Systematic examination of a heart failure risk prediction tool: The pooled cohort equations to prevent heart failure

Identification of individuals at risk for heart failure is needed to deliver targeted preventive strategies and maximize net benefit of interventions. To examine the clinical utility of the recently published heart failure-specific risk prediction model, the Pooled Cohort Equations to Prevent Heart Failure, we sought to demonstrate the range of risk values associated with diverse risk factor combinations in White and Black men and women. We varied individual risk factors while holding the other risk factors constant at age-adjusted national mean values for risk factors in each race-sex and age group. We also examined multiple combinations of risk factor levels and examined the range of predicted 10-year heart failure risk using the Pooled Cohort Equations to Prevent Heart Failure risk tool. Ten-year predicted heart failure risk varied widely for each race-sex group across a range of ages and risk factor scenarios. For example, predicted 10-year heart failure risk in a hypothetical 40 year old varied from 0.1% to 9.7% in a White man, 0.5% to 12.3% in a Black man, <0.1% to 9.3% in a White woman, and 0.2% to 28.0% in a Black woman. Higher risk factor burden (e.g. diabetes and hypertension requiring treatment) consistently drove higher risk estimates in all race-sex groups and across all ages. Our analysis highlights the importance of a race and sex-specific multivariable risk prediction model for heart failure to personalize the clinician-patient discussion, inform future practice guidelines, and provide a framework for future risk-based prevention trials for heart failure.