中医临床疗效评价的统计方法  

Statistical Methods for Evaluating Clinical Therapeutic Effects

作　　者：易丹辉[1] 李芃芃 童小军[1] 

机构地区：[1]中国人民大学统计学院中国人民大学应用统计科学研究中心,北京100872

出　　处：《世界科学技术-中医药现代化》2007年第4期81-85,共5页Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology

基　　金：国家"十一五"科撑计划项目(2006BAI08805-09):"中医药诊疗与评价技术研究"之课题"中医药诊疗信息处理技术研究"子课题"中医临床疗效评价技术探索"子课题

摘　　要：临床疗效评价的目的是寻找针对某种疾病、某类人群的有效治疗方案、方法、手段、药方。在临床治疗的实际过程中,通过试验设计,可以选定一些人群,采用随机分组控制一些影响因素,由于预期结果并不仅仅是研究因素,还有许多混杂因素,这些修饰因素作为解释变量或称自变量、协变量参与临床疗效研究,运用统计模型对疗效做出分析评价。Logistic模型、Cox比率危险率模型、纵向数据模型、多层线性模型都是可以用于临床疗效评价的统计方法。The purpose of evaluating clinical therapeutic effects is to confirm the effectiveness of a therapeutic plan, method, and recipe in treating diseases, in the context of selected patients. In the course of clinical treatment, we may choose some patients groups, and control some influence factors using random grouping. However, the realization of anticipated results has to be determined by a range of mixed factors. As a result, it is difficult to make an evaluation merely using a statistical method with an identical time. Fortunately, we can treat them as decorative factors, i. e. , explanation variables, independent variables, or covariates, before making the evaluation using statistical models. As index types that reflect the efficacy of clinical treatment are different, statistical models have to be different too. Logistic model, Cox proportional hazards regression model, longitudinal models, and multilevel linear model are useful statistical approaches for evaluating clinical therapeutic effects.

关 键 词：临床疗效评价Logistic模型 Cox比率危险率模型 纵向数据模型 多层线性模型 

分 类 号：R978.1[医药卫生—药品]