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血清间皮素和血管内皮生长因子C对卵巢癌的诊断价值

Diagnostic Value of Serum Mesothelin and VEGF-C for Ovarian Cancer
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摘要 目的:探讨血清间皮素和血管内皮生长因子C(VEGF-C)对卵巢癌的诊断价值。方法比较卵巢癌组(108例)、卵巢良性疾病组(126例)和正常对照组(200例)血清间皮素和VEGF-C水平,以受试者工作特征(ROC)曲线和Logistic回归-ROC曲线分别评估单一和联合指标对卵巢癌的诊断价值。结果血清间皮素和VEGF-C水平在卵巢癌组均显著高于卵巢良性疾病组和健康对照组(<0.05)。血清间皮素和VEGF-C的ROC曲线下面积(AUC)分别为0.88[95%参考区间(CI),0.80~0.93]和0.85(95%CI,0.81~0.92)。联合检测血清间皮素和VEGF-C的AUC为0.91(95%CI,0.88~0.95),灵敏度和特异性分别为86.1%和89.4%。结论联合检测血清间皮素和VEGF-C有助于卵巢癌的鉴别诊断。 Objective To investigate the diagnostic significance of serum mesothelin and vascular endothelial growth factor-C(VEGF-C)for ovarian cancer.Methods Serum levels of mesothelin and VEGF-C were compared among the patients with ovarian cancer(n=108),patients with ovarian benign diseases(n=126)and the healthy controls(n=200).The methods of the receiver operating characteristic(ROC)curve and logistic regression analysis-ROC curve were used to evaluate the diagnostic values of serum mesothelin and VEGF-C individually and in combination.Results Serum levels of mesothelin and VEGF-C in the ovarian cancer group were significantly higher than those in the ovarian benign diseases group and the healthy controls(<0.05).The area under the ROC(AUC)of serum mesothelin and VEGF-C was 0.88[95%confidence intervals(CI),0.80~0.93],and 0.85(95%CI,0.81~0.92),respectively.The AUC of combined serum biomarkers of mesothelin and VEGF-C was 0.91(95%CI,0.88~0.95)with 86.1%of sensitivity and 89.4%of specificity.Conclusion The combined measurement of serum mesothelin and VEGF-C is helpful for the diagnosis of ovarian cancer.
作者 王琴 田刚 WANG Qin;TIAN Gang(Department of Obsterics and Gynecology,The Affiliated Hospital of Southwest Medical University,Luzhou 646000,Sichuan,China;Department of Clinical Laboratory of Medicine,The Affiliated Hospital of Southwest Medical University,Luzhou 646000,Sichuan,China)
出处 《医学信息(医学与计算机应用)》 2016年第29期120-121,共2页 Medical Information
基金 西南医科大学自然科学基金(30543) 西南医科大学附属医院人才基金(12277)。
关键词 卵巢癌 间皮素 血管内皮生长因子C Ovarian cancer Mesothelin Vascular endothelial growth factor-C
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