Validation of the IberScore model in a primary care population

Clin Investig Arterioscler. 2024 May-Jun;36(3):101-107. doi: 10.1016/j.arteri.2023.12.003. Epub 2024 Jan 13.
[Article in English, Spanish]

Abstract

Background: This study aimed to validate the IberScore cardiovascular risk model in a population attended in the primary care setting.

Methods: A cohort of patients with no history of cardiovascular disease visited in a primary care center during the years 2008 and/or 2009 and followed up until 2018 was selected. Cardiovascular risk was calculated with the IberScore formula for all the subjects of the cohort and the model was calibrated, graphically represented by risk deciles the proportion of expected events and proportion of observed events at 10-year follow-up, stratified by sex. The area under the ROC curve was calculated to assess the discrimination of the model.

Results: A total of 10,085 patients visited during the years 2008 and/or 2009 were included in the study. Men showed a mean 10-year risk of suffering a fatal or non-fatal cardiovascular events according to IberScore of 17.07% (SD 20.13), with a mean estimated vascular age of more than 4 years higher than the biological age; while women had a mean 10-year risk of 7.91% (SD 9.03), with an estimated vascular age of more than 2 years above the biological age. The area under the ROC curve showed a discrimination index of the model of 0.86 (95% CI 0.84-0.88) in men and 0.82 (95% CI 0.79-0.85) in women.

Conclusion: IberScore model discriminates well in the population attended in primary care but the model overestimates the risk.

Keywords: Cardiovascular disease; Enfermedad cardiovascular; Predicción del riesgo; Prevención primaria; Primary prevention; Risk prediction.

Publication types

  • Validation Study

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Cardiovascular Diseases* / epidemiology
  • Cohort Studies
  • Female
  • Follow-Up Studies
  • Heart Disease Risk Factors*
  • Humans
  • Male
  • Middle Aged
  • Primary Health Care*
  • ROC Curve
  • Risk Assessment / methods
  • Sex Factors