Computed tomography-guided cutting needle biopsy for lung nodules: when the biopsy-based benign results are real benign

Abstract

Abstract Background Computed tomography (CT)-guided cutting needle biopsy (CNB) is an effective diagnostic method for lung nodules (LNs). The false-negative rate of CT-guided lung biopsy is reported to be up to 16%. This study aimed to determine the predictors of true-negative results in LNs with CNB-based benign results. Methods From January 2011 to December 2015, 96 patients with CNB-based nonspecific benign results were included in this study as the training group to detect predictors of true-negative results. From January 2016 to December 2018, an additional 57 patients were included as a validation group to test the reliability of the predictors. Results In the training group, a total of 96 patients underwent CT-guided CNB for 96 LNs. The CNB-based results were true negatives for 82 LNs and false negatives for 14 LNs. The negative predictive value of the CNB-based benign results was 85.4% (82/96). Univariate and multivariate logistic regression analyses revealed that CNB-based granulomatous inflammation (P = 0.013, hazard ratio = 0.110, 95% confidential interval = 0.019–0.625) was the independent predictor of true-negative results. The area under the receiver operator characteristic (ROC) curve was 0.697 (P = 0.019). In the validation group, biopsy results for 47 patients were true negative, and 10 were false negative. When the predictor was used on the validation group, the area under the ROC curve was 0.759 (P = 0.011). Conclusions Most of the CNB-based benign results were true negatives, and CNB-based granulomatous inflammation could be considered a predictor of true-negative results.

Keywords

• Computed tomography
• Cutting needle biopsy
• Lung nodule
• Benign