A nomogram for predicting the risk of pulmonary fungal infection for patients with pulmonary tuberculosis

Abstract

Abstract Background: Pulmonary fungal infection is one of the common complications in patients with pulmonary tuberculosis(PTB).The aim of this study was to construct a nomogram to predict the risk of pulmonary fungal infection in patients with PTB.Methods: The present case control study retrospectively collected materials of 286 patients affected by PTB and received treatment from 2016.12.6-2021.12.6, in Beijing Chest Hospital, Capital Medical University. As control subjects, patients with sex and address corresponding to those of the case subjects were included in the study at a proportion of 1 controls for every case subject. These 286 patients were randomly divided into a training set and an internal validation set at a ratio of 3:1.Chi-square test and logistic regression analysis were performed in the training set, and a nomogram was developed using selected predictors. Then a bootstrapping procedure was used for internal validation.Results: Seven variables [illness course, pulmonary avitation, advanced antibiotics were used for at lest 1 week, chemotherapy or immunosuppressants, surgery, bacterial infection in the lungs, hypoproteinemia] were finally validated and used to develop a nomogram. The nomogram showed good discrimination capability for both training set[area under the curve (AUC) =0.860, 95% confidence interval (CI) = 0.811–0.909] and internal validation set(AUC =0.884, 95% CI = 0.799–0.970). Its calibration curves also showed that the probabilities as predicted by the nomogram displayed a satisfied consistence with the actual probability for both training set and internal validation set.Conclusions: We developed a nomogram that can predict the risk of pulmonary fungal infection in patients with PTB. It showed potential clinical utility.