Development and validation of a prediction model of pneumothorax after CT-guided coaxial core needle lung biopsy

Background Pneumothorax is the most common complication of computed tomography-guided coaxial core needle biopsy (CCNB) and may be life-threatening. We aimed to evaluate the risk factors and develop a model for predicting pneumothorax in patients undergoing computed tomography-guided CCNB, and to further determine its clinical utility. Methods Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for pneumothorax from 18 variables. A predictive model was established using multivariable logistic regression and presented as a nomogram based on a training cohort of 690 patients who underwent computed tomography-guided CCNB. The model was validated in 253 consecutive patients in the validation cohort and 250 patients in the test cohort. The area under the curve was used to determine the predictive accuracy of the proposed model. Results The risk factors associated with pneumothorax after computed tomography-guided CCNB were sex, patient position, lung field, lesion contact with the pleura, lesion size, distance from the pleura to the lesion, presence of emphysema adjacent to the biopsy tract, and crossing fissures. The predictive model that incorporated these predictors showed good predictive performance in the training cohort [area under the curve, 0.71 (95% confidence interval: 0.67–0.75)], validation cohort [0.71 (0.64–0.78)], and internal test cohort [0.68 (0.60–0.75)]. The nomogram also provided excellent calibration and discrimination, and decision curve analysis (DCA) demonstrated its clinical utility. Conclusions The predictive model showed good performance for pneumothorax after computed tomography-guided CCNB and may help improve individualized preoperative prediction.