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Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study

Daniel Mølager Christensen, Matthew Phelps, Thomas Gerds, Morten Malmborg, Anne-Marie Schjerning, Jarl Emanuel Strange, Mohamad El-Chouli, Lars Bruun Larsen, Emil Fosbøl, Lars Køber, Christian Torp-Pedersen, Suneela Mehta, Rod Jackson, Gunnar Gislason

12 Citations (Scopus)

Abstract

Aims: The aim of this study was to derive and validate a risk prediction model with nationwide coverage to predict the individual and population-level risk of cardiovascular disease (CVD).

Methods and results: All 2.98 million Danish residents aged 30-85 years free of CVD were included on 1 January 2014 and followed through 31 December 2018 using nationwide administrative healthcare registries. Model predictors and outcome were pre-specified. Predictors were age, sex, education, use of antithrombotic, blood pressure-lowering, glucose-lowering, or lipid-lowering drugs, and a smoking proxy of smoking-cessation drug use or chronic obstructive pulmonary disease. Outcome was 5-year risk of first CVD event, a combination of ischaemic heart disease, heart failure, peripheral artery disease, stroke, or cardiovascular death. Predictions were computed using cause-specific Cox regression models. The final model fitted in the full data was internally-externally validated in each Danish Region. The model was well-calibrated in all regions. Area under the receiver operating characteristic curve (AUC) and Brier scores ranged from 76.3% to 79.6% and 3.3 to 4.4. The model was superior to an age-sex benchmark model with differences in AUC and Brier scores ranging from 1.2% to 1.5% and -0.02 to -0.03. Average predicted risks in each Danish municipality ranged from 2.8% to 5.9%. Predicted risks for a 66-year old ranged from 2.6% to 25.3%. Personalized predicted risks across ages 30-85 were presented in an online calculator (https://hjerteforeningen.shinyapps.io/cvd-risk-manuscript/).

Conclusion: A CVD risk prediction model based solely on nationwide administrative registry data provided accurate prediction of personal and population-level 5-year first CVD event risk in the Danish population. This may inform clinical and public health primary prevention efforts.

Original languageEnglish
Article numberoeab015
JournalEuropean heart journal open
Volume1
Issue number2
Pages (from-to)oeab015
ISSN2752-4191
DOIs
Publication statusPublished - Sept 2021

Keywords

  • Cardiovascular disease
  • Nationwide
  • Primary prevention
  • Registries
  • Risk prediction
  • Risk stratification

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