摘要
目的通过检测与乳腺癌预后相关的临床病理及分子生物学指标,对照随访结果,筛选影响乳腺癌患者预后的因素。方法应用免疫组化SP法检测乳腺癌组织中S100A4、nm23-H1、C-erbB-2、p53、ER及PR的表达,对比临床病理指标及随访结果,应用多因素Logistic回归的统计学方法分析。结果在11项可能影响乳腺癌患者预后的相关因素中,单因素分析显示,肿瘤大小、淋巴结转移状况、组织学分级、S100A4、C-erbB-2、p53、ER状态与预后相关(P<0.05);而临床分期、病理类型、PR状态及nm23-H1与预后不相关(P>0.05);多因素Logistic回归分析发现,腋淋巴结转移状况和组织学分级是影响乳腺癌患者预后最有价值的指标(P<0.05)。结论肿瘤大小、S100A4、p53、C-erbB-2、ER状态对乳腺癌患者预后有明显的提示作用,但不是独立的预后指标;淋巴结转移状况和组织学分级是判断预后最有价值的因素。
Objective To study the influent factors of prognosis of breast cancer.Methods S100A4,nm23H1,C-erbB-2,p53,ER and PR were detected with corresponding reagents by immunohisto-chemistry S-P method,and clinicopathological and follow-up data were investigated.The patients'prognostic significance was analyzed by χ2 test and multivariable logistic regression.Results In all 11 influence factors,tumor size,lymph node metastasis,histopathologic grading,S100A4,p53,C-erbB-2 expression and ER state had correlation with prognosis (P〈0.05),but TNM stage,pathological type,PR state and nm23-H1 protein expression were not correlated with the prognosis by univariate analysis (P〉 0.05).In multivariate analysis,the most important factors affecting prognostic significance were histopathologic grading and lymph node metastasis state(P〈0.05).Conclusion Our findings demonstrate that tumor size,S100A4,p53,C-erbB-2 protein expression and ER state were correlated with prognosis of breast cancer but not with the dependent factors,histopathologic grading and lymph node metastasis can be used to predict the prognosis of breast cancer as the independent parameters in clinical practice.
出处
《医学研究与教育》
CAS
2010年第1期24-26,29,共4页
Medical Research and Education
关键词
乳腺癌
预后
因素分析
统计学
breast cancer prognosis factor analysis statistical