Predicting dementia risk: Discrimination accuracy of the NCGG-FAT

Early detection of mild cognitive impairment (MCI) is essential for dementia prevention. We developed the National Center for Geriatrics and Gerontology-Functional Assessment Tool (NCGG-FAT) using age- and education-adjusted norms with a 1.5 standard deviation (SD) cutoff. This study examined the associations between cognitive domains assessed by the NCGG-FAT and incident dementia using the existing and expanded databases.

A 5-year prospective cohort of 2,441 participants without dementia at baseline was analyzed. Hazard ratios (HRs) and 95% confidence intervals (CIs) for individual cognitive tests and cognitive states (normal cognition, MCI, and global cognitive impairment) were estimated using Cox proportional hazards models. Competing risk of death was addressed using Fine-Gray models. Predictive models for dementia were also developed and validated.

In the expanded database, declines ≥1.5 SD in word list memory, TMT-B, forward and backward digit span, and SDST were significantly associated with dementia onset (HRs 1.77-3.22). Fine-Gray analyses yielded similar results. For cognitive states, amnestic and non-amnestic MCI, particularly moderate subtypes, and global cognitive impairment showed elevated risks (HRs 1.55-2.92), although some associations lost significance after accounting for competing mortality. The NCGG-FAT composite score demonstrated high discrimination for incident dementia (AUC = 0.96; accuracy = 0.95).

The expanded NCGG-FAT database is a useful auxiliary tool for assessing future dementia risk in community-dwelling older adults.