Abstract
INTRODUCTION: Nontuberculous mycobacteria (NTM) and pulmonary tuberculosis (PTB) are difficult to distinguish in initial acid-fast bacilli (AFB) smear-positive patients. OBJECTIVES: Establish a predictive model to identify more effectively NTM infections in initial AFB patients. METHODS: Consecutive AFB smear-positive patients in the Respiratory Department of Shanghai Pulmonary Hospital from January 2019 to February 2020 were retrospectively analysed. A multivariate regression was used to determine the independent risk factors for NTM. A receiver operating characteristic (ROC) curve was used to determine the model's predictive discrimination. The model was validated internally by a calibration curve and externally for consecutive AFB smear-positive patients from March to June 2020 in this institution. RESULTS: Presenting with haemoptysis, bronchiectasis, a negative QuantiFERON tuberculosis (QFT) test and being female were characteristics significantly more common in patients with NTM (P ≤ 0.001), when compared with PTB. The involvement of right middle lobe, left lingual lobe and cystic change was more commonly seen on chest high-resolution computed tomography (HRCT) in patients with NTM (P < 0.05), compared with PTB. Multivariate regression showed female, bronchiectasis, negative test for QFT and right middle lobe lesion were independent risk factors for NTM (P < 0.05). A ROC curve showed a sensitivity and specificity of 85.9% and 93.4%, respectively, and the area under the curve (AUC) was 0.963. Moreover, internal and external validation both confirmed the effectiveness of the model. CONCLUSIONS: The predictive model would be useful for early differential diagnosis of NTM in initial AFB smear-positive patients.