孤立性肺结节病变性质临床鉴别诊断预测模型的初探

Clinical analysis of 44 patients with solitary pulmonary nodule

目的探讨孤立性肺结节的良恶性鉴别诊断的有效方法。方法回顾性分析44例孤立性肺结节患者的临床特点,血清学指标及其鉴别诊断效果,并建立临床预测模型。结果 44例肺内孤立性结节患者中,恶性肿瘤占19例,良性肿瘤占25例。单因素分析结果患者的年龄、结节大小、结节边界、肿瘤病史、CEA、CA125及miR-21、miR-27b和miR-193b在良恶性孤立性肺结节患者间具有显著差异,多因素判别分析并建立Fisher线性判别函数,交互验证一致函数与原始个案的符合率为93%。结论除患者的一般情况、影像学表现和常规血清标记物外,microRNAs也是鉴别孤立性肺结节良恶性的良好指标,具有重要临床意义。

Objective To explore an effective method of benign and malignant solitary pulmonary nodule differential diagnosis. Methods Clinical features, serum markers and effects of differential diagnosis of 44 patients with solitary pulmonary nodule were analyzed retrospectively, and a clinical prediction model was established. Results Among 44 patients with solitary pulmonary nodule, malignant tumors accounted for 19 cases, and benign tumors accounted for 25 cases. Univariate analysis shows that patient＇s age, nodule size, nodule boundary, history of cancer, CEA, CA125, miR-21, miR-27b and miR-193b between benign and malignant solitary pulmonary have significant differences. After analyzing each variable by the method of diseriminant analysis, we established a Fisher linear discriminant function equations, and the rate of this function equations consistent with the original case classification was 93%. Conclusion In addition to the general situation of the patients, imaging findings and conventional serum markers, microRNAs are also a good indicator to identify solitary pulmonary nodule in benign and malignant, have important clinical significance.