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Updated: Oct 1, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Dementia Risk Score for a Population in Southern Europe Calculated Using Competing Risk Models
Oliver Ibarrondo1,2, José María Huerta3,4,5, Pilar Amiano2,5,6
1Research Unit, Debagoiena Integrated Healthcare Organisation, Basque Health Service (Osakidetza), Arrasate-Mondragón, Spain.
Background:
Dementia prevention can be addressed if the intervention is applied early.
Objective:
The objective of this study was to develop and validate competing risk models to predict the late risk of dementia based on variables assessed in middle age in a southern European population.
Methods:
We conducted a prospective observational study of the EPIC-Spain cohort that included 25,015 participants. Dementia cases were identified from electronic health records and validated by neurologists. Data were gathered on sociodemographic characteristics and cardiovascular risk factors. To stratify dementia risk, Fine and Gray competing risk prediction models were constructed for the entire sample and for over-55-year-olds. Risk scores were calculated for low (the 30% of the sample with the lowest risk), moderate (> 30% -60%), and high (> 60% -100%) risk.
Results:
The 755 cases of dementia identified represented a cumulative incidence of 3.1% throughout the study period. The AUC of the model for over-55-year-olds was much higher (80.8%) than the overall AUC (68.5%) in the first 15 years of follow-up and remained that way in the subsequent follow-up. The weight of the competing risk of death was greater than that of dementia and especially when the entire population was included.
Conclusion:
This study presents the first dementia risk score calculated in a southern European population in mid-life and followed up for 20 years. The score makes it feasible to achieve the early identification of individuals in a southern European population who could be targeted for the prevention of dementia based on the intensive control of risk factors.
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