Sun Qianqian, Song Yanlong, Kong Panpan, Yu Hongmei
School of Public Health, Shanxi Medical University, Taiyuan 030001, China.
School of Public Health, Shanxi Medical University, Taiyuan 030001, China; Email:
Zhonghua Liu Xing Bing Xue Za Zhi. 2015 Mar;36(3):241-4.
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).
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.
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%).
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.
将竞争风险模型引入老年人轻度认知障碍(MCI)的预后预测,探讨MCI进展为阿尔茨海默病(AD)的影响因素。
收集2010年10月至2013年5月期间对太原市600名社区老年人进行的6次随访数据,随访间隔为6个月。将MCI状态定义为瞬态状态,AD及AD前死亡作为两个吸收状态(AD前死亡视为竞争风险事件),构建竞争风险模型以识别模型参数,并探讨MCI进展为AD的影响因素。同时,基于多状态马尔可夫模型估计3年MCI-AD转化概率。
经多变量竞争风险模型分析筛选,年龄较大(估计HR = 1.56,95%CI:1.01-2.39)、女性(HR = 1.72,95%CI:1.02-2.92)、受教育程度较高(HR = 0.64,95%CI:0.41-1.00)、经常阅读(HR = 0.57,95%CI:0.32-0.99)、高血压(HR = 3.43,95%CI:1.08-10.85)和收缩压较高(HR = 1.67,95%CI:1.04-2.66)等因素在3年内从MCI转化为AD方面具有统计学意义。3年MCI-AD转化概率为10.7%(95%CI:8.6%-13.2%)。
年龄、性别、教育程度、阅读和血压是MCI进展为AD的影响因素。竞争风险模型在研究具有多个潜在结局的纵向数据方面具有优势。