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Developing cardiovascular risk prediction models for Australia

Mark R Nelson and Mark Woodward
Med J Aust 2019; 210 (4): . || doi: 10.5694/mja2.50010
Published online: 4 March 2019

Risk stratification is the best strategy for deciding who needs medication for primary prevention of cardiovascular events

An absolute risk approach to managing cardiovascular disease (CVD) risk factors is superior to managing individual risk factors, and has been endorsed by peak professional bodies and in CVD management guidelines.1 However, clinicians need to be confident about the robustness of the risk estimates if they are to act upon them. Ideally, a CVD risk score model for patients in Australia should be based upon a large Australian cohort study including information on all relevant risk factors and a sufficient number of CVD outcomes.2 As this is not available, one applies an algorithm based on other data, such as those of the American Framingham Heart Study; the Australian Risk Calculator (https://www.cvdcheck.org.au), a recalibration of a Framingham algorithm, is currently the recommended tool. In the study published in this issue of the MJA, Albarqouni and colleagues3 compared four algorithms derived wholly or partially from Framingham data, including the 2013 Pooled Cohort Risk Equation (PCE‐ASCVD), an algorithm based on data for four American cohorts, including the Framingham study. The authors did not include the 1976 Framingham‐based algorithm in their assessment.4 The New Zealand prediction equations5 could also have been assessed as a contemporary algorithm.

  • Mark R Nelson1
  • Mark Woodward2,3

  • 1 University of Tasmania, Hobart, TAS
  • 2 The George Institute for Global Health, University of New South Wales, Sydney, NSW
  • 3 The George Institute for Global Health, University of Oxford, Oxford, United Kingdom

Correspondence: Mark.Nelson@utas.edu.au

Competing interests:

No relevant disclosures.

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