Prediction of individual lifetime cardiovascular risk and potential treatment benefit: development and recalibration of the LIFE-CVD2 model to four European risk regions

Eur J Prev Cardiol. 2024 Oct 10;31(14):1690-1699. doi: 10.1093/eurjpc/zwae174.

Abstract

Aims: The 2021 European Society of Cardiology prevention guidelines recommend the use of (lifetime) risk prediction models to aid decisions regarding initiation of prevention. We aimed to update and systematically recalibrate the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model to four European risk regions for the estimation of lifetime CVD risk for apparently healthy individuals.

Methods and results: The updated LIFE-CVD (i.e. LIFE-CVD2) models were derived using individual participant data from 44 cohorts in 13 countries (687 135 individuals without established CVD, 30 939 CVD events in median 10.7 years of follow-up). LIFE-CVD2 uses sex-specific functions to estimate the lifetime risk of fatal and non-fatal CVD events with adjustment for the competing risk of non-CVD death and is systematically recalibrated to four distinct European risk regions. The updated models showed good discrimination in external validation among 1 657 707 individuals (61 311 CVD events) from eight additional European cohorts in seven countries, with a pooled C-index of 0.795 (95% confidence interval 0.767-0.822). Predicted and observed CVD event risks were well calibrated in population-wide electronic health records data in the UK (Clinical Practice Research Datalink) and the Netherlands (Extramural LUMC Academic Network). When using LIFE-CVD2 to estimate potential gain in CVD-free life expectancy from preventive therapy, projections varied by risk region reflecting important regional differences in absolute lifetime risk. For example, a 50-year-old smoking woman with a systolic blood pressure (SBP) of 140 mmHg was estimated to gain 0.9 years in the low-risk region vs. 1.6 years in the very high-risk region from lifelong 10 mmHg SBP reduction. The benefit of smoking cessation for this individual ranged from 3.6 years in the low-risk region to 4.8 years in the very high-risk region.

Conclusion: By taking into account geographical differences in CVD incidence using contemporary representative data sources, the recalibrated LIFE-CVD2 model provides a more accurate tool for the prediction of lifetime risk and CVD-free life expectancy for individuals without previous CVD, facilitating shared decision-making for cardiovascular prevention as recommended by 2021 European guidelines.

Keywords: Cardiovascular disease; Lifetime; Prevention; Primary prevention; Risk prediction.

Plain language summary

The study introduces LIFE-CVD2, a new tool that helps predict the risk of heart disease over a person’s lifetime, and highlights how where you live in Europe can affect this risk.Using health information from over 687 000 people, LIFE-CVD2 looks at things like blood pressure and whether someone smokes to figure out their chance of having heart problems later in life. Health information from another 1.6 million people in seven different European countries was used to show that it did a good job of predicting who might develop heart disease.Knowing your heart disease risk over your whole life helps doctors give you the best advice to keep your heart healthy. Let us say there is a 50-year-old woman who smokes and has a bit high blood pressure. Right now, she might not look like she is in danger. But with the LIFE-CVD2 tool, doctors can show her how making changes today, like lowering her blood pressure or stopping smoking, could mean many more years without heart problems. These healthy changes can make a big difference over many years.

Publication types

  • Multicenter Study

MeSH terms

  • Adult
  • Aged
  • Cardiovascular Diseases* / epidemiology
  • Cardiovascular Diseases* / prevention & control
  • Decision Support Techniques
  • Europe / epidemiology
  • Female
  • Heart Disease Risk Factors*
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • Risk Assessment
  • Risk Factors
  • Time Factors