Zhang Wei, Liu Haiqing, Li Tuantuan, Jiang Ying, Cao Xiaoyu, Chen Li, Zhou Lili
The Second People's Hospital of Fuyang City, Fuyang, Anhui, People's Republic of China.
Infect Drug Resist. 2024 Jul 23;17:3189-3197. doi: 10.2147/IDR.S467257. eCollection 2024.
Investigate the differences in clinical manifestations, imaging features, and associated inflammatory markers between Nontuberculous Mycobacterial Pulmonary Disease (NTM-PD) and Pulmonary Tuberculosis (PTB), identify potential risk factors for NTM-PD, and establish a logistic regression model to evaluate its diagnostic value.
Baseline data were collected from 145 patients with NTM-PD and 206 patients with PTB. Propensity score matching (PSM) was utilized to achieve a 1:1 match between the two groups, resulting in 103 matched pairs. The differences in comorbidities, imaging features, and inflammatory markers were compared between the two groups. Multivariate binary logistic regression analysis was conducted to identify independent influencing factors, and the diagnostic value of the established model was evaluated.
After matching, significant differences were observed between the NTM-PD group and the PTB group in terms of diabetes, bronchiectasis, chronic obstructive pulmonary disease(COPD), cystic and columnar changes, lung cavity presentation, and monocyte percentage (MONO%), lymphocyte count (LYMPH#), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) (0.05). Logistic regression analysis confirmed that diabetes, bronchiectasis, COPD, and lung cavities were risk factors for NTM-PD. The established regression analysis model was analyzed by the Receiver Operating Characteristic (ROC) curve, the Area Under the Curve (AUC) was obtained as 0.795 (0.001, 95% CI 0.734-0.857). At a Youden index of 0.505, the sensitivity was 84.5% and the specificity was 66.6%. The Hosmer-Lemeshow test was used to evaluate the model's calibration, with a chi-square value of 11.023 and =0.200>0.05, indicating no significant difference between predicted and observed values.
For patients without diabetes but with bronchiectasis, COPD, and imaging characteristics of lung cavities, a high level of vigilance and active differential diagnosis for NTM-PD should be exercised. Given that the clinical manifestations of NTM-PD are similar to those of PTB, a detailed differential diagnosis is necessary during the diagnostic process to avoid misdiagnosis.
探讨非结核分枝杆菌肺病（NTM-PD）与肺结核（PTB）在临床表现、影像学特征及相关炎症标志物方面的差异，识别NTM-PD的潜在危险因素，并建立逻辑回归模型评估其诊断价值。
收集145例NTM-PD患者和206例PTB患者的基线数据。采用倾向评分匹配（PSM）方法使两组达到1:1匹配，最终得到103对匹配病例。比较两组患者的合并症、影像学特征及炎症标志物的差异。进行多因素二元逻辑回归分析以确定独立影响因素，并评估所建立模型的诊断价值。
匹配后，NTM-PD组与PTB组在糖尿病、支气管扩张、慢性阻塞性肺疾病（COPD）、囊柱状改变、肺空洞表现以及单核细胞百分比（MONO%）、淋巴细胞计数（LYMPH#）、血小板与淋巴细胞比值（PLR）和淋巴细胞与单核细胞比值（LMR）方面存在显著差异（P<0.05）。逻辑回归分析证实，糖尿病、支气管扩张、COPD及肺空洞是NTM-PD的危险因素。通过受试者工作特征（ROC）曲线对所建立的回归分析模型进行分析，曲线下面积（AUC）为0.795（95%CI 0.734-0.857，P<0.001）。在约登指数为0.505时，灵敏度为84.5%，特异度为66.6%。采用Hosmer-Lemeshow检验评估模型的校准情况，卡方值为11.023，P=0.200>0.05，表明预测值与观察值之间无显著差异。
对于无糖尿病但有支气管扩张、COPD及肺空洞影像学特征的患者，应高度警惕并积极进行NTM-PD的鉴别诊断。鉴于NTM-PD的临床表现与PTB相似，在诊断过程中需进行详细的鉴别诊断以避免误诊。
