肺癌肿瘤标记物联合检测的信息提示和预测分析

目的:研究肺癌检测指标组合、联检标准和预测模式。 方法:采用蛋白芯片测量技术检测肺癌组和非癌组 12项肿瘤标记物 (TM)粗选指标 ,在此基础上制定组合联检方案 ,并引入数学函数式和构建肿瘤预测图。 结果 :(1)非癌组与肺癌组 12项标记物中糖链抗原 19- 9(CA19- 9)、神经元特异性烯醇化酶 (NSE)、癌胚抗原 (CEA)、糖链抗原 2 4 2 (CA2 4 2 )、癌抗原 12 5 (CA12 5 )、铁蛋白 (Ferritin) 6项测定值差异有统计学意义 (P均 <0 .0 1)。 (2 )非癌组与肺癌组 12项标记物阳性检测实验中 6项指标检测阳性率差异有统计学意义 (P均 <0 .0 1) ,其中肺癌组CEA、CA2 4 2和 CA12 5呈现高阳性检出率 ,结合测定值选择该 3项指标作为联检核心指标。 (3)联检技术参数优于单检技术参数 ,预测阳性率与联检阳性率高度吻合。 结论 :将联合检测与公式判定组合应用 ,对肿瘤的筛选、临床辅诊、疗效判定和随访跟踪具有重要价值

The signification and prediction analysis of conbined detection of tumor markers in cancer

Objective: To explore the combined detection of tumor markers in lung cancer, standards of combined detection and predictive model. Methods: Using the protein chip technique, we detected the twelve tumor markers in lung cancer group and control group in which three core markers were picked out and were introduced from mathematical function formula as well as set up predictive map. Result: The results were as follows: (1) There were statistical significance in measuring value of CA199, NSE, CEA, CA242, Ferritin, CA125 (P<0.01). (2) The positive rate of five tumor markers had statistical significance in lung cancer group and control group (P<0.01) P.CEA, CA242 and CA125 were chose the core markers which has high positive rate and mean value in lung cancer group. (3) establishment of predictive map of lung cancer with mathematical function formula. The parameter of combined detection was superior to that of single detection. The positive rate of predictive map was consistent with that of combined detection (P>0.05). Conclusion: The combination of combined detection with mathematical judgment has an important value in screening, supplementary diagnosis, judgment of cancer treatment and follow up of the patients with lung cancer. This study will bring a new reflection in the melting of biology with its related subjects.