A Bayesian model of psychosis symptom trajectory in Alzheimer's disease.

ABSTRACT:

Objective

Psychosis, like other neuropsychiatric symptoms of dementia, has many features that make predictive modeling of its onset difficult. For example, psychosis onset is associated with both the absolute degree of cognitive impairment and the rate of cognitive decline. Moreover, psychotic symptoms, while more likely than not to persist over time within individuals, may remit and recur. To facilitate predictive modeling of psychosis for personalized clinical decision making, including evaluating the role of risk genes in its onset, we have developed a novel Bayesian model of the dual trajectories of cognition and psychosis symptoms.

Methods

Cognition was modeled as a four-parameter logistic curve with random effects for all four parameters and possible covariates for the

SUBMITTER: Seltman HJ 

PROVIDER: S-EPMC4707989 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature