Predicting dementia risk: Discrimination accuracy of the NCGG-FAT

Area of Science:

• Gerontology
• Neurology
• Cognitive Science

Background:

• Early detection of mild cognitive impairment (MCI) is vital for effective dementia prevention strategies.
• The National Center for Geriatrics and Gerontology-Functional Assessment Tool (NCGG-FAT) was developed using age- and education-adjusted norms with a 1.5 standard deviation (SD) cutoff.
• Assessing cognitive domains is key to identifying individuals at risk for dementia.

Purpose of the Study:

• To examine the associations between cognitive domains assessed by the NCGG-FAT and the incidence of dementia.
• To validate the predictive capabilities of the NCGG-FAT using existing and expanded databases.
• To evaluate the NCGG-FAT's utility in community-dwelling older adults for dementia risk assessment.

Main Methods:

• A 5-year prospective cohort study of 2,441 participants without dementia at baseline.
• Cox proportional hazards models and Fine-Gray models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), accounting for competing risks of death.
• Predictive models for dementia were developed and validated using the NCGG-FAT cognitive assessments.

Main Results:

• Declines of ≥1.5 SD in specific cognitive tests (word list memory, TMT-B, digit span, SDST) were significantly associated with dementia onset (HRs 1.77-3.22).
• Both amnestic and non-amnestic MCI, particularly moderate subtypes, and global cognitive impairment indicated elevated dementia risks (HRs 1.55-2.92).
• The NCGG-FAT composite score demonstrated high predictive accuracy for incident dementia (AUC = 0.96; accuracy = 0.95).

Conclusions:

• The expanded NCGG-FAT database serves as a valuable auxiliary tool for assessing future dementia risk.
• The NCGG-FAT effectively identifies cognitive declines associated with increased dementia risk in community-dwelling older adults.
• This tool aids in early detection, supporting dementia prevention efforts.