ABSTRACT
BACKGROUND: Lack of external validation of dementia risk tools is a major limitation for generalizability and translatability of prediction scores in clinical practice and research. OBJECTIVES: We aimed to validate a new dementia prediction risk tool called CogDrisk and a version, CogDrisk-AD for predicting Alzheimer's disease (AD) using cohort studies. DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS: Four cohort studies were identified that included majority of the dementia risk factors from the CogDrisk tool. Participants who were free of dementia at baseline were included. The predictors were component variables in the CogDrisk tool that include self-reported demographics, medical risk factors and lifestyle habits. Risk scores for Any Dementia and AD were computed and Area Under the Curve (AUC) was assessed. To examine modifiable risk factors for dementia, the CogDrisk tool was tested by excluding age and sex estimates from the model. RESULTS: The performance of the tool varied between studies. The overall AUC and 95% CI for predicting dementia was 0.77 (0.57, 0.97) for the Swedish National study on Aging and Care in Kungsholmen, 0.76 (0.70, 0.83) for the Health and Retirement Study - Aging, Demographics and Memory Study, 0.70 (0.67,0.72) for the Cardiovascular Health Study Cognition Study, and 0.66 (0.62,0.70) for the Rush Memory and Aging Project. CONCLUSIONS: The CogDrisk and CogDrisk-AD performed well in the four studies. Overall, this tool can be used to assess individualized risk factors of dementia and AD in various population settings.