COX交互效应模型在胶质母细胞瘤预后因素分析中的应用

发布时间：2018-07-09 23:20

  本文选题：胶质母细胞瘤 + 预后因子　； 参考：《浙江大学》2017年硕士论文

【摘要】：背景:胶质母细胞瘤是中枢神经系统中恶性程度最高、预后最差的肿瘤之一,最大程度肿瘤切除及术后同步放化疗为现阶段的标准治疗方案,但不同患者的预后存在较大差异,且目前为止仍未发现决定患者预后的核心因素。胶质母细胞瘤的异质性可能是造成预后差异的重要原因。因此,不同因素之间的交互效应可能对预后产生显著的作用。目的:验证目前已发现的胶质母细胞瘤预后相关因素;寻找并解读因素间交互效应;最终为胶质母细胞瘤个体化治疗方案的制定提供依据。方法:连续性地收集浙一医院2009年4月至2015年4月间住院治疗的66例胶质母细胞瘤病例。收集患者一般资料如性别、起病时年龄、基础疾病情况、确诊年份等;患者术前卡氏评分、症状、起病至手术时间间隔、肿瘤部位、手术治疗情况、术后并发症、放化疗、复发时间、复发后治疗、影像学表现、肿瘤分子标记物、术后生存期等。采用Cox比例风险模型进行单因素、多因素以及交互效应分析。结果:与胶质母细胞瘤总体生存期相关的独立危险因素包括肿瘤定位于额叶[HR(95%CI):0.339(0.185-0.622),P0.001;adjusted:0.186(0.059-0.586),P=0.004]、肿瘤完全切除[HR(95%CI):0.391(0.166-0.923),P=0.032;ad justed:0.110(0.020-0.610),P=0.012]、复发后积极治疗[HR(95%CI):0.321(0.118-0.871),P=0.026;adjusted:0.229(0.060-0.878),P=0.032]。与胶质母细胞瘤无进展生存期相关的独立危险因素主要为肿瘤定位于额叶[HR(95%CI):0.412(0.227-0.748),P=0.004;adjusted:0.382(0.172-0.850),P=0.018]。除广泛的二阶交互效应网络外,复发后治疗、前额叶肿瘤、术前卡氏评分之间存在显著的三阶交互效应(HR:0.957,95%CI:0.920-0.996,P=0.030)。结论:因素间交互效应与胶质母细胞瘤的预后存在相关性,提示可基于交互效应进行胶质母细胞瘤预后评估、指导个体化治疗方案制定。
[Abstract]:Background: glioblastoma is one of the most malignant tumors with the worst prognosis in the central nervous system. So far, no core factors have been found to determine the prognosis of patients. The heterogeneity of glioblastoma may be an important reason for the difference of prognosis. Therefore, the interaction between different factors may play a significant role in prognosis. Objective: to verify the prognostic factors of glioblastoma, to find out the interaction between the factors, and to provide the basis for the individual treatment of glioblastoma. Methods: 66 cases of glioblastoma were collected from April 2009 to April 2015 in Zhejiang first Hospital. Collect general data of patients such as gender, age at onset, condition of underlying disease, year of diagnosis, etc. The patients had preoperative Karnox score, symptoms, time interval between onset and operation, tumor location, surgical treatment, postoperative complications, radiotherapy and chemotherapy, etc. Recurrence time, post-recurrence therapy, imaging findings, tumor molecular markers, postoperative survival time, etc. Cox proportional hazard model was used to analyze single factor, multi factor and interaction effect. 缁撴灉:涓庤兌璐ㄦ瘝缁嗚優鐦ゆ，

本文编号：2111084