title: Latent classes of course in Alzheimer's disease and predictors: the Cache County Dementia Progression Study.
abstract: OBJECTIVE
  Several longitudinal studies of Alzheimer's disease (AD) report heterogeneity in progression. We sought to identify groups (classes) of progression trajectories in the population-based Cache County Dementia Progression Study (N = 328) and to identify baseline predictors of membership for each group.
  
  
  METHODS
  We used parallel-process growth mixture models to identify latent classes of trajectories on the basis of Mini-Mental State Exam (MMSE) and Clinical Dementia Rating sum of boxes scores over time. We then used bias-corrected multinomial logistic regression to model baseline predictors of latent class membership. We constructed receiver operating characteristic curves to demonstrate relative predictive utility of successive sets of predictors.
  
  
  RESULTS
  We fit four latent classes; class 1 was the largest (72%) and had the slowest progression. Classes 2 (8%), 3 (11%), and 4 (8%) had more rapid worsening. In univariate analyses, longer dementia duration, presence of psychosis, and worse baseline MMSE and Clinical Dementia Rating sum of boxes were associated with membership in class 2, relative to class 1. Lower education was associated with membership in class 3. In the multivariate model, only MMSE remained a statistically significant predictor of class membership. Receiver operating characteristic areas under the curve were 0.98, 0.88, and 0.67, for classes 2, 3, and 4 relative to class 1.
  
  
  CONCLUSIONS
  Heterogeneity in AD course can be usefully characterized using growth mixture models. The majority belonged to a class characterized by slower decline than is typically reported in clinical samples. Class membership could be predicted using baseline covariates. Further study may advance our prediction of AD course at the population level and in turn shed light on the pathophysiology of progression.
authors.affiliation: Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Jeannie-Marie S
authors.initials: JM
authors.lastname: Leoutsakos
authors.affiliation: Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Sarah N
authors.initials: SN
authors.lastname: Forrester
authors.affiliation: Center for Epidemiologic Studies, Utah State University, Logan, UT, USA.|Department of Mathematics and Statistics, Utah State University, Logan, UT, USA.
authors.forename: Christopher D
authors.initials: CD
authors.lastname: Corcoran
authors.affiliation: Center for Epidemiologic Studies, Utah State University, Logan, UT, USA.|Department of Psychology, Utah State University, Logan, UT, USA.|Department of Family, Consumer and Human Development, Utah State University, Logan, UT, USA.
authors.forename: Maria C
authors.initials: MC
authors.lastname: Norton
authors.affiliation: Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Peter V
authors.initials: PV
authors.lastname: Rabins
authors.affiliation: Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Martin I
authors.initials: MI
authors.lastname: Steinberg
authors.affiliation: Center for Epidemiologic Studies, Utah State University, Logan, UT, USA.|Department of Psychology, Utah State University, Logan, UT, USA.
authors.forename: Joann T
authors.initials: JT
authors.lastname: Tschanz
authors.affiliation: Department of Psychiatry, Division of Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Constantine G
authors.initials: CG
authors.lastname: Lyketsos
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000145:classification* / Q000175:diagnosis / Q000523:psychology; D018450:Disease Progression; D005260:Female; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D011569:Psychiatric Status Rating Scales; D012372:ROC Curve
keywords: Alzheimer; disease course; growth mixture model; trajectory