OBJECTIVE: The aim of the study was to conceptualize neuropsychiatric symptoms in patients with Alzheimer disease as distinct symptom profiles with differential disease outcomes. Two outcomes of interest in the study were nursing home placement and survival. METHOD: Cluster analysis was used to categorize 122 patients with Alzheimer disease based on their neuropsychiatric symptoms as assessed by the Neuropsychiatric Inventory. Both the presence as well as the severity and frequency of symptoms were considered. After identification of the subgroups, the predictive validity of the categorization was tested on time to nursing home placement and time to death over a three-year period. Cox proportional hazard models were used to perform survival analysis. Important covariates such as severity of cognitive and functional impairments, comorbid medical conditions, presence of parkinsonism, and marital status were adjusted at baseline. RESULTS: Based on the presence of neuropsychiatric symptoms, three subgroups were identified: minimally symptomatic, highly symptomatic, and affective/apathetic. Over a three-year period, the highly symptomatic group had an increased risk of nursing home placement. In addition, the rates of survival were significantly lower for the highly symptomatic and the affective/apathetic subgroups. Based on the severity and frequency of symptoms, two-cluster and four-cluster solutions were produced. The groupings based on severity and frequency of symptoms predicted significant differential outcomes in survival and nursing home placement. CONCLUSIONS: Neuropsychiatric subgroups were able to predict differential outcomes and identify those with an increased risk for a worse prognosis. The findings were discussed through their research and clinical implications.
OBJECTIVE: The aim of the study was to conceptualize neuropsychiatric symptoms in patients with Alzheimer disease as distinct symptom profiles with differential disease outcomes. Two outcomes of interest in the study were nursing home placement and survival. METHOD: Cluster analysis was used to categorize 122 patients with Alzheimer disease based on their neuropsychiatric symptoms as assessed by the Neuropsychiatric Inventory. Both the presence as well as the severity and frequency of symptoms were considered. After identification of the subgroups, the predictive validity of the categorization was tested on time to nursing home placement and time to death over a three-year period. Cox proportional hazard models were used to perform survival analysis. Important covariates such as severity of cognitive and functional impairments, comorbid medical conditions, presence of parkinsonism, and marital status were adjusted at baseline. RESULTS: Based on the presence of neuropsychiatric symptoms, three subgroups were identified: minimally symptomatic, highly symptomatic, and affective/apathetic. Over a three-year period, the highly symptomatic group had an increased risk of nursing home placement. In addition, the rates of survival were significantly lower for the highly symptomatic and the affective/apathetic subgroups. Based on the severity and frequency of symptoms, two-cluster and four-cluster solutions were produced. The groupings based on severity and frequency of symptoms predicted significant differential outcomes in survival and nursing home placement. CONCLUSIONS: Neuropsychiatric subgroups were able to predict differential outcomes and identify those with an increased risk for a worse prognosis. The findings were discussed through their research and clinical implications.
Authors: Donovan T Maust; Hyungjin Myra Kim; Lisa S Seyfried; Claire Chiang; Janet Kavanagh; Lon S Schneider; Helen C Kales Journal: JAMA Psychiatry Date: 2015-05 Impact factor: 21.596
Authors: James R Hall; April R Wiechmann; Leigh A Johnson; Melissa Edwards; Robert C Barber; Rebecca Cunningham; Meharvan Singh; Sid E O'Bryant Journal: Dement Geriatr Cogn Disord Date: 2014-07-04 Impact factor: 2.959