Risk factors for bronchiectasis complicated with non-tuberculous Mycobacterium infection and establishment of prediction model

OBJECTIVE To explore the risk factors for bronchiectasis patients complicated with non-tuberculous Mycobacterium (NTM) infection and establish the nomogram prediction model and validate it. METHODS The patients who were diagnosed with bronchiectasis and infections in The First Affiliated Hospital of Zhengzhou University from May 2021 to Oct. 2024 were enrolled in the study, the clinical data of the enrolled patients were retrospectively analyzed, the patients were grouped according to the status of complication with NTM infection. The independent predictive factors were screened out through LASSO regression and multivariate logistic regression so as to establish the nomogram model. The accuracy, calibration blot and clinical practicability of the model were assessed through receiver operating characteristic (ROC) curve. RESULTS Of the 329 bronchiectasis patients complicated with infections, 99 (30.09%) were complicated with NTM infection. Totally 5 independent predictive factors, including age odds ratio (OR) =1.037,95%CI :1.008 to 1.066,P=0.012, involvement of middle lobe of the right lung (OR=2.136,95%CI:1.052 to 4.339,P=0.036), cavity (5.812(1.821 to 18.552)OR=5.812,95%CI:1.821 to 18.552, P=0.003), autoimmune disease (OR=18.444, 95%CI:1.705 to 199.468, P=0.016) and rise of white blood cell (OR=0.825,95%CI:0.727 to 0.936, P=0.003)), were screened out by Lasso regression and multivariate logistic regression. The area under the curve (AUC) of the nomogram model was 0.743(95%CI:0.671 to 0.815) in the training set, 0.739(95%CI:0.636 to 0.843) in the validation set. CONCLUSIONS The age, involvement of middle lobe of the right lung, cavity formation, autoimmune disease and WBC level are the independent predictive factors for the bronchiectasis complicated with NTM. The nomogram prediction model that is established based on the factors has high predictive efficiency.