Objective To construct and validate the efficacy of a risk prediction model for pneumothorax after CT-guided percutaneous pulmonary puncture biopsy(CT-PCNB)based on nomograms.Methods A total of 246 patients who underwent CT-PCNB examination in the hospital from October 2020 to October 2023 were selected and divided into training set(n=144)and validation set(n=102)using a random sampling method.In the training set,univariate and multivariate logistic regression analyses were performed to identify risk factors for pneumothorax after CT-PCNB.A nomogram model was constructed based on the identified risk factors,and its accuracy was validated using the validation set.Results Multifactorial logistic regression analysis showed that age≥60 years,concomitant underlying lung disease,lesion diameter<2 cm,distance from lesion to pleura≥10 mm,puncture through interlobular pleura,and≥2 pleural punctures were the risk factors for pneumothorax after CT-PCNB in the training set(P<0.05).A nomogram model was constructed based on these six factors.The ROC curve results for the training set showed an AUC of 0.852,sensitivity of 84.50%,and specificity of 67.50%.The nomogram model was validated using the validation set,with ROC curve results showing an AUC of 0.845,sensitivity of 83.00%,and specificity of 69.50%.There was no statistically significant difference between the predicted and actual values in both the training and validation sets(χ2=1.803,1.225;P>0.05),indicating clinical validity.Conclusion The nomogram model constructed based on the risk factors for pneumothorax after CT-PCNB has high predictive efficacy and is clinically meaningful.

Objective To construct and validate the efficacy of a risk prediction model for pneumothorax after CT-guided percutaneous pulmonary puncture biopsy(CT-PCNB)based on nomograms.Methods A total of 246 patients who underwent CT-PCNB examination in the hospital from October 2020 to October 2023 were selected and divided into training set(n=144)and validation set(n=102)using a random sampling method.In the training set,univariate and multivariate logistic regression analyses were performed to identify risk factors for pneumothorax after CT-PCNB.A nomogram model was constructed based on the identified risk factors,and its accuracy was validated using the validation set.Results Multifactorial logistic regression analysis showed that age≥60 years,concomitant underlying lung disease,lesion diameter<2 cm,distance from lesion to pleura≥10 mm,puncture through interlobular pleura,and≥2 pleural punctures were the risk factors for pneumothorax after CT-PCNB in the training set(P<0.05).A nomogram model was constructed based on these six factors.The ROC curve results for the training set showed an AUC of 0.852,sensitivity of 84.50%,and specificity of 67.50%.The nomogram model was validated using the validation set,with ROC curve results showing an AUC of 0.845,sensitivity of 83.00%,and specificity of 69.50%.There was no statistically significant difference between the predicted and actual values in both the training and validation sets(χ2=1.803,1.225;P>0.05),indicating clinical validity.Conclusion The nomogram model constructed based on the risk factors for pneumothorax after CT-PCNB has high predictive efficacy and is clinically meaningful.