Ye Maosong, Zheng Xiaoxuan, Ye Xin, Zhang Juncheng, Huang Chuoji, Liu Zilong, Huang Meng, Fan Xianjun, Chen Yanci, Xiao Botao, Sun Jiayuan, Bai Chunxue
Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Department of Respiratory Endoscopy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Front Oncol. 2021 Mar 11;11:638223. doi: 10.3389/fonc.2021.638223. eCollection 2021.
Lung cancer screening using low-dose computed tomography (LDCT) often leads to unnecessary biopsy because of the low specificity among patients with pulmonary nodules ≤10 mm. Circulating genetically abnormal cells (CACs) can be used to discriminate lung cancer from benign lung disease. To examine the diagnostic value of CACs in detecting lung cancer for patients with malignant pulmonary nodules ≤10 mm.
In this prospective study, patients with pulmonary nodules ≤10 mm who were detected at four hospitals in China from January 2019 to January 2020 were included. CACs were detected using fluorescence hybridization. All patients were confirmed as lung cancer or benign disease by further histopathological examination. Multivariable logistic regression models were established to detect the presence of lung cancer using CACs and other associated characteristics. Receiver operating characteristic analysis was used to evaluate the performance of CACs for lung cancer diagnosis.
Overall, 125 patients were included and analyzed. When the cutoff value of CACs was >2, the sensitivity and specificity for lung cancer were 70.5 and 86.4%. Male (OR = 0.330, P = 0.005), maximum solid nodule (OR = 2.362, P = 0.089), maximum nodule located in upper lobe (OR = 3.867, P = 0.001), and CACs >2 (OR = 18.525, P < 0.001) met the P < 0.10 criterion for inclusion in the multivariable models. The multivariable logistic regression model that included the dichotomized CACs (>2 ≤2) and other clinical factors (AUC = 0.907, 95% CI = 0.842-0.951) was superior to the models that only considered dichotomized CACs or other clinical factors and similar to the model with numerical CACs and other clinical factors (AUC = 0.913, 95% CI = 0.850-0.956).
CACs presented a significant diagnostic value in detecting lung cancer for patients with pulmonary nodules ≤10 mm.
使用低剂量计算机断层扫描（LDCT）进行肺癌筛查时，由于≤10mm肺结节患者的特异性较低，常常导致不必要的活检。循环基因异常细胞（CACs）可用于区分肺癌与良性肺病。旨在研究CACs在检测≤10mm恶性肺结节患者肺癌中的诊断价值。
在这项前瞻性研究中，纳入了2019年1月至2020年1月在中国四家医院检测出的≤10mm肺结节患者。使用荧光杂交检测CACs。所有患者均通过进一步的组织病理学检查确诊为肺癌或良性疾病。建立多变量逻辑回归模型，以利用CACs和其他相关特征检测肺癌的存在。采用受试者工作特征分析来评估CACs对肺癌诊断的性能。
总共纳入并分析了125例患者。当CACs的截断值>2时，肺癌的敏感性和特异性分别为70.5%和86.4%。男性（OR = 0.330，P = 0.005）、最大实性结节（OR = 2.362，P = 0.089）、最大结节位于上叶（OR = 3.867，P = 0.001）以及CACs>2（OR = 18.525，P < 0.001）符合纳入多变量模型的P < 0.10标准。包含二分法CACs（>2与≤2）和其他临床因素的多变量逻辑回归模型（AUC = 0.907，95%CI = 0.842 - 0.951）优于仅考虑二分法CACs或其他临床因素的模型，且与包含数值型CACs和其他临床因素的模型相似（AUC = 0.913，95%CI = 0.850 - 0.956）。
对于≤10mm肺结节患者，CACs在检测肺癌方面具有显著的诊断价值。
