Department of Endoscopy, Guangxi Medical University Cancer Hospital, Nanning 530021, China.
Int J Clin Pract. 2024 Feb 29;2024:3711123. doi: 10.1155/2024/3711123. eCollection 2024.
Endobronchial ultrasound (EBUS) sonographic features help identify benign/malignant lymph nodes while conducting transbronchial needle aspiration (TBNA). This study aims to identify risk factors for malignancy based on EBUS sonographic features and to estimate the risk of malignancy in lymph nodes by constructing a nomogram.
1082 lymph nodes from 625 patients were randomly enrolled in training ( = 760) and validation ( = 322) sets. The subgroup of EBUS-TBNA postoperative negative lymph nodes ( = 317) was randomly enrolled in a training ( = 224) set and a validation ( = 93) set. Logistic regression analysis was used to identify the EBUS features of malignant lymph nodes. A nomogram was formulated using the EBUS features in the training set and later validated in the validation set.
Multivariate analysis revealed that long-axis, short-axis, echogenicity, fusion, and central hilar structure (CHS) were the independent predictors of malignant lymph nodes. Based on these risk factors, a nomogram was constructed. Both the training and validation sets of 5 EBUS features nomogram showed good discrimination, with area under the curve values of 0.880 (sensitivity = 0.829 and specificity = 0.807) and 0.905 (sensitivity = 0.819 and specificity = 0.857). Subgroup multivariate analysis revealed that long-axis, echogenicity, and CHS were the independent predictors of malignancy outcomes of EBUS-TBNA postoperative negative lymph nodes. Based on these risk factors, a nomogram was constructed. Both the training and validation sets of 3 EBUS features nomogram showed good discrimination, with the area under the curve values of 0.890 (sensitivity = 0.882 and specificity = 0.786) and 0.834 (sensitivity = 0.930 and specificity = 0.636).
Our novel scoring system based on two nomograms can be utilized to predict malignant lymph nodes.
经支气管超声(EBUS)声像特征有助于在进行经支气管针吸活检(TBNA)时识别良性/恶性淋巴结。本研究旨在根据 EBUS 声像特征确定恶性肿瘤的危险因素,并构建列线图来评估淋巴结的恶性肿瘤风险。
将 625 例患者的 1082 个淋巴结随机分为训练集(n=760)和验证集(n=322)。将 EBUS-TBNA 术后阴性淋巴结亚组(n=317)随机分为训练集(n=224)和验证集(n=93)。采用 logistic 回归分析识别恶性淋巴结的 EBUS 特征。在训练集中使用 EBUS 特征构建列线图,然后在验证集中进行验证。
多变量分析显示,长轴、短轴、回声、融合和中央门结构(CHS)是恶性淋巴结的独立预测因素。基于这些危险因素构建了一个列线图。训练集和验证集的 5 个 EBUS 特征列线图的鉴别能力均较好,曲线下面积值分别为 0.880(敏感性=0.829,特异性=0.807)和 0.905(敏感性=0.819,特异性=0.857)。亚组多变量分析显示,长轴、回声和 CHS 是 EBUS-TBNA 术后阴性淋巴结恶性肿瘤结果的独立预测因素。基于这些危险因素构建了一个列线图。训练集和验证集的 3 个 EBUS 特征列线图的鉴别能力均较好,曲线下面积值分别为 0.890(敏感性=0.882,特异性=0.786)和 0.834(敏感性=0.930,特异性=0.636)。
我们的两个列线图新型评分系统可用于预测恶性淋巴结。