论文部分内容阅读
目的：研究17种肺癌标志物在肺癌临床诊治中的应用价值。方法：对肺癌患者、肺部良性疾病患者及健康对照人群各40例，测定血清中17种肺癌标志物的水平并用多元逐步回归方法进行筛选，在综合分析17种肺癌标志物间的相互作用后，淘汰价值较小的标志物，最后用判别分析的方法建立相应的判别函数式。结果：第一次共筛选出NSE、CYFRA21-1，SIL-2R、CEA、SF、CA125、SA、SOD等8个指标，用判别函数进行判断其诊断准确性为75.83%，进一步筛选，又剔出SIL-2R，SF，CA125，SA等4个影响较小的因素后其诊断准确性达到98.3%。结论：用y=0.1259（NSE）+0.3737(CYFRA21-1)+018492(CEA)+0.12993(SOD)判别函数作为肺癌的辅助诊断方法及治疗后的疗效观察指标有较高的临床应用价值。
Objective: To study the application value of 17 lung cancer markers in the diagnosis and treatment of lung cancer. Methods: Forty lung cancer patients, benign lung disease patients, and healthy control subjects were studied in 40 patients. The levels of 17 lung cancer markers in serum were determined and screened by multiple stepwise regression methods. After comprehensive analysis of the interactions among 17 lung cancer markers , Eliminating the less valuable markers, and finally using the method of discriminant analysis to establish the corresponding discriminant function formula. Results: For the first time, 8 indexes such as NSE, CYFRA21-1, SIL-2R, CEA, SF, CA125, SA and SOD were screened out. The diagnostic accuracy was 75.83% with the discriminant function, and further screening was performed. The diagnostic accuracy of SIL-2R, SF, CA125, SA and other four factors with less influence reached 98.3%. Conclusion: Using y=0.1259(NSE)+0.3737(CYFRA21-1)+018492(CEA)+0.12993(SOD) discriminant function as the auxiliary diagnosis method for lung cancer and the therapeutic effect observation index have higher clinical application value.