中文摘要：

目的 建立轻度认知损害（mild cognitive impairment,MCI）向阿尔茨海默病（Alzheimer＇s disease,AD）状态转归的时间转换Markov模型,探讨MCI状态向AD状态转归的影响因素并进行转归预测,同时对模型进行评价。方法 截止到2012年对太原市518名社区老年人共进行5次随访调查,将MCI到AD的过程分为MCI（状态1）,中重度认知损害状态（状态2）和AD（状态3）3个状态。对随访数据拟合3状态的时间转换Markov模型,评价模型拟合情况并分析AD进程不同阶段的影响因素,依据拟合的时间转换Markov模型计算转移强度矩阵,并预测3年转移概率。结果 通过假设检验,数据不满足时齐性（P0.05）。采用时间转换Markov模型,经多因素筛选,发现性别、年龄、教育水平、工作类型、吸烟和高血压对状态1到状态2的转移有统计学意义,年龄、教育水平、工作类型、糖尿病和高血压对状态1到状态3的转移有统计学意义,年龄、教育水平、吸烟、糖尿病和高血压对状态2到状态3的转移有统计学意义。结论 在AD发展进程的不同阶段,主要影响因素不同。与齐次Markov模型相比,时间转换Markov模型能更全面地分析相关的影响因素与探讨疾病进程的变化规律。

英文摘要：

Objective Based on a time transformation Markov model,the aims of this study were to find out related factors which influence the risk of progression on various progressive stages and to make prediction in outcome of mild cognitive impairment（MCI） to Alzheimer＇s disease （AD） and evaluate the model at the same time. Methods Our data came from five waves of cohort study of 518 community elders in Taiyuan by the end of 2012. The progression from MCI to AD were defined as MCI（ state 1 ）, moderate to severe cognitive impairment（ state 2）, and AD（ state 3 ）. A three-state time transformation Markov model was evaluated and applied to explore influencing factors at different disease stages. According to the fitted time transfor- mation Markov model, transition intensities and three years transition probabilities among each state were also estimated. Results Based on hypothesis testing, the time-homogeneous assumption was not satisfied（P 〈 0. 005 ）and the Markov assump- tion was satisfied（P =0. 468）,so time transformation Markov model was applied and the goodness of fit is good（P 〉0. 05）. Multivariate analysis showed that gender, age education level, occupation, smoking and hypertention were statistically significant for transition from state 1 to state 2;age, education level, occupation, diabetes and hypertension were statistically significant for transition from state 1 to state 3 ; age, education level, smoking, diabetes and hypertension were statistically significant for transition from state 2 to state 3. Conclusion The main influence factors of AD in each stage are different. Compared with homogeneous Markov model, the time transformation Markov model is more all-around in the related factors analysis and variation pattern during disease progressive process.