Performance of the CHARGE-AF risk model for incident atrial fibrillation in the EPIC Norfolk cohort

Eur J Prev Cardiol. 2015 Jul;22(7):932-9. doi: 10.1177/2047487314544045. Epub 2014 Jul 24.

Abstract

Background: Identification of individuals at risk for developing atrial fibrillation (AF) will help to target screening and preventive interventions. We aimed to validate the CHARGE-AF model (including variables age, race, height, weight, blood pressure, smoking, antihypertensive medication, diabetes, myocardial infarction and heart failure) for prediction of five-year incident AF in a representative European population with a wide age range.

Methods and results: The CHARGE-AF model was calculated in 24,020 participants of the population-based EPIC Norfolk study with 236 cases of hospitalization with diagnosis of AF within five years. The model showed good discrimination (c-statistic 0.81, 95% confidence interval (CI) 0.75-0.85), but weak calibration (Chi(2)-statistic 142) with an almost two-fold overestimation of AF incidence. A recalibration to characteristics of the European Prospective Investigation into Cancer and Nutrition (EPIC) Norfolk cohort improved calibration considerably (Chi(2)-statistic 13.3), with acceptable discrimination in participants both >65 and ≤65 years of age (c-statistics 0.70, 95% CI 0.61-0.77 and 0.83, 95% CI 0.74-0.88). The recalibrated model also showed good discrimination in participants free of cardiovascular disease (c-statistics 0.80, 95% CI 0.75-0.84). Categories of predicted risk (<2.5%, 2.5-5% or >5%) showed good concordance with observed five-year AF incidence of 0.62%, 3.49% and 8.74% (log rank test p < 0.001), respectively.

Conclusion: A recalibration of the CHARGE-AF model is necessary for accurate predictions of five-year risk of AF in the EPIC Norfolk population. The recalibrated model showed good discrimination across a wide age range and in individuals free of cardiovascular disease, and hence is broadly applicable in primary care to identify people at risk for development of AF.

Keywords: Atrial fibrillation; risk prediction; score.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Atrial Fibrillation / diagnosis
  • Atrial Fibrillation / epidemiology*
  • Atrial Fibrillation / ethnology
  • Chi-Square Distribution
  • Comorbidity
  • Discriminant Analysis
  • England / epidemiology
  • European Continental Ancestry Group
  • Female
  • Health Status Indicators*
  • Health Status*
  • Humans
  • Incidence
  • Kaplan-Meier Estimate
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Primary Health Care
  • Proportional Hazards Models
  • Prospective Studies
  • Reproducibility of Results
  • Risk Assessment
  • Risk Factors
  • Smoking / adverse effects
  • Time Factors