Construction of a prediction model for Non-tuberculous mycobacterial lung disease based on clinical characteristics and analysis of its application value

Abstract

Objective The objective of this study was to explore the differential clinical features between Nontuberculous mycobacterial pulmonary disease (NTM-PD) and pulmonary tuberculosis (PTB), and to develop a predictive model for the differential diagNosis of these two conditions. The study aimed to provide clinical guidance for the diagNosis and treatment of NTM-PD. Methods The study included 145 patients with NTM-PD and 206 patients with PTB, whose clinical characteristics,imaging findings,and inflammatory markers were compared.A binary logistic regression model was used to analyze the influencing factors and evaluate the predictive performance and calibration accuracy of the model. Results A comparative analysis of clinical, imaging, and inflammatory markers between NTM-PD and PTB groups revealed significant differences in demographics (age, gender, occupation, BMI), symptoms (dyspnea, loss of appetite, fever), risk factors (smoking, alcohol consumption history, diabetes), and comorbidities (bronchiectasis, emphysema, COPD, cystic-columnar, honeycomb, lung cavitation, MONo%; P < 0.05). Multivariate binary logistic regression identified gender and diabetes as protective, while bronchiectasis, COPD, and lung cavitation as risk factors. The model's predictive performance was strong with an AUC of 0.874 (95% CI 0.837 ~ 0.910; P < 0.001) and a Youden index of 0.611, yielding sensitivity of 83.4% and specificity of 77.7%. Model calibration was assessed by the Hosmer-Lemeshow test, showing no significant difference between predicted and observed values (χ²=7.895, P = 0.444 > 0.05). Conclusion In female patients without diabetes or underlying conditions such as bronchiectasis or COPD, when high-resolution computed tomography (HRCT) of the chest reveals predominantly cavitated lesions, it is imperative to give high priority to the differential diagnosis for possible NTM-PD, given its clinical resemblance to PTB. A meticulous distinction between these diagnoses is essential during the diagnostic process to prevent misdiagnosis.