Zo Sungmin, Woo Sook-Young, Kim Seonwoo, Lee Jung Eun, Jeong Byeong-Ho, Um Sang-Won, Kim Hojoong, Kwon O Jung, Lee Ho Yun, Lee Kyungjong
Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
Statistics and Data Center, Samsung Medical Center, Seoul 06351, Korea.
J Clin Med. 2020 Nov 13;9(11):3652. doi: 10.3390/jcm9113652.
The next diagnostic step in cases of indeterminate radial probe endobronchial ultrasound (radial EBUS)-guided biopsy results remains uncertain. This study aimed to identify risk factors for malignancy based on clinical findings, chest computed tomography (CT), and radial EBUS images, and to estimate the risk of malignancy in lung nodules that showed indeterminate radial EBUS-guided biopsy results by constructing a nomogram. This retrospective study included 157 patients with indeterminate results on an initial radial EBUS biopsy performed at the Samsung Medical Center from January 2017 to December 2018, but with a definitive final diagnosis. Medical records, chest CT, radial EBUS images, and the final diagnoses were reviewed. Patients were randomly divided into training and validation sets. Factors related to malignancy were identified through logistic regression analysis, and a nomogram was constructed using the training set and subsequently applied to the validation set. Six factors in univariable and multivariable analyses, including upper lobe location, spiculation, satellite nodules, echogenicity, presence of dots or linear arcs, and patency of vessels and bronchi predicted malignancy. A nomogram was constructed based on these predictors. The area under the curve (AUC) value of the nomogram was 0.858 using the chest CT factors, which improved to 0.952 when radial EBUS factors were added. The calibration curve showed good agreement between the actual and nomogram-predicted malignancy outcomes. The utility of radial EBUS images for revealing risk factors of malignancy was confirmed. Furthermore, our nomogram was able to predict the probability of malignancy in lung nodules with indeterminate radial EBUS-guided biopsy results.
对于径向探头支气管内超声（径向EBUS）引导下活检结果不确定的病例，下一步的诊断措施仍不明确。本研究旨在根据临床发现、胸部计算机断层扫描（CT）和径向EBUS图像确定恶性肿瘤的危险因素，并通过构建列线图来估计径向EBUS引导下活检结果不确定的肺结节的恶性风险。这项回顾性研究纳入了2017年1月至2018年12月在三星医疗中心进行的首次径向EBUS活检结果不确定但最终诊断明确的157例患者。对病历、胸部CT、径向EBUS图像和最终诊断进行了回顾。患者被随机分为训练集和验证集。通过逻辑回归分析确定与恶性肿瘤相关的因素，并使用训练集构建列线图，随后应用于验证集。单变量和多变量分析中的六个因素，包括上叶位置、毛刺征、卫星结节、回声性、点状或线性弧的存在以及血管和支气管的通畅性，可预测恶性肿瘤。基于这些预测因素构建了列线图。使用胸部CT因素时，列线图的曲线下面积（AUC）值为0.858，加入径向EBUS因素后提高到0.952。校准曲线显示实际和列线图预测的恶性肿瘤结果之间具有良好的一致性。证实了径向EBUS图像在揭示恶性肿瘤危险因素方面的实用性。此外，我们的列线图能够预测径向EBUS引导下活检结果不确定的肺结节的恶性概率。
