Development and validation of the age-associated dementia policy (AgeD-Pol) computer simulation model in the USA and Europe.

ABSTRACT

OBJECTIVE: To develop and validate a novel, microsimulation model that accounts for the prevalence and incidence of age-associated dementias (AAD), disease progression and associated mortality. DESIGN, DATA SOURCES AND OUTCOME MEASURES: We developed the AAD policy (AgeD-Pol) model, a microsimulation model to simulate the natural history, morbidity and mortality associated with AAD. We populated the model with age-stratified and sex-stratified data on AAD prevalence, AAD incidence and mortality among people with AAD. We first performed internal validation using data from the Adult Changes in Thought (ACT) cohort study. We then performed external validation of the model using data from the Framingham Heart Study, the Rotterdam Study and Kaiser Permanente Northern California (KPNC). We compared model-projected AAD cumulative incidence and mortality with published cohort data using mean absolute percentage error (MAPE) and root-mean-square error (RMSE). RESULTS: In internal validation, the AgeD-Pol model provided a good fit to the ACT cohort for cumulative AAD incidence, 10.4% (MAPE, 0.2%) and survival, 66.5% (MAPE, 8.8%), after 16 years of follow-up among those initially aged 65-69 years. In the external validations, the model-projected lifetime cumulative incidence of AAD was 30.5%-32.4% (females) and 16.7%-23.0% (males), using data from the Framingham and Rotterdam cohorts, and AAD cumulative incidence was 21.5% over 14 years using KPNC data. Model projections demonstrated a good fit to all three cohorts (MAPE, 0.9%-9.0%). Similarly, model-projected survival provided good fit to the Rotterdam (RMSE, 1.9-3.6 among those with and without AAD) and KPNC cohorts (RMSE, 7.6-18.0 among those with AAD). CONCLUSIONS: The AgeD-Pol model performed well when validated to published data for AAD cumulative incidence and mortality and provides a useful tool to project the AAD disease burden for health systems planning in the USA.