首页> 中文期刊> 《福建医科大学学报》 >肝癌根治术后早期肺转移临床因素及CXCR7蛋白数学预测模型的研究

肝癌根治术后早期肺转移临床因素及CXCR7蛋白数学预测模型的研究

         

摘要

目的 探讨建立肝癌根治术后早期肺转移临床因素及CXCR7蛋白数学预测模型.方法 收集根治性切除279例患者的肝癌组织、癌旁组织标本及14例正常肝组织构建组织芯片,利用免疫组织化学方法 检测CXCR7蛋白在肝癌组织、癌旁组织及正常肝脏组织中的表达情况;回顾性分析279例患者的临床资料,以10项相关的临床病理因素及肝癌细胞中CXCR7蛋白表达情况进行单因素分析,筛选相关影响因素,并进行多因素分析及建立术后肺转移的预测模型.结果 术后1年肺转移发生率为12.9%(36/279).单因素分析提示肺转移组和无肺转移组在CXCR7蛋白表达、性别、肿瘤大小、术前AFP、镜下脉管癌栓方面相比较有显著性差异.多因素分析提示术后发生肺转移的独立判断因素为CXCR7蛋白阳性表达、肿瘤大小.结论 随着肿瘤直径增大、CXCR7蛋白阳性表达,患者术后早期肺转移可能性较大.本预测数学模型P=Y/(1+Y),Y=EXP(-6.676+肿瘤大小的B值+CXCR7蛋白表达的B值)具有较高的预测准确率.%Objective To investigate the establishment of the mathematical prediction model linked to clinically relevant factors and CXCR7 after curative hepatic resection. Methods Tissue microarrays was constructed, among these patients, the expression of protein were evaluated by immunohis-tochemical method in 279 HCC. The hepatocelluar carcinoma patients who received radical operation were investigated retrospectively. A single factor analysis was performed to find the risk factors pulmonary metastasis after curative hepatic resection. And a multivariate logistic regression analysis was performed according to the relevant clinical and pathology factors and CXCR7 to establish the prediction equation of early pulmonary metastasis Results The ratio of pulmonary metastasis of hepatocelluar carcinoma after curative hepatic resection in 1 year was 12. 9% (36/279). According to single factor analysis, the indicators , including the tumor diameters, the level of AFP, microvascular invasion by the microscope examination, the expression of CXCR7 were different significantly in two groups. The multivariate logistic regression analysis indicated that the independent prognostic factors of pulmonary metastasis of hepatocelluar carcinoma after curative hepatic resection was the expression of CXCR7 and the tumor diameters. Conclusions The patients whose tumor expressed CXCR7 protein, and tumor diameter was more than others was prone to pulmonary metastasis after curative hepatic resection. Clinical vertification indicates that the prediction equation is credible.

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