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Predicting malignancy risk of lung nodules diagnosed as indeterminate on radial endobronchial ultrasound guided biopsy
( Sungmin Zo ) , ( Kyungjong Lee ) , ( Sook-young Woo ) , ( Seonwoo Kim ) , ( Ho Yun Lee ) , ( Byeong-ho Jeong ) , ( Sang-won Um ) , ( Hojoong Kim )
UCI I410-ECN-0102-2021-500-000608518
This article is 4 pages or less.
* This article is free of use.

Background: Advancement of technology has improved diagnostic sensitivity of radial endobronchial ultrasound (EBUS). Also, image characteristics of radial EBUS provide additional information of risk for malignancy of a lung nodule. However, when indeterminate radial EBUS guided biopsy results, such as atypical cell, fibrosis and inflammation are reported, there is no consensus among doctors whether to consider re-biopsy or surgery, or to observe with follow up. In this study, first, we identified malignancy associated risk factors from radial EBUS image findings, clinical and radiological factors. Second, based on identified risk factors, we constructed a nomogram to predict the risk of malignancy in indeterminate biopsy results. Methods: This retrospective designed study included 157 patients, diagnosed as indeterminate with radial EBUS guided biopsy from January 2017 to December 2018. Medical records, Chest Computed tomography (CT), radial EBUS images and final diagnosis results were reviewed. Patients were randomly divided into training and validation sets. The factors related to malignancy were identified through logistic regression analysis, and nomogram was constructed using the training set and subsequently applied to the validation set. Results: Through univariate and multivariate analysis, upper lobe location, spiculation, presence of satellite nodules, echogenicity, presence of dot or linear arc and patency of vessels and bronchus were identified as predictors. The nomogram was constructed based on predictors. The area under the receiver operating characteristic curve (AUC) value of constructed nomogram was 0.858 (0.786-0.930) using radiological factors, and improved to 0.952 (0.914-0.990) when radial EBUS factors was added. The calibration curve showed optimal agreement between the malignant probability as predicted by nomogram and the actual probability. Conclusions: The nomogram constructed in this study could be utilized in predicting the probability of malignancy in lung nodules diagnosed as indeterminate on radial EBUS, and may help in selecting patients who are at high risk for malignancy.

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