Establishment and internal validation of the model and the nomogram
PTB, pulmonary fungal coinfection
PULMONARY CAVITATION, REGRESSION, BACTERIAL PNEUMONIA, HYPOPROTEINEMIA
We developed a predictive model for assessing the probability of pulmonary fungal coinfection in PTB patients based on the aforementioned 7 predictors. The Odds Ratios of predictors entered in the model were as follows:1 year < illness course ≤ 5 years, 3.978; 5 years < illness course ≤ 10 years, 4.180; illness course > 10 years, 11.368; pulmonary cavitation, 3.460; use of broad-spectrum antibiotics for at least 1 week, 3.153; chemotherapy or immunosuppressants, 20.646; surgery, 2.157; bacterial pneumonia, 6.645, and hypoproteinemia, 6.054. As shown in Figs. ROC curve of the established model in training setROC curve of the established model in validation set. *ROC curve of the established model and in the internal validation. AUC (1) shows the discrimination in the model, and AUC (2) of the internal validation. ROC, receiver operating characteristic; AUC, area under the curveCalibration curve in training setCalibration curve in validation setTo provide physicians with a quantitative tool for individualized prediction of pulmonary fungal coinfection, a nomogram was constructed according to the results of multivariable logistic regression (Fig. Nomogram for predicting the probability of pulmonary fungal coinfection in PTB patients. *Nomogram for predicting the probability of pulmonary fungal coinfection in PTB patients and its predictive performance. First, find the points for each predictor (variable) of a patient on the uppermost rule; then, add all points to calculate the “total points;” finally find the corresponding predicted probability of pulmonary fungal coinfection on the lowest rule.