Dementia Population Risk Tool (DemPoRT): study protocol for a predictive algorithm assessing dementia risk in the...

Area of Science:

• Gerontology
• Epidemiology
• Biostatistics

Background:

• Dementia prevalence is a growing global concern due to increasing life expectancy and aging populations.
• Current dementia prevalence projections lack accuracy, hindering effective public health planning.
• Reliable dementia incidence and prevalence prediction is crucial for resource allocation and healthcare strategies.

Purpose of the Study:

• To develop and validate the Dementia Population Risk Tool (DemPoRT) for predicting dementia incidence and prevalence.
• To enhance the accuracy of population-level dementia projections using multivariable modeling.
• To provide a tool for clinicians and policymakers to better understand and plan for dementia in aging demographics.

Main Methods:

• Utilized Canadian Community Health Survey (CCHS) data (2001, 2003, 2005, 2007) for model derivation, including sociodemographic, health, and functional variables.
• Linked survey respondents to administrative healthcare databases to identify incident dementia cases, treating death as a competing risk.
• Employed sex-specific proportional hazards regression models and validated the DemPoRT algorithm using the 2008/2009 CCHS survey data.

Main Results:

• Sex-specific proportional hazards regression models were estimated to predict dementia incidence.
• The Dementia Population Risk Tool (DemPoRT) was developed for projecting dementia prevalence.
• Validation assessed calibration and discrimination within clinically relevant subgroups.

Conclusions:

• The Dementia Population Risk Tool (DemPoRT) offers improved predictive accuracy for dementia incidence and prevalence.
• DemPoRT will aid in more reliable planning for aging populations and dementia care.
• The algorithm will be accessible online for both population and individual risk assessments.