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. 2025 Jan-Dec:80:100750.
doi: 10.1016/j.clinsp.2025.100750. Epub 2025 Aug 16.

Risk factors and nomogram prediction model for pneumothorax after CT-guided coaxial biopsy combined with microwave ablation in ground-glass nodules

Canxing Wu  1 , Yangtao Zhao  1 , Mengjun Chen  1 , Jun Ma  2
Affiliations

Risk factors and nomogram prediction model for pneumothorax after CT-guided coaxial biopsy combined with microwave ablation in ground-glass nodules

Canxing Wu et al. Clinics (Sao Paulo). 2025 Jan-Dec.

Abstract

Objective: To identify risk factors and develop a validated nomogram for predicting pneumothorax after CT-guided coaxial biopsy with synchronous Microwave Ablation (MWA) in Ground-Glass Nodules (GGNs).

Methods: 383 GGN patients were divided into a training set (n = 268) and a validation set (n = 115) in a 7:3 ratio. Univariate and multivariate logistic regression were employed to identify risk factors, followed by the construction of a nomogram model. Receiver Operating Characteristic (ROC) curves and calibration plots were generated to evaluate model performance, with further validation in the independent cohort. Decision curve analysis was applied to assess clinical utility.

Results: Pneumothorax occurred in 72 cases (26.87 %) in the training set and 32 cases (27.83 %) in the validation set. Multivariate logistic regression revealed that BMI, lesion location, lesion depth, needle diameter, and number of punctures were independent risk factors for pneumothorax (all p < 0.05). Factor importance ranking was as follows: number of punctures > BMI > lesion depth > lesion location > needle diameter. The nomogram demonstrated robust calibration and predictive accuracy, with C-index values of 0.877 (training set) and 0.897 (validation set). The areas under the ROC curve (AUC) were 0.875 (95 % CI: 0.825-0.926) and 0.897 (95 % CI: 0.829-0.965), respectively. Sensitivity and specificity were 0.855/0.813 (training set) and 0.765/0.823 (validation set).

Conclusion: Key determinants of postprocedural pneumothorax in GGN patients were identified through logistic regression and nomogram modeling. The validated predictive model exhibited excellent discriminative ability and clinical applicability, providing a scientific basis for individualized risk assessment and intervention strategies.

Keywords: CT-guided percutaneous biopsy; Ground-glass nodule; Logistic regression; Microwave ablation; Pneumothorax.

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Conflict of interest statement

Declaration of competing interest The authors declare no conflicts of interest.

Figures

Fig 1
Fig. 1
Ranking of the importance of influencing factors.
Fig 2
Fig. 2
Nomogram model for pneumothorax after synchronous MWA treatment combined with CT-guided coaxial cannula puncture biopsy in patients with GGN. Note: X1, BMI; X2, Lesion location; X3, Lesion depth; X4, Puncture needle diameter; X5, Number of punctures.
Fig 3
Fig. 3
Calibration curves are presented (Curve A represents the calibration curve for the training set, while Curve B represents that for the validation set).
Fig 4
Fig. 4
ROC curves (A is the ROC curve of the training set, B is the ROC curve of the validation set).
Fig 5
Fig. 5
Decision curves (A represents the decision curve of the training set, B represents the decision curve of the validation set).
See this image and copyright information in PMC

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