Cardiovascular disease risk prediction equations in 400000 primary care patients in New Zealand: a derivation and

Romana Pylypchuk1, Sue Wells1, Andrew Kerr2

  • 1School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.

PubMed

Insights

New cardiovascular disease risk equations developed in New Zealand outperform US guidelines. These updated models better account for socioeconomic and ethnic diversity, improving risk prediction for contemporary primary care patients.

Area of Science:

  • Cardiovascular Disease Epidemiology
  • Health Services Research
  • Biostatistics

Background:

  • Current cardiovascular disease (CVD) risk prediction equations often use outdated cohorts with limited socioeconomic and ethnic diversity.
  • Contemporary primary care populations differ significantly from historical cohorts used for risk equation development.

Purpose of the Study:

  • To develop and validate new CVD risk prediction equations using a nationally representative New Zealand cohort.
  • To compare the performance of these new equations against established US-recommended equations (Pooled Cohort Equations - PCEs).

Main Methods:

  • A prospective cohort of 401,752 New Zealand primary care patients (aged 30-74, no prior CVD) was established.
  • New Cox regression models incorporated clinical predictors, socioeconomic deprivation, and self-identified ethnicity.
  • Calibration and discrimination were assessed and compared with 2013 PCEs.

Main Results:

  • New PREDICT equations showed significantly better performance than PCEs across all metrics.
  • PCEs overestimated hard atherosclerotic CVD risk by ~40% (men) and ~60% (women).
  • Socioeconomic deprivation and ethnicity were independent predictors, with higher risk in Māori, Pacific, and Indian populations.

Conclusions:

  • New Zealand-specific CVD risk equations are more relevant for contemporary primary care populations.
  • Existing equations like PCEs may overestimate risk in the general population but underestimate it in vulnerable subgroups.
  • Incorporating socioeconomic and ethnic factors is crucial for accurate CVD risk assessment and equitable care.
Abstract

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