ROC曲线评价NSE、CEA、CYFRA21-1辅助肺癌诊断效能

    Diagnostic Value Analysis of Serum NSE, CEA, CYFRA21-1 for Lung Cancer Based on ROC Curve and Logistic Regression

    • 摘要: 目的 评估本实验室NSE、CEA、CYFRA21-1阳性判断值,分析其辅助肺癌诊断的效能。 方法 研究对象为广东省人民医院2013-2014年度门诊及住院患者,化学/电发光法检测血清中的NSE、CEA、CYFRA21-1浓度,以病理或穿刺活检诊断为诊断标准,SPSS16.0、MedCale软件进行Logistic回归、ROC曲线分析,以尤登指数最大为阳性判断值,通过比较AUC分析单/多指标联合辅助肺癌诊断的效能。
      结果 最佳阳性判断值NSE为>18.48 ng/mL敏感度55.7%(53.0%~58.4%),特异度63.1%(56.6%~69.2%、CEA为>3.36 ng/mL敏感度60.0%(57.6%~62.3%),特异度79.6%(75.7%~83.1%)、CYFRA21-1为>4.4 ng/mL敏感度47.4%(45.0%~49.8%),特异度83.7%(79.3%~87.4%)。CEA+CYFRA21-1+NSE联合辅助肺癌诊断,AUC比各单项应用均有增加(P值均<0.01),但与CEA+CYFRA21-1联合应用AUC差异无显著性(P>0.05)。两项指标联合应用组间比较,CEA+CYFRA21-1为最佳组合。NSE辅助小细胞肺癌(AUC=0.938),CEA辅助腺癌(AUC=0.793),CYFRA21-1辅助鳞癌诊断(AUC=0.843)的效能最佳。 结论 本地人群血清NSE、CEA、CYFRA21-1辅助肺癌诊断的最佳阳性判断值与生产商提供的值略有差异,多指标联合的辅助诊断效能高于单指标,NSE、CYFRA21-1、CEA对不同病理类型肺癌的辅助诊断各有针对性,推荐三项联合检测辅助肺癌诊断。

       

      Abstract: Objective To investigate the diagnostic values of tumor markers (NSE、CEA、CYFRA21-1)for lung cancer with receiver operating characteristic (ROC)curve and logistic regression (LR)analysis. Methods The serum concentrations of NSE、 CEA and CYFRA21-1 were measured by chemiluminescent or electrochemica immunoassay. The area under the ROC curve(AUC), sensitivity, specificity and Youden’s index were calculated and compared by SPSS 16.0 and MedCale software. Results In patients with lung cancer, the ideal threshold point identified from the ROC curve for NSE was >18.48 ng/mL, with a sensitivity of 55.7% (95%CI 53.0%~58.4%) and a specificity of 63.1%(95%CI 56.6%~69.2%). The ideal threshold point for CEA is >3.36 ng/mL, with a sensitivity of 60.0% (95%CI 57.6%~62.3%) and a Specificity of 79.6%(95%CI 75.7%~83.1%). The ideal threshold point based on ROC curve for CYFRA21-1 was >4.4 ng/mL, with a Sensitivity of 47.4%(95%CI 45.0%~49.8%) and a Specificity of 83.7%(95%CI 79.3%~87.4%). Combined two or three indexes can increase AUC significantly. NSE has the best AUC(0.938) in small cell lung cancer, CEA has the best AUC (0.793) in adenocarcinoma, CYFRA21-1 has the best AUC(0.843) in squamous carcinoma. Conclusions Combined analysis three indexes indicated an increase in AUC for lung cancer diagnostis.

       

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