title: Multi-state Markov model in outcome of mild cognitive impairments among community elderly residents in Mainland China.
abstract: BACKGROUND
  Although knowledge of established risk factors for Alzheimer's disease (AD) can logically contribute to the search for predictors of the progression of cognitive impairment, it has not yet been firmly established where in the cognitive impairment process these risk factors exert their effects and how to predict quantitatively for the progression of mild cognitive impairments (MCI) to AD. This study aimed to determine whether known risk factors increased the risk of progression from MCI to AD and to make prediction based on transition probabilities.
  
  
  METHODS
  Based on ten examinations of 600 community-dwelling MCI residents and cognitive assessments to classify individuals into MCI, global impairment, and AD, a multi-state Markov Cox's regression model was used and the hazard ratios with their confidence intervals and transition probabilities were estimated.
  
  
  RESULTS
  Multivariate analysis showed that gender, age, and hypertension were statistically significant predictors of transition from MCI to global impairment; age, education, and reading statistically influenced transition from global impairment to MCI; gender, age, hypertension, diabetes, and apolipoprotein E geneε4 status were statistically associated with transition from global impairment to AD. Subjects at MCI were more likely (67%) to remain in that cognitive state at the next cognitive assessment than to transition to cognitive deterioration. For global impairment, probability of remaining in the same state was only 18% and that of forward transition was three times more likely than that of backward transition.
  
  
  CONCLUSIONS
  Known risk factors influenced differently for different transitions. Transition from global impairment was more likely to worsen to severe cognitive deterioration than transition from MCI.
authors.affiliation: Department of Health Statistics, School of Public Health, Shanxi Medical University, People's Republic of China. yu_hongmei@hotmail.com
authors.forename: Hong-mei
authors.initials: HM
authors.lastname: Yu
authors.forename: Shan-shan
authors.initials: SS
authors.lastname: Yang
authors.forename: Jian-wei
authors.initials: JW
authors.lastname: Gao
authors.forename: Li-ye
authors.initials: LY
authors.lastname: Zhou
authors.forename: Rui-feng
authors.initials: RF
authors.lastname: Liang
authors.forename: Cheng-yi
authors.initials: CY
authors.lastname: Qu
mesh_terms: D000203:Activities of Daily Living; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000523:psychology; D053327:Apolipoprotein E4; D001057:Apolipoproteins E; D002681:China; D060825:Cognitive Dysfunction / Q000175:diagnosis* / Q000523:psychology; D016001:Confidence Intervals; D003430:Cross-Sectional Studies; D018450:Disease Progression; D005260:Female; D006801:Humans; D008297:Male; D008390:Markov Chains; D009483:Neuropsychological Tests; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011594:Psychometrics; D012111:Residence Characteristics; D012307:Risk Factors; D012959:Socioeconomic Factors
chemical_list: D053327:Apolipoprotein E4; D001057:Apolipoproteins E