Şafak Alıcı Nur, Alıcı İbrahim Onur
Department of Chest Diseases, Occupational and Occupational Diseases Polyclinic, Dr. Suat Seren Chest Diseases and Surgery Training and Research Hospital, Izmir, Türkiye.
Department of Chest Diseases, Dr. Suat Seren Chest Diseases and Surgery Training and Research Hospital, Izmir, Türkiye.
Turk Gogus Kalp Damar Cerrahisi Derg. 2023 Jan 30;31(1):63-68. doi: 10.5606/tgkdc.dergisi.2023.22276. eCollection 2023 Jan.
In this study, we aimed to compare the diagnostic performances of three existing prediction tools in visually identifying a malignant lymph node.
Between April 2016 and January 2021, a total of 827 lymph nodes of 259 patients (211 males, 48 females; mean age: 61.1±7.2 years; range, 41 to 79 years) who underwent endobronchial ultrasound procedure for diagnosis and/or staging of lung cancer and diagnosis of mediastinal lymphadenopathy of unknown origin were retrospectively analyzed. This external validation study was designed to compare the diagnostic yields of the prediction tools developed by Shafiek et al., Alici et al., and Canada Lymph Node Score (CLNS). Endobronchial ultrasoundguided transbronchial needle aspiration results and predictions were compared to gold-standard tool.
Overall, endobronchial ultrasound-guided transbronchial needle aspiration had a sensitivity, specificity, positive and negative predictive value, and accuracy of 95.6%, 100%, 100%, 97.6%, and 98.4%, respectively. Diagnostic performances of proposed tools were quite remarkable. Among them, Alici algorithm had a higher sensitivity and negative predictive value, which were matched by excellent specificity and positive predictive value offered by CLNS ≥3 and Shafiek tool. The area under the curve value of CLNS ≥3 was higher than Shafiek tool and CLNS ≥2.
Conventional prediction tools relying on simple real-time sonographic features were found to be consistent by the means of diagnostic performance in this external validation dataset. Despite being inferior to cytology, their superior performance was proven with defined individual strengths and weaknesses.
在本研究中，我们旨在比较三种现有预测工具在视觉识别恶性淋巴结方面的诊断性能。
回顾性分析了2016年4月至2021年1月期间259例患者（211例男性，48例女性；平均年龄：61.1±7.2岁；范围41至79岁）的827个淋巴结，这些患者接受了支气管内超声检查以进行肺癌诊断和/或分期以及不明原因纵隔淋巴结肿大的诊断。这项外部验证研究旨在比较由沙菲克等人、阿利奇等人开发的预测工具以及加拿大淋巴结评分（CLNS）的诊断率。将支气管内超声引导下经支气管针吸活检结果和预测与金标准工具进行比较。
总体而言，支气管内超声引导下经支气管针吸活检的敏感性、特异性、阳性和阴性预测值以及准确性分别为95.6%、100%、100%、97.6%和98.4%。所提出工具的诊断性能相当显著。其中，阿利奇算法具有较高的敏感性和阴性预测值，而CLNS≥3和沙菲克工具提供的优异特异性和阳性预测值与之相匹配。CLNS≥3的曲线下面积值高于沙菲克工具和CLNS≥2。
在这个外部验证数据集中，通过诊断性能发现，依赖简单实时超声特征的传统预测工具是一致的。尽管不如细胞学检查，但它们的卓越性能通过明确的个体优势和劣势得到了证明。
