基于潜在类别回归模型的失眠中医人群特征分类方法研究

项目名称： 基于潜在类别回归模型的失眠中医人群特征分类方法研究

项目编号： No.81503679

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 医药、卫生

项目作者： 刘岩

作者单位： 中国中医科学院中医临床基础医学研究所

项目金额： 18万元

中文摘要： 中医个体诊疗中“人群特征”如何科学表达是临床评价研究亟待解决的关键问题之一，主要原因是症状、体征等临床表型信息“高维、高稀疏、高相关冗余以及存在测量误差”的数据特点，且研究中忽视表型信息整体效应的评价。本研究提出“利用潜在类别综合降维的分析思想及其容许测量误差存在的优点，整合多维度的临床表型信息来解决”的工作假说，以现有1379例不同名老中医诊疗失眠的临床实际数据为载体，运用多源数据预处理技术、潜在类别回归法、非参数自助抽样法，构建失眠表型信息整体效应的人群分类模型，采用前瞻性横断面研究设计，拟收集200例失眠患者的临床数据进行验证，从而探索临床表型信息之间的交互关系，进一步验证潜在类别理论在中医人群分类研究的可行性和准确度。本研究在为失眠临床表型信息之间高阶交互作用问题的处理提供更为有效的统计模型及数据分析方法的同时，也为中医辨证论治过程中利用多维信息进行特征分类的辩证研究提供新途径。

中文关键词： 人群分类；潜在类别回归；高阶交互；中医；个体化诊疗

英文摘要： Establishment of patient classification standards is one of the key issues for clinical evaluation studies in TCM individualized treatment,. The main reason is clinical phenotypic information with the characteristics of high-dimensional, high-sparse, high redundancy and the presence of measurement error, and previous studies had ignored the overall effect of phenotypic information. In our study, working hypothesis is that the use of dimension reduction methods based in latent class variable modelling and allowing the presence of measurement error, TCM patient classification will integrate multi-dimensional clinical phenotypic information. Our study included the existing 1379 cases from famous highly experienced experts during diagnosis and treatment of insomnia disease, will adopt the multi-source data preprocessing technology, latent class regression analysis, Non-parametric bootstrap method, and build patient classification model based on overall effect of the clinical phenotype information, and then a cross-sectional study is designed as a prospective collection clinical data of 200 cases with insomnia, in order to explore the higher-order interaction among multiple clinical phenotypes, to further validate the feasibility and accuracy of latent class theory for TCM patient classification. This study will provide a more effective statistical model and data analysis methods for dealing with higher-order interaction among clinical phenotypic information of insomnia, and a new way for the research of TCM syndrome differentiation with multi-dimensional information.

英文关键词： Patient Classification;Latent Class Regression;Higher-Order Interactions;Medicine; Chinese Traditional ;Individualized Treatment