Chen Haiyan, Tong Zhaowei, Zhong Jianfeng, Tong Yong, Zeng Qingqiu, Shen Bin, Song Qun, Qian Fuchu, Xiao Xin
Department of Infection, Huzhou Central Hospital, Huzhou, Zhejiang, China.
Department of Clinical Medicine, Huzhou University, Huzhou, Zhejiang, China.
Front Public Health. 2025 Jul 22;13:1588196. doi: 10.3389/fpubh.2025.1588196. eCollection 2025.
This study aimed to develop and validate a reliable nomogram based on clinical factors to predict development of multidrug-resistant tuberculosis (MDR-TB) associated with individuals with tuberculosis (TB), so as to reduce the harm and economic burden caused by disease progression.
The study included 4,251 individuals with TB who received treatment at Huzhou Central Hospital between January 2016 and December 2023, excluding 87 individuals because of infection with non-TB mycobacterium or incomplete information (including missing laboratory or clinical data). A total of 4,164 individuals (2,261 sputum smear-positive and 1,903 sputum smear-negative patients) were ultimately included in the analysis. This analysis incorporated clinical baseline presentations, demographic information, imaging findings, laboratory results, and clinical diagnoses to develop a predictive model for MDR-TB.
This study demonstrated that sex, age, a history of anti-TB therapy, body mass index (BMI) ≤ 18.5, smoking history, occupation, previously diagnosed TB, pulmonary cavitation, comorbidities, poverty, and C-reactive protein (CRP) ≥ 37.3 mg/L were major risk factors for MDR-TB in patients with TB. The area under the receiver operating characteristic (ROC) curve was 0.902 for the training group and 0.909 for the validation group. Calibration curve analysis revealed that the predicted and actual incidence rates of MDR-TB in the two groups were in good agreement, whereas decision curve analysis (DCA) indicated that the predictive model resulted in better clinical benefit.
The nomogram model established in this study included 11 clinical characteristics and demographic features of patients with TB, which may be valuable for predicting MDR-TB.
本研究旨在基于临床因素开发并验证一种可靠的列线图,以预测结核病(TB)患者发生耐多药结核病(MDR-TB)的情况,从而减少疾病进展所造成的危害和经济负担。
本研究纳入了2016年1月至2023年12月期间在湖州市中心医院接受治疗的4251例TB患者,排除了87例因感染非结核分枝杆菌或信息不完整(包括实验室或临床数据缺失)的患者。最终共有4164例患者(2261例痰涂片阳性和1903例痰涂片阴性患者)纳入分析。该分析纳入了临床基线表现、人口统计学信息、影像学检查结果、实验室检查结果和临床诊断,以建立MDR-TB的预测模型。
本研究表明,性别、年龄、抗结核治疗史、体重指数(BMI)≤18.5、吸烟史、职业、既往诊断的TB、肺空洞、合并症、贫困以及C反应蛋白(CRP)≥37.3mg/L是TB患者发生MDR-TB的主要危险因素。训练组的受试者工作特征(ROC)曲线下面积为0.902,验证组为0.909。校准曲线分析显示,两组中MDR-TB的预测发病率与实际发病率吻合良好,而决策曲线分析(DCA)表明该预测模型具有更好的临床效益。
本研究建立的列线图模型纳入了TB患者的11项临床特征和人口统计学特征,可能对预测MDR-TB具有重要价值。