Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi · 2015
[Competing risk model based study of outcomes of mild cognitive impairment of seniors].
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Sun Qianqian, Song Yanlong, Kong Panpan, Yu Hongmei
Аннотация
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.
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.