| 应用ROC曲线分析人附睾分泌蛋白4和糖类抗原153在广西早期乳腺癌诊断中的价值 |
| 投稿时间：2017-12-21 修订日期：2017-12-24 点此下载全文 |
| 引用本文：王英,李佩章,黄玲莎,黄蕾,江宗蔚,黄文成.应用ROC曲线分析人附睾分泌蛋白4和糖类抗原153在广西早期乳腺癌诊断中的价值[J].医学研究杂志,2017,46(12):57-59 |
| DOI：
10.11969/j.issn.1673-548X.2017.12.015 |
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| 基金项目:广西卫生和计划生育委员会基金资助项目（Z2015590） |
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| 中文摘要:目的 应用ROC曲线（receiver operating characteristic curve）分析血清人附睾分泌蛋白4（human epididymis protein 4，HE4）和糖类抗原153（carbohydrate antigen 153，CA153）在广西早期乳腺癌诊断中的价值。方法 用酶联免疫吸附测定（enzyme-linked immunosorbent assay，ELISA）法检测100例Ⅰ~Ⅱ期乳腺癌患者及50例健康对照者血清中HE4和CA153水平，应用ROC曲线（receiver operating characteristic curve）分析HE4和CA153对乳腺癌的诊断价值。结果 早期乳腺癌组HE4和CA153水平高于健康对照组，差异有统计学意义（P=0.000），当HE4和CA153的截断值分别为 ≥ 99.35pg/L和 ≥ 28.35U/L时，HE4的AUC为0.897，P=0.000，95% CI：0.848~0.947；CA153的AUC为0.859，P=0.000，95% CI：0.801~0.916，为乳腺癌最佳临床诊断临界点。结论 HE4和CA153水平变化可作为诊断早期乳腺癌重要参考依据。 |
| 中文关键词:乳腺癌 HE4 CA153 ROC曲线 |
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| Value of HE4 and CA153 in DiagnosiS of Early Stage Breast Cancer by ROC Curve Analysis |
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| Abstract:Objective To explore the diagnostic significance of serum human epididymis protein 4 (HE4)and carbohydrate antigen 153 (CA153)in early stage breast cancer by receiver operating characteristic curve (ROC curve).Methods Serum HE4 and CA153 levels were detected with enzyme-linked immunosorbent (ELISA) in 100 cases Ⅰ-Ⅱ patients with breast cancer surgery and 40 cases with normal healthy controls. We explored the diagnostic significance of serum HE4 and CA153 in breast cancer by ROC curve.Results HE4 and CA153 levels in early stage breast cancer patients were higher than that of the healthy normal group, and the difference was statistically significant (P=0.000). It is the best clinical tipping point for the diagnosis of breast cancer when the cutoff value of HE4 and CA153 were ≥ 99.35pg/L and ≥ 28.35U/L, the AUC of HE4 was 0.897, P=0.000, 95%CI:0.848-0.947; the AUC of CA153 was 0.859, P=0.000, 95% CI:0.801-0.916.Conclusion The change of HE4 and CA153 levels can be used as important reference for diagnosis of early breast cancer. |
| keywords:Breast cancer HE4 CA153 Receiver operating characteristic curve |
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