Calibration of the Pooled Cohort Equations for Atherosclerotic Cardiovascular Disease: An Update

Nancy R Cook1, Paul M Ridker1

  • 1From Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Insights

New cardiovascular disease risk calculators (PCEs) from 2013 guidelines overestimated actual risk in validation studies. Recalibration may be needed for accurate clinical practice.

Area of Science:

  • Cardiology
  • Public Health
  • Epidemiology

Background:

  • The 2013 American College of Cardiology/American Heart Association guidelines updated cholesterol management recommendations.
  • These guidelines introduced new Pooled Cohort Equations (PCEs) to estimate atherosclerotic cardiovascular disease (ASCVD) risk, including coronary heart disease and stroke.
  • The previous Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) served as a prior standard.

Purpose of the Study:

  • To review and analyze external validation studies of the 2013 PCEs.
  • To identify discrepancies between predicted and observed ASCVD risks.
  • To discuss potential reasons for these discrepancies and inform future recalibration efforts.

Main Methods:

  • A narrative review of published reports evaluating the PCEs.
  • Analysis of 15 external validation studies from the US and Europe.
  • Assessment of study methodologies, cohort characteristics, and reported outcomes.

Main Results:

  • The PCEs overestimated observed ASCVD risk in almost all external validation cohorts.
  • Validation cohorts often used more contemporary populations than the guideline development cohorts.
  • Significant discrepancies were noted between predicted and actual cardiovascular event rates.

Conclusions:

  • The PCEs require recalibration to improve accuracy in current clinical practice.
  • Understanding the limitations of validation studies is crucial for interpreting PCE performance.
  • Accurate risk prediction is essential for effective cardiovascular disease prevention strategies.

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