Using tumor markers to predict the survival of patients with metastatic renal cell carcinoma
Using tumor markers to predict the survival of patients with metastatic renal cell carcinoma
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DOI：
10.1097/01.ju.0000154351.37249.f0
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发表时间：
2005-05-01
影响因子：
6.6
通讯作者：
Figlin, RA
中科院分区：
文献类型：
--
作者：
Kim, HL;Seligson, D;Figlin, RA
目的：大约30%的肾细胞癌（RCCs）表现为转移性疾病。分子标记物有可能准确地描述肿瘤的生物学行为，它们可能对确定预后有用。材料和方法：使用150例在免疫治疗前接受肾切除术的转移性肾细胞癌患者的透明细胞肾细胞癌构建定制组织阵列。组织阵列对Ki67、p53、gelsolin、碳酸酐酶（CA）9、CA12、PTEN（10号染色体上缺失的磷酸酶和紧张素同源物）、上皮细胞粘附分子和vimentin 8个分子标记进行染色。在建立疾病特异性生存的预后模型时，应考虑标志物状态和已建立的临床预后预测因子。结果：单因素Cox回归分析显示，CA9 （p < 0.00001）、p53 （p = 0.0072）、gelsolin （p = 0.030）、Ki67 （p = 0.036）和CA12 （p = 0.043）是有统计学意义的生存预测因子。纳入所有标志物和临床变量的多因素Cox回归分析显示，CA9 （p = 0.00002）、PTEN （p < 0.0001）、vimentin （p = 0.0032）、p53 （p = 0.028）、T类别（p = 0.0025）和工作状态（p = 0.0013）是疾病特异性生存的显著独立预测因子，并用于构建分子与临床联合预后模型。该联合预后模型的偏倚校正一致性指数（C-index）为C = 0.68，显著高于基于UCLA综合分期系统（T分类、组织学分级和表现状态）的多变量临床预测模型（C = 0.62） （p = 0.0033）。结论：在透明细胞癌患者中，包括分子和临床预测因素的生存预后模型明显比结合分期、组织学分级和表现状态的标准临床模型更准确。
Purpose: Approximately 30% of renal cell carcinomas (RCCs) present as metastatic disease. Molecular markers have the potential to characterize accurately the biological behavior of tumors and they may be useful for determining prognosis.Materials and Methods: A custom tissue array was constructed using clear cell RCC from 150 patients with metastatic RCC who underwent nephrectomy prior to immunotherapy. The tissue array was stained for 8 molecular markers, namely Ki67, p53, gelsolin, carbonic anhydrase (CA)9, CA12, PTEN (phosphatase and tensin homologue deleted on chromosome 10), epithelial cell adhesion molecule and vimentin. Marker status and established clinical predictors of prognosis were considered when developing a prognostic model for disease specific survival.Results: On univariate Cox regression analysis certain markers were statistically significant predictors of survival, namely CA9 (p < 0.00001), p53 (p = 0.0072), gelsolin (p = 0.030), Ki67 (p = 0.036) and CA12 (p = 0.043). On multivariate Cox regression analysis that included all markers and clinical variables CA9 (p = 0.00002), PTEN (p < 0.0001), vimentin (p = 0.0032), p53 (p = 0.028), T category (p = 0.0025) and performance status (p = 0.0013) were significant independent predictors of disease specific survival and they were used to construct a combined molecular and clinical prognostic model. The bias corrected concordance index (C-index) of this combined prognostic model was C = 0.68, which was significantly higher (p = 0.0033) than that of a multivariate clinical predictor model (C = 0.62) based on the UCLA Integrated Staging System (T category, histological grade and performance status).Conclusions: In patients with clear cell RCC a prognostic model for survival that includes molecular and clinical predictors is significantly more accurate than a standard clinical model using the combination of stage, histological grade and performance status.