The innovative diagnostic model facilitates the differentiation between non - tuberculous mycobacterial lung disease and pulmonary tuberculosis

Objectives To construct a differential diagnostic model for Non-Tuberculous Mycobacterial Lung Disease (NTM-LD) and Pulmonary Tuberculosis Lung Disease (PTB-LD). Methods Retrospective analysis of 300 NTM-LD and 300 PTB-LD patients (pathogen-confirmed) was performed. Patients were randomly split into training (2/3) and validation (1/3) sets. CT imaging, clinical data, and symptoms were analyzed. Logistic regression identified significant discriminative features, followed by random forest modeling to develop a diagnostic tool with web-based calculator. Model performance was validated using the independent validation set. Results Univariate and multivariate analyses identified key discriminative factors ( P Conclusions The model constructed based on patients' CT imaging, basic clinical data, and symptomatic signs demonstrates commendable performance in the differential diagnosis of NTM-LD and PTB-LD, offering a convenient and practical auxiliary tool for clinical practice.