Zhang W, Liu H, Li T, Jiang Y, Cao X, Chen L, Zhou L. The Study of Associated Factors for Non-Tuberculous Mycobacterial Pulmonary Disease Compared to Pulmonary Tuberculosis: A Propensity Score Matching Analysis.
Infect Drug Resist 2024;
17:3189-3197. [PMID:
39070718 PMCID:
PMC11283239 DOI:
10.2147/idr.s467257]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 07/20/2024] [Indexed: 07/30/2024] Open
Abstract
Objective
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.
Methods
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.
Results
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) (P<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 (P<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 P=0.200>0.05, indicating no significant difference between predicted and observed values.
Conclusion
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.
Collapse