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TOPLINE:
A universal cardiovascular disease (CVD) prediction tool performs well in patients with and without atherosclerotic CVD (ASCVD), a new study showed, suggesting this model could facilitate transition from primary to secondary prevention by streamlining risk classification.
METHODOLOGY:
- Researchers used different models to evaluate whether established CVD predictors, including age, sex, race, diabetes, systolic blood pressure, or smoking, are associated with major adverse cardiovascular events (MACEs), including myocardial infarction (MI), stroke, and heart failure (HF), among 9138 patients, mean age 63.8 years, in the Atherosclerosis Risk in Communities (ARIC) study.
- Of these, 609 had ASCVD (history of MI, ischemic stroke, or symptomatic peripheral artery disease) and 8529 did not.
- They extended their exploration to other predictors available in clinical practice, including family history of premature ASCVD, high-sensitivity C-reactive protein, lipoprotein(a), triglycerides, and apolipoprotein B, as well as predictors of HF such as body mass index and heart rate and blood-based cardiac biomarkers.
- An external validation analysis included 5322 participants in the Multi-Ethnic Study of Atherosclerosis (MESA).
- Over a median follow-up of 18.9 years, 3209 ARIC participants (35%) developed MACE for an incidence rate per 1000 person-years of 21.3 for MACE, 12.6 for MI/stroke, and 13.8 for HF.
TAKEAWAY:
- Of all candidate predictors, 10 variables (including established predictors and cardiac biomarkers) were included in the universal prediction model, which demonstrated good calibration in both those with ASCVD (hazard ratio [HR] C-statistic, 0.692; 95% CI, 0.650-0.735) and without ASCVD (HR C-statistic, 0.748; 95% CI, 0.726-0.770).
- As anticipated, the risk for MACE was generally lower in those with no prior ASCVD, but the 5-year risk in the highest quintile of predicted risk in those without ASCVD was higher than that in the lowest two quintiles of the ASCVD group.
- The universal risk prediction model was validated in the MESA community–based cohort; over a median follow-up of 13.7 years, 12% of participants with and without prior ASCVD developed MACE for an incidence rate per 1000 person-years of 10.2 for MACE, 7.4 for MI/stroke, and 4.3 for HF.
- The results were generally similar when examining individual outcomes (MI/stroke and HF) and for both no ASCVD and ASCVD groups across demographic subgroups by age, sex, and race.
IN PRACTICE:
The findings “support the importance of established predictors for classifying long-term CVD risk in both primary and secondary prevention settings,” the authors wrote, adding an advantage to this risk prediction approach could be to help providers and patients “further personalize secondary prevention.”
In an accompanying editorial, Pier Sergio Saba, MD, PhD, Clinical and Interventional Cardiology, Sassari University Hospital, Sassari, Italy, and others said the universal risk assessment approach “is conceptually promising” but noted patients with ASCVD represented only 7% of the study population, and this population was relatively young, potentially limiting the applicability of this risk model in older individuals. Before the risk model can be used in clinical settings, results need to be validated and given incorporation of cardiac biomarkers, “careful cost-benefit analyses may also be needed,” the editorial writers added.
SOURCE:
The study was conducted by Yejin Mok, PHD, MPH, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, and colleagues. It was published online on January 29, 2024, in the Journal of the American College of Cardiology (JACC).
LIMITATIONS:
The somewhat limited number of study participants with prior ASCVD precluded researchers from quantifying the prognostic impact of ASCVD subtypes (eg, history of MI vs stroke vs peripheral artery disease). The study didn’t have data on some predictors recognized in guidelines (eg, coronary artery calcium and left ventricular ejection fraction). The ARIC analysis included only Black and White participants, and although models were validated in MESA, which included Chinese and Hispanic adults, extrapolation of results to more racially/ethnically diverse populations should be done with care.
DISCLOSURES:
The ARIC study received funding from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health, and Department of Health and Human Services. The MESA study was supported by the NHLBI and National Center for Advancing Translational Sciences. The study authors and editorial writers had no relevant conflicts of interest.
A version of this article first appeared on Medscape.com.
