摘要
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。
To evaluate the diagnosis and treatment ef fect of 17 lung tumor markers in serumMethods:Three groups o fs ubjects: 40 lung cancer,40 benign lung diseases, 40 health controls, were studie dThe levels of the 17 lung tumor markers in serum were determined To select less significant lung tumor marker,17 lung tumor markers in serum were studied by mu ltivariate analysis, then the discriminating analysis models were established fo r the diagnosis and treatment prognosisResults:At first, 8 lu ng tumor markers in serum: NSE、CYFRA21.1 ， SIL-2R、CEA、SF、CA125、SA、SOD w ere selected to make discriminating analysis models The accuracy rate of this mod el was 7583% ， further analysis, 4 tumor marker: SIL-2R，SF，CA125，SA199 were selected again for considering as less significantThe discriminating ana lysis models which were made by NSE, CEA, CYFRA21.1, SOD reached 983% in dia gnosis accuracy rateConclusion:The discriminating analysis mo de: y=0.1259 ( NSE ) +0.3737(CYFRA21.1)+0.18492(CEA)+0.12993(SOD) for lung cancer patients had significant value in clinical practice for early diagnosis a nd prognosis However, further studies with big examples are required to confir med its value
