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SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  • Steven Hageman
  • Lisa Pennells
  • Francisco Ojeda
  • Stephen Kaptoge
  • Kari Kuulasmaa
  • Tamar de Vries
  • Zhe Xu
  • Frank Kee
  • Ryan Chung
  • Angela Wood
  • John William McEvoy
  • Giovanni Veronesi
  • Thomas Bolton
  • Paul Dendale
  • Brian A. Ference
  • Martin Halle
  • Adam Timmis
  • Panos Vardas
  • John Danesh
  • Ian Graham
  • Veikko Salomaa
  • Frank Visseren
  • Dirk De Bacquer
  • Stefan Blankenberg
  • Jannick Dorresteijn
  • Emanuele Di Angelantonio
  • Stephan Achenbach
  • Krasimira Aleksandrova
  • Pilar Amiano
  • Philippe Amouyel
  • Jonas Andersson
  • Stephan J. L. Bakker
  • Rui Bebiano Da Providencia Costa
  • Joline W. J. Beulens
  • Michael Blaha
  • Martin Bobak
  • Jolanda M. A. Boer
  • Catalina Bonet
  • Fabrice Bonnet
  • Marie-Christine Boutron-Ruault
  • Tonje Braaten
  • Hermann Brenner
  • Fabian Brunner
  • Eric J. Brunner
  • Mattias Brunstrom
  • Torben Jørgensen
  • Linneberg, Allan René
  • Kim Overvad
  • Tjønneland, Anne
  • Tybjærg-Hansen, Anne
  • SCORE2 Working Grp
  • ESC Cardiovasc Risk Collaboration

Aims The aim of this study was to develop, validate, and illustrate an updated prediction model (SCORE2) to estimate 10-year fatal and non-fatal cardiovascular disease (CVD) risk in individuals without previous CVD or diabetes aged 40-69 years in Europe.

Methods and results We derived risk prediction models using individual-participant data from 45 cohorts in 13 countries (677 684 individuals, 30 121 CVD events). We used sex-specific and competing risk-adjusted models, including age, smoking status, systolic blood pressure, and total- and HDL-cholesterol. We defined four risk regions in Europe according to country-specific CVD mortality, recalibrating models to each region using expected incidences and risk factor distributions. Region-specific incidence was estimated using CVD mortality and incidence data on 10 776 466 individuals. For external validation, we analysed data from 25 additional cohorts in 15 European countries (1 133 181 individuals, 43 492 CVD events). After applying the derived risk prediction models to external validation cohorts, C-indices ranged from 0.67 (0.65-0.68) to 0.81 (0.76-0.86). Predicted CVD risk varied several-fold across European regions. For example, the estimated 10-year CVD risk for a 50-year-old smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/L, and HDL-cholesterol of 1.3 mmol/L, ranged from 5.9% for men in low- risk countries to 14.0% for men in very high-risk countries, and from 4.2% for women in low-risk countries to 13.7% for women in very high-risk countries.

Conclusion SCORE2-a new algorithm derived, calibrated, and validated to predict 10-year risk of first-onset CVD in European populations-enhances the identification of individuals at higher risk of developing CVD across Europe.

OriginalsprogEngelsk
TidsskriftEuropean Heart Journal
Vol/bind42
Udgave nummer25
Sider (fra-til)2439-2454
Antal sider16
ISSN0195-668X
DOI
StatusUdgivet - 2021

ID: 275058395