TOPLINE:
A universal cardiovascular disease (CVD) prediction tool performs well in patients with and without atherosclerotic CVD (ASCVD), a new study showed, suggesting this model could facilitate transition from primary to secondary prevention by streamlining risk classification.
METHODOLOGY:
- Researchers used different models to evaluate whether established CVD predictors, including age, sex, race, diabetes, systolic blood pressure, or smoking, are associated with major adverse cardiovascular events (MACEs), including myocardial infarction (MI), stroke, and heart failure (HF), among 9138 patients, mean age 63.8 years, in the Atherosclerosis Risk in Communities (ARIC) study.
- Of these, 609 had ASCVD (history of MI, ischemic stroke, or symptomatic peripheral artery disease) and 8529 did not.
- They extended their exploration to other predictors available in clinical practice, including family history of premature ASCVD, high-sensitivity C-reactive protein, lipoprotein(a), triglycerides, and apolipoprotein B, as well as predictors of HF such as body mass index and heart rate and blood-based cardiac biomarkers.
- An external validation analysis included 5322 participants in the Multi-Ethnic Study of Atherosclerosis (MESA).
- Over a median follow-up of 18.9 years, 3209 ARIC participants (35%) developed MACE for an incidence rate per 1000 person-years of 21.3 for MACE, 12.6 for MI/stroke, and 13.8 for HF.
TAKEAWAY:
- Of all candidate predictors, 10 variables (including established predictors and cardiac biomarkers) were included in the universal prediction model, which demonstrated good calibration in both those with ASCVD (hazard ratio [HR] C-statistic, 0.692; 95% CI, 0.650-0.735) and without ASCVD (HR C-statistic, 0.748; 95% CI, 0.726-0.770).
- As anticipated, the risk for MACE was generally lower in those with no prior ASCVD, but the 5-year risk in the highest quintile of predicted risk in those without ASCVD was higher than that in the lowest two quintiles of the ASCVD group.
- The universal risk prediction model was validated in the MESA community–based cohort; over a median follow-up of 13.7 years, 12% of participants with and without prior ASCVD developed MACE for an incidence rate per 1000 person-years of 10.2 for MACE, 7.4 for MI/stroke, and 4.3 for HF.
- The results were generally similar when examining individual outcomes (MI/stroke and HF) and for both no ASCVD and ASCVD groups across demographic subgroups by age, sex, and race.
IN PRACTICE:
The findings “support the importance of established predictors for classifying long-term CVD risk in both primary and secondary prevention settings,” the authors wrote, adding an advantage to this risk prediction approach could be to help providers and patients “further personalize secondary prevention.”
In an accompanying editorial, Pier Sergio Saba, MD, PhD, Clinical and Interventional Cardiology, Sassari University Hospital, Sassari, Italy, and others said the universal risk assessment approach “is conceptually promising” but noted patients with ASCVD represented only 7% of the study population, and this population was relatively young, potentially limiting the applicability of this risk model in older individuals. Before the risk model can be used in clinical settings, results need to be validated and given incorporation of cardiac biomarkers, “careful cost-benefit analyses may also be needed,” the editorial writers added.
SOURCE:
The study was conducted by Yejin Mok, PHD, MPH, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, and colleagues. It was published online on January 29, 2024, in the Journal of the American College of Cardiology (JACC).
LIMITATIONS:
The somewhat limited number of study participants with prior ASCVD precluded researchers from quantifying the prognostic impact of ASCVD subtypes (eg, history of MI vs stroke vs peripheral artery disease). The study didn’t have data on some predictors recognized in guidelines (eg, coronary artery calcium and left ventricular ejection fraction). The ARIC analysis included only Black and White participants, and although models were validated in MESA, which included Chinese and Hispanic adults, extrapolation of results to more racially/ethnically diverse populations should be done with care.
DISCLOSURES:
The ARIC study received funding from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health, and Department of Health and Human Services. The MESA study was supported by the NHLBI and National Center for Advancing Translational Sciences. The study authors and editorial writers had no relevant conflicts of interest.
A version of this article first appeared on Medscape.com.
