Dementia risk in the general population: large-scale external validation of prediction models in the AGES-Reykjavik study

We aimed to evaluate the external performance of prediction models for all-cause dementia or AD in the general population, which can aid selection of high-risk individuals for clinical trials and prevention. We identified 17 out of 36 eligible published prognostic models for external validation in the population-based AGES-Reykjavik Study. Predictive performance was assessed with c statistics and calibration plots. All five models with a c statistic > .75 (.76-.81) contained cognitive testing as a predictor, while all models with lower c statistics (.67-.75) did not. Calibration ranged from good to poor across all models, including systematic risk overestimation or overestimation for particularly the highest risk group. Models that overestimate risk may be acceptable for exclusion purposes, but lack the ability to accurately identify individuals at higher dementia risk. Both updating existing models or developing new models aimed at identifying high-risk individuals, as well as more external validation studies of dementia prediction models are warranted.

Automated summary

The study aimed to evaluate the external performance of prediction models for dementia or AD in the general population. Models with cognitive testing as a predictor showed better predictive performance, while calibration across all models ranged from good to poor, indicating potential risk overestimation for some models. Updating existing models or developing new ones for accurately identifying high-risk individuals is needed, along with more external validation studies on dementia prediction models.