基于竞争风险模型的老年人轻度认知损害转归研究

目的 将竞争风险模型应用于老年人轻度认知损害(MCI)转归研究,探讨MCI向阿尔茨海默病(AD)转归的影响因素并进行转归预测。方法 利用太原市600例社区老年人2010年10月至2013年5月每6个月随访1次的共6次随访数据,以MCI作为暂态,AD与发生AD前死亡分别作为两个吸收态,发生AD前死亡为AD的竞争风险事件,构建竞争风险模型,获得模型参数,分析MCI向AD转归的影响因素,同时根据多状态模型估计3年转移概率。结果 经过多因素竞争风险模型筛选,高年龄(HR=1.56,95%CI:1.01～2.39)、女性(HR=1.72,95%CI:1.02～2.92)、高文化程度(HR=0.64,95%CI:0.41～1.00)、经常读书看报(HR=0.57,95%CI:0.32～0.99)、有高血压(HR=3.43,95%CI:1.08～10.85)和高SBP(HR=1.67,95%CI:1.04～2.66)是MCI转移为AD的影响因素。MCI 3年后转移为AD的概率为10.7%(95%CI:8.6%～13.2%)。结论 年龄、性别、文化程度、高血压,读书看报和SBP对MCI状态向AD状态的转归过程有影响。竞争风险模型对具有多种潜在结局的纵向资料分析有一定的优势。

Competing risk model based study of outcomes of mild cognitive impairment of seniors

Objective To introduce the competing risk model into outcome prediction of mild cognitive impairment (MCI) of seniors and to explore influencing factors for the prognosis of MCI to Alzheimer''s disease (AD). Methods Data were collected from six follow-up visits to 600 seniors from communities in Taiyuan city, which were conducted at an interval of six months from October 2010 to May 2013. MCI state was defined as the transient state, AD and death before AD as two absorbing states (death before AD in which was regarded as a competing risk event), building the competing risk model to identify the model parameters, and to explore influencing factors on MCI prognosis to AD. In the meantime, the 3-year MCI-AD transition probability was estimated based on the multi-state Markov model. Results Based on screening with the multivariate competing risk model analysis,factors such as higher age (estimate HR=1.56,95%CI:1.01-2.39), female gender (HR=1.72,95%CI:1.02-2.92), higher education(HR=0.64, 95%CI:0.41-1.00),reading frequently(HR=0.57,95%CI:0.32-0.99),hypertension (HR=3.43,95%CI:1.08-10.85) and high SBP(HR=1.67,95%CI:1.04-2.66), were statistically significant for transition from MCI to AD in three years. 3-year MCI-AD transition probability was 10.7%(95%CI:8.6%-13.2%). Conclusion Age,gender,education,reading and blood pressure were the influencing factors for the prognosis of MCI to AD. Competing risk model was advantageous in studying longitudinal data with multiple potential outcomes.