TOPLINE:
A universal cardiovascular disease (CVD) prediction tool performs well in patients with and without atherosclerotic CVD (ASCVD), a new study showed, suggesting this model could facilitate transition from primary to secondary prevention by streamlining risk classification.
METHODOLOGY:
- Researchers used different models to evaluate whether established CVD predictors, including age, sex, race, diabetes, systolic blood pressure, or smoking, are associated with major adverse cardiovascular events (MACEs), including myocardial infarction (MI), stroke, and heart failure (HF), among 9138 patients, mean age 63.8 years, in the Atherosclerosis Risk in Communities (ARIC) study.
- Of these, 609 had ASCVD (history of MI, ischemic stroke, or symptomatic peripheral artery disease) and 8529 did not.
- They extended their exploration to other predictors available in clinical practice, including family history of premature ASCVD, high-sensitivity C-reactive protein, lipoprotein(a), triglycerides, and apolipoprotein B, as well as predictors of HF such as body mass index and heart rate and blood-based cardiac biomarkers.
- An external validation analysis included 5322 participants in the Multi-Ethnic Study of Atherosclerosis (MESA).
- Over a median follow-up of 18.9 years, 3209 ARIC participants (35%) developed MACE for an incidence rate per 1000 person-years of 21.3 for MACE, 12.6 for MI/stroke, and 13.8 for HF.
TAKEAWAY:
- Of all candidate predictors, 10 variables (including established predictors and cardiac biomarkers) were included in the universal prediction model, which demonstrated good calibration in both those with ASCVD (hazard ratio [HR] C-statistic, 0.692; 95% CI, 0.650-0.735) and without ASCVD (HR C-statistic, 0.748; 95% CI, 0.726-0.770).
- As anticipated, the risk for MACE was generally lower in those with no prior ASCVD, but the 5-year risk in the highest quintile of predicted risk in those without ASCVD was higher than that in the lowest two quintiles of the ASCVD group.
- The universal risk prediction model was validated in the MESA community–based cohort; over a median follow-up of 13.7 years, 12% of participants with and without prior ASCVD developed MACE for an incidence rate per 1000 person-years of 10.2 for MACE, 7.4 for MI/stroke, and 4.3 for HF.
- The results were generally similar when examining individual outcomes (MI/stroke and HF) and for both no ASCVD and ASCVD groups across demographic subgroups by age, sex, and race.
IN PRACTICE:
The findings “support the importance of established predictors for classifying long-term CVD risk in both primary and secondary prevention settings,” the authors wrote, adding an advantage to this risk prediction approach could be to help providers and patients “further personalize secondary prevention.”
In an accompanying editorial, Pier Sergio Saba, MD, PhD, Clinical and Interventional Cardiology, Sassari University Hospital, Sassari, Italy, and others said the universal risk assessment approach “is conceptually promising” but noted patients with ASCVD represented only 7% of the study population, and this population was relatively young, potentially limiting the applicability of this risk model in older individuals. Before the risk model can be used in clinical settings, results need to be validated and given incorporation of cardiac biomarkers, “careful cost-benefit analyses may also be needed,” the editorial writers added.
SOURCE:
The study was conducted by Yejin Mok, PHD, MPH, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, and colleagues. It was published online on January 29, 2024, in the Journal of the American College of Cardiology (JACC).
LIMITATIONS:
The somewhat limited number of study participants with prior ASCVD precluded researchers from quantifying the prognostic impact of ASCVD subtypes (eg, history of MI vs stroke vs peripheral artery disease). The study didn’t have data on some predictors recognized in guidelines (eg, coronary artery calcium and left ventricular ejection fraction). The ARIC analysis included only Black and White participants, and although models were validated in MESA, which included Chinese and Hispanic adults, extrapolation of results to more racially/ethnically diverse populations should be done with care.
DISCLOSURES:
The ARIC study received funding from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health, and Department of Health and Human Services. The MESA study was supported by the NHLBI and National Center for Advancing Translational Sciences. The study authors and editorial writers had no relevant conflicts of interest.
A version of this article first appeared on Medscape.com.