摘要
目的分析7项血清自身抗体P53、PGP9.5、SOX2、GAGE7、GBU4-5、MAGEA1和CAGE在肺癌患者中的临床诊断价值。方法采用ELISA法检测114例肺癌患者和194例肺部良性病变患者血清中7项自身抗体的表达水平并比较两组阳性表达率的差异,通过绘制ROC曲线比较7项自身抗体单项及联合检测在肺癌中的诊断效能,分别分析7项自身抗体与肺癌患者的临床病理特征的关系。结果肺癌组7项自身抗体表达水平及阳性率均明显高于非肺癌组,差异均具有统计学意义(P<0.05),7项自身抗体联合检测诊断肺癌患者灵敏度为57.89%,特异度为82.13%,AUCROC为0.69,其灵敏度和AUCROC均高于各自身抗体单项检测,并且GAGE7、MAGEA1和CAGE与肺癌患者的TNM分期具有相关性(χ~2=11.897,χ~2=8.720,χ~2=9.146;P=0.008,P=0.033,P=0.027)。结论 7项血清自身抗体联合检测可有效提高肺癌辅助诊断水平。
Objective The clinical diagnostic value of seven serum autoantibodies(P53,PGP9.5,SOX2,GAGE7,GBU4-5,MAGEA1 and CAGE)in patients with lung cancer was analyzed.Methods The serum levels of seven autoantibodies in 114 patients with lung cancer and 194 patients with benign pulmonary disease were measured by ELISA.The differences between the two groups were compared.The ROC curve was used to analysis the diagnostic efficacy of seven autoantibodies against lung cancer,and the analysis of seven autoantibodies in lung cancer patients with clinicopathological features was made respectively.Results The autoantibodies expression and positive rate of 7 autoantibodies in lung cancer group were significantly higher than those in non-lung cancer group(P<0.05).The sensitivity and specificity of 7 autoantibodies in detecting lung cancer were 57.89%and 82.13%,The AUC ROC was 0.691,the sensitivity and AUC ROC were higher than the individual antibodies,and GAGE7,MAGEA1 and CAGE were correlated with the TNM stage of lung cancer(χ2=11.897,χ2=8.720,χ2=9.146;P=0.008,P=0.033,P=0.027).Conclusion Seven serum autoantibodies combined detection can effectively improve the diagnostic level of lung cancer.
作者
刘苗苗
南岩东
陈艳丽
谢永宏
金发光
Liu Miaomiao;Nan Yandong;Chen Yanli;Xie Yonghong;Jin Faguang(Department of pulmonary and critical care medicine,Tangdu Hospital,the Air Force Medical University,Xi′an 710038,China)
出处
《中华肺部疾病杂志（电子版）》
CAS
2018年第1期35-38,共4页
Chinese Journal of Lung Diseases(Electronic Edition)
基金
国家自然科学基金资助项目(81570067)
第四军医大学唐都医院骨干人才资助基金(No.2017-01)
关键词
支气管肺癌
自身抗体
联合检测
Lung bronchogenic carcinoma
Autoantibodies
Combined detection
