Factors influencing p53 expression in ovarian cancer as a biomarker of clinical outcome in multicentre studies.
Factors influencing p53 expression in ovarian cancer as a biomarker of clinical outcome in multicentre studies.
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在多中心研究中，影响卵巢癌p53表达的因素是临床结果的生物标志物。
DOI：
10.1038/sj.bjc.6603300
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发表时间：
2006-09-04
影响因子：
8.8
通讯作者：
van der Zee, A G J
中科院分区：
文献类型：
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作者：
de Graeff, P;Hall, J;Crijns, A P G;de Bock, G H;Paul, J;Oien, K A;ten Hoor, K A;de Jong, S;Hollema, H;Bartlett, J M S;Brown, R;van der Zee, A G J
在一项两中性的研究中，p53免疫染色在来自上皮卵巢癌患者的大量肿瘤中的预后影响得到了分析。研究人群（n = 476）由一个回顾性系列188例患者（荷兰队列）和一组预期的288名患者（苏格兰队列）组成，该患者（苏格兰队列）参加了临床试验。通过在组织微阵列上的免疫组织化学确定p53表达。通过单变量和多元COX回归分析分析与无进展生存期（PFS）和总生存期（OS）的关联。异常p53的过表达与荷兰和苏格兰队列中的PF显着相关（分别为p = 0.001和0.038），但在单变量分析中与OS无关。在多变量分析中，当将这两组组合在一起并考虑了队列的临床因素和起源国家时，p53表达不是PFS或OS的独立预后预测指标。在这项具有最小方法学变异性的能力较低的研究中，p53免疫染色并不是上皮卵巢癌临床结果的独立预后标志。数据表明，如果要合并来自多中心研究的生物标志物数据，则方法学标准化的重要性，尤其是定义患者特征和生存终点数据的重要性。
The prognostic impact of p53 immunostaining in a large series of tumours from epithelial ovarian cancer patients in a two-centre study was analysed. The study population (n=476) comprised of a retrospective series of 188 patients (Dutch cohort) and a prospective series of 288 patients (Scottish cohort) enrolled in clinical trials. P53 expression was determined by immunohistochemistry on tissue microarrays. Association with progression-free survival (PFS) and overall survival (OS) was analysed by univariate and multivariate Cox regression analysis. Aberrant p53 overexpression was significantly associated with PFS in the Dutch and Scottish cohorts (P=0.001 and 0.038, respectively), but not with OS in univariate analysis. In multivariate analysis, when the two groups were combined and account taken of clinical factors and country of origin of the cohort, p53 expression was not an independent prognostic predictor of PFS or OS. In this well-powered study with minimal methodological variability, p53 immunostaining is not an independent prognostic marker of clinical outcome in epithelial ovarian cancer. The data demonstrate the importance of methodological standardisation, particularly defining patient characteristics and survival end-point data, if biomarker data from multicentre studies are to be combined.