摘要
目的探讨基于血清CA72-4、CA242、CA19-9和CEA的模式识别技术对胃癌的诊断价值。方法对212例胃癌患者,116例胃良性疾病患者和117例健康体检者血清4项肿瘤标志物测定结果进行回顾性分析,比较单项指标的诊断效能并建立主成分分析(PCA)、决策树、PCA-决策树和Fisher判别分析模型。结果 4项指标中CA242对胃癌的诊断效能最佳,ROC曲线下面积(AUC)为0.841(95%CI:0.804~0.877)。PCA模型表明,胃癌组患者血清4项肿瘤标志物代谢明显紊乱,与胃良性疾病患者和健康对照个体差异显著。决策树、PCA-决策树和Fisher判别分析模型对胃癌患者的诊断准确率分别为58.6%、65.5%和58.6%,预测准确率分别为65.7%、77.6%和73.1%;对非胃癌患者(胃良性疾病患者+健康对照)的诊断准确率分别为94.7%、99.4%和97.6%,预测准确率分别为87.5%、96.9%和96.9%。结论血清CA72-4、CA242、CA19-9和CEA的PCA-决策树模型有助于胃癌的鉴别诊断和预测分析。
Objective To evaluate the diagnostic value of serum tumors CA72-4,CA242,CA19-9and carcino-embryonic antigen（CEA）in patients with gastric cancer based on pattern recognition techniques.Methods Data of serum concentrations of CA72-4,CA242,CA19-9and CEA of 212 patients with gastric cancer,116 patients with benign gastric disease and 117 healthy subjects were retrospectively analyzed;and the diagnostic performance of each tumor marker,four tumor markers based principle component analysis（PCA）,decision tree,PCA-decision tree and the fisher discriminant analysis models were established.ResultsCA242 had the best diagnostic effect on gastric cancer,and the area under the ROC curve（AUC）was 0.841（95%CI：0.804-0.877）.PCA model showed that the serum levels of four tumor markers in patients with gastric cancer were significantly different from those in benign and healthy patients,and obvious metabolic disorders of serum with four tumor markers were found among the patients with gastric cancer.The diagnosis accuracy of the decision tree,PCA-decision tree and the Fisher discriminant analysis models for gastric cancer patients was 58.6%,65.5% and 58.6% respectively,and for non-gastric cancer patients（benign gastric diseases and healthy controls）was 94.7%,99.4% and 97.6%.And the prediction accuracy of the decision tree,PCA-decision tree and the fisher discriminant analysis models for gastric cancer patients was 65.7%,77.6% and 73.1%,and for non-gastric cancer patients was 87.5%,96.9% and 96.9%,respectively.Conclusion The PCA-decision tree model of serum CA72-4,CA242,CA19-9and CEA might be helpful for the diagnosis and prediction of patients with gastric cancer.
出处
《重庆医学》
CAS
北大核心
2017年第15期2060-2062,共3页
Chongqing medicine
基金
四川省卫生厅课题资助项目(120336)
西南医科大学人才基金(2014ZD-017)
关键词
胃癌
诊断
主成分分析
决策树
FISHER判别分析
stomach neoplasms
diagnosis
principle component analysis
decision tree analysis
Fisher discriminant analysis
作者简介
桂林（1986-），技师，硕士，主要从事输血相关疾病方面研究。
通信作者，E-mail：26074937@qq．com。
