摘要
目的对于肿瘤病人的预后分析,传统方法多集中于对预后相关因素的探讨,而由生存树方法得到的预后分组不仅可以有助了解具有相似预后人群的临床特征,还可以从中发现传统的生存模型不易发现的交互作用。方法本文结合生存树方法与传统的Cox回归模型,对235例胃癌病人进行预后分析。结果在Cox回归中,淋巴结转移、肿瘤大小、手术切缘有无癌组织作为3个独立的预后因素被筛选出来;对该资料进行生存树分析,得到3个预后子群,其中位生存期分别为24个月、12个月、5个月。结论将生存树方法与Cox回归模型相结合,可以得到更完善的预后分析结论。
Objective The traditional model focused on assessing the relative prognostic factors, while the survival tree method could identify subsets of patients with homogeneous clinical feature. It was also useful for detecting nonlinear interactions between baseline variables. Methods The survival tree and Cox regression were applied to analyze prognostic among 235 patients with gastric cancer. Results Lymph nodemetastasis, tumor size and cancer cells of operation cutting were selected to be independent factors in Cox regression, three subgroups of patients were found with median survival times of 24, 12 and 5 months respectively. Conclusions Combined with Cox regression, the survival tree method may be helpful to perfect the prognostic analysis,
出处
《疾病控制杂志》
2005年第6期557-560,共4页
Chinese Journal of Disease Control and Prevention
关键词
存活率
比例危险度模型
预后
Survival rate
Proportional hazards models
Prognosis
