Li Xianfeng, Zhang Qinghua, Jin Xiayun, Cao Lihua
Department of Graduate School, the Second Hospital Affiliated to Dalian Medical University, Dalian, 116027, Liaoning, China.
Department of Clinical Medicine, the Second Hospital Affiliated to Dalian Medical University, Dalian, 116027, Liaoning, China.
World J Surg Oncol. 2017 May 25;15(1):107. doi: 10.1186/s12957-017-1171-y.
BACKGROUND: Our study was designed to improve the accuracy of determining whether pulmonary nodules are benign or malignant.
We evaluated the clinical and imaging features and serum markers: neuron specific enolase (NSE), carcino-embryonic antigen (CEA), cytokeratin fragment antigen 21-1 (CYFRA 21-1), miRNA-21-5p, and miR-574-5pof in 39 patients with pathology information. Factors that differed significantly between those with benign versus malignant pulmonary nodules were used to establish a prediction model for identifying malignant nodules.
The studied nodules were 51.3% malignant and 48.7% benign. Age, smoking status, nodule diameter, history of emphysema, vascular sign, burr sign, CYFRA21-1, CEA, miRNA-21-5p, and miRNA-574-5p differed significantly between the benign and malignant nodule groups. Serum levels of CYRFA21-1 and CEA could be used to distinguish between malignant and benign nodules with a positive predictive value (PPV) of 80.0%, a negative predictive value (NPV) of 84.2%, and an area under the receiver operating characteristics curve (AUC) of 0.863. Using the serum levels of miRNA-21-5p and miRNA-574-5p, the PPV was 55%, the NPV was 84.2%, and the AUC was 0.797. When all four serum markers were combined, the PPV was 80%, the NPV was 89.5%, and the AUC was 0.921. We established a prediction model for malignant nodules, including clinical features, imaging features, and serum markers. In cross-validation, the ratio of discriminant conformance was 95%.
Serum levels of miRNA-21-5p and miRNA-574-5p are significantly higher in patients with malignant nodules than in patients with benign nodules and are potential serum biomarkers. Our prediction model could improve malignant nodule diagnosis.
背景:我们的研究旨在提高判断肺结节是良性还是恶性的准确性。
我们评估了39例有病理信息患者的临床和影像特征以及血清标志物:神经元特异性烯醇化酶(NSE)、癌胚抗原(CEA)、细胞角蛋白片段抗原21-1(CYFRA 21-1)、miRNA-21-5p和miR-574-5p。良性与恶性肺结节患者之间存在显著差异的因素用于建立识别恶性结节的预测模型。
所研究的结节中,恶性占51.3%,良性占48.7%。年龄、吸烟状况、结节直径、肺气肿病史、血管征、毛刺征、CYFRA21-1、CEA、miRNA-21-5p和miRNA-574-5p在良性和恶性结节组之间存在显著差异。CYRFA21-1和CEA的血清水平可用于区分恶性和良性结节,阳性预测值(PPV)为80.0%,阴性预测值(NPV)为84.2%,受试者工作特征曲线下面积(AUC)为0.863。使用miRNA-21-5p和miRNA-574-5p的血清水平,PPV为55%,NPV为84.2%,AUC为0.797。当将所有四种血清标志物联合使用时,PPV为80%,NPV为89.5%,AUC为0.921。我们建立了一个恶性结节预测模型,包括临床特征、影像特征和血清标志物。在交叉验证中,判别一致性比例为95%。
恶性结节患者的miRNA-21-5p和miRNA-574-5p血清水平显著高于良性结节患者,是潜在的血清生物标志物。我们的预测模型可改善恶性结节的诊断。