价值。

关键词: 活动性肺结核, 糖尿病, 白介素, 趋化因子, 治疗失败

Abstract: Objective To explore the correlation between the expression profiles of inflammatory cytokines and anti-tuberculosis treatment failure in type 2 diabetes mellitus (T2DM) patients complicated with active tuberculosis (ATB) (hereinafter referred to as ATB-T2DM patients). Method A total of 294 ATB-T2DM patients who were treated in People's Hospital of Xinjiang Uygur Autonomous Region from December 2020 to September 2023 were selected as the research subjects. All patients received 6 month standard anti-tuberculosis treatment. According to the treatment outcomes within 12 months after starting anti-tuberculosis treatment, they were divided into the treatment failure group(73cases) and the treatment success group(221cases). The basic clinical data and the expression profiles of serum inflammatory cytokines [interleukins (ILs), CXC chemokine ligands (CXCLs)] of the two groups were compared. Binary logistic regression analysis was used to evaluate the risk factors associated with treatment failure. The receiver operating characteristic curve (ROC) and the area under the curve (AUC curve) were employed to assess the efficacy of each risk factor in independently and jointly predicting treatment failure. The calibration curve and the decision curve were utilized to evaluate the accuracy of the joint prediction of each risk factor. Result Among the enrolled patients, 73 cases had treatment failure, with a treatment failure rate of 24.83%. There was a significant difference in the proportion of patients with pulmonary cavities between the treatment success group and the treatment failure group (P<0.05). The levels of IL-1β, IL-6, IL-10, CXCL2, CXCL5, CXCL8, and CXCL10 in the treatment failure group were significantly higher than those in the treatment success group (P<0.05). Binary logistic regression analysis showed that high levels of serum IL-1β, IL-6, IL-10, CXCL5, CXCL8, and CXCL10 were all risk factors for treatment failure (P<0.05). ROC curve analysis indicated that the AUCs of IL-1β, IL-6, IL-10, CXCL5, CXCL8, CXCL10 in independently and jointly predicting anti-tuberculosis treatment failure in ATB-T2DM patients were 0.649, 0.665, 0.617, 0.643, 0.626, 0.650, and 0.819 respectively. The joint prediction efficacy was significantly higher than that of each factor independently (P<0.05). The calibration curve suggested that the joint prediction model based on ILs and CXCLs had a good fit (Hosmer-Lemeshow χ²=10.068, P=0.260), and the decision curve indicated that this model had a high net benefit of use within the risk threshold range of 0-0.9. Conclusion The anti-tuberculosis treatment outcomes of ATB-T2DM patients are closely related to the levels of IL-1β, IL-6, IL-10, CXCL5, CXCL8, and CXCL10. The risk model for treatment failure constructed based on the above-mentioned indicators has a high predictive value.

Key words: Active tuberculosis, Diabetes mellitus, Interleukins, Chemokines, Treatment failure

中图分类号:

R521

李敬萍, 刘凯, 卡迪丽娅·阿布都卫力. 合并活动性肺结核的2型糖尿病患者炎性细胞因子表达谱与抗结核治疗失败的相关性研究[J]. 新发传染病电子杂志, 2025, 10(2): 47-53.

Li Jingping, Liu Kai, Kadiliya Abuduweili. Correlation between Inflammatory cytokine expression profiles and anti-tuberculosis treatment failure in type 2 diabetes mellitus patients complicated with active tuberculosis[J]. Electronic Journal of Emerging Infectious Diseases, 2025, 10(2): 47-53.

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