Dementia is a major global health concern, necessitating effective risk assessment tools early intervention. This study compared the performance of five modifiable dementia risk indices - ANU-ADRI, CAIDE, CogDrisk, LIBRA, and LIBRA2 and a "demographics-only" (age, education) model. We analyzed data from 5247 Norwegian participants in the Trøndelag Health Study (HUNT4 70+, 2017-2019) and dementia risk indices from baseline data in HUNT3 (2006-2008). Logistic regression models assessed associations between standardized index scores and all-cause dementia and Alzheimer's disease (AD) across age group (<65 vs. ≥65 years), sex, and APOE4 status. During the mean follow-up of 10.6 (9.3-12.3) years (SD=0.74), all indices significantly predicted dementia and AD, though none outperformed the demographics-only model. CogDrisk showed significantly better discriminative ability than all other indices (0.76, 95 % CI:0.74-0.78; DeLong p < 0.05), followed by LIBRA (0.75, 95 % CI:0.72-0.77) and ANU-ADRI (0.74, 95 % CI:0.72-0.76). LIBRA2 (0.69, 95 % CI:0.66-0.71) and CAIDE (0.59, 95 % CI:0.56-0.61) had significantly lower accuracy (DeLong p < 0.001). Removing demographics maintained rank order but reduced accuracy across all indices. Stratified analyses showed stronger performance in those ≥65 years and females at HUNT3, while APOE4 status did not affect performance. All indices were associated with dementia risk, with CogDrisk performing best across all conditions, and LIBRA2 and CAIDE performing weakest. No index outperformed a model including age and education only. Future research should refine risk indices for age- and sex-specific applications and assess whether simpler demographic models may suffice in some contexts.
Stuebs et al. (Fri,) studied this question.