基于Bayes法的C-12蛋白芯片联合检测判别函数的建立及临床意义分析

Establishment of multiple tumor marker discriminant function,its clinical significance for tumor diagnosis,and the differences with C-12 protein chip based on Bayes method

目的结合C-12蛋白芯片检测结果,采用Bayes法建立多肿瘤标志物判别函数,以明确肿瘤类型,提高肿瘤诊断准确率;比较多肿瘤标志物判别函数与C-12多肿瘤标志物蛋白芯片检测系统的差异及对肿瘤诊断的临床意义。方法用C-12蛋白芯片法检测2 177例恶性肿瘤患者(肺癌836例,肝癌318例,胰腺癌84例,胃癌123例,肠癌338例,乳腺癌206例,卵巢癌47例,子宫内膜癌28例,食管癌197例)和2 111例正常及患良性疾病的非肿瘤患者的12项常见肿瘤标志物,并结合临床资料进行回顾性研究。应用Bayes法建立肿瘤判别诊断函数,比较12种肿瘤标志物和判别诊断函数对肿瘤诊断的准确率差异。结果成功建立了多肿瘤标志物的三级诊断判别函数。一级判别函数诊断的特异度为82.11%,灵敏度为71.28%,准确率为83.97%,而C-12蛋白芯片法检测12项肿瘤标志物的特异度为70.11%,灵敏度为66.10%,准确率为68.07%。二级判别函数能显著提高10种常规肿瘤诊断的灵敏度、特异度和准确率。三级诊断判别函数对确定部分肿瘤的类型有意义。结论基于Bayes法建立的C-12蛋白芯片联合检测判别函数具有较高的灵敏度、特异度和准确率,对肿瘤的诊断具有重要临床价值。

Objective To establish the diagnostic function by Bayesian method to identify the type of tumor and evaluate the accuracy rate. The difference between the diagnostic function and the C-12 multiple tumor marker protein chip system was compared to evaluate their clinical significance for tumor diagnosis. Methods A retrospective study was done on the data of 2177 patients with malignant tumors （836 with lung cancer, 318 with liver cancer, 84 with pancreatic cancer, 123 with gastric cancer, 338 with colorectal cancer, 206 with breast cancer, 47 with ovarian cancer, 28 with endometrial cancer, and 197 with esophageal cancer） and 2111 normal and benign lesions （control group）, in whom 12 tumor markers were detected by protein chip technology. Furthermore, the diagnostic function was established by Bayesian method to compare the accuracy for tumor diagnosis with these 12 tumor markers. Results 1） The tertiary diagnostic function was successfully established in C-12 multiple tumor markers. 2） The specificity, sensitivity and accuracy were 70. 11%, 66. 10% and 68. 07%, respectively, by C-12 multiple tumor markers, while 82. 11%, 71.28% and 83. 97% by the first grade of diagnostic function. 3） The accuracy, sensitivity and specificity were higher than that of C-12 multiple tumor marker chip in all the 10 types of malignant tumors by the second grade of diagnostic function. 4） The third grade of diagnostic function could identify a part of the tumor types, such as breast cancer, prostate cancer, lung cancer, liver cancer, ovarian cancer, endometrial cancer and pancreatic cancer. Conclusion Diagnostic functions established by Bayesian methods have such advantages as high sensitivity, specificity and accuracy, and are of great clinical value in early diagnosis of cancers.