Short-Term Global Cardiovascular Disease Risk Prediction in Older Adults
Current prevention guidelines recommend using the Pooled Cohort Equation (PCE) for 10-year atherosclerotic cardiovascular disease (CVD) risk assessment. However, the PCE has serious limitations in older adults: it excludes heart failure (HF) hospitalization, estimates 10-year risk, which may not be...
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| Vydáno v: | Journal of the American College of Cardiology Ročník 71; číslo 22; s. 2527 |
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| Médium: | Journal Article |
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United States
05.06.2018
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| ISSN: | 1558-3597, 1558-3597 |
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| Abstract | Current prevention guidelines recommend using the Pooled Cohort Equation (PCE) for 10-year atherosclerotic cardiovascular disease (CVD) risk assessment. However, the PCE has serious limitations in older adults: it excludes heart failure (HF) hospitalization, estimates 10-year risk, which may not be the most relevant time frame, and is not indicated for individuals age >79 years.
This study sought to determine whether adding biomarkers to PCE variables improves global CVD (coronary heart disease, stroke, and HF) risk prediction in older adults over a shorter time period.
Atherosclerosis Risk in Communities study participants without prevalent CVD including HF (n = 4,760; age 75.4 ± 5.1 years) were followed for incident global CVD events. Adding N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponin T, and high-sensitivity C-reactive protein to the PCE and a "lab model" with the biomarkers, age, race, and gender were assessed for prediction improvement. Area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI) were calculated.
Over median follow-up of ∼4 years, incident HF was the leading CVD event (n = 193 vs. 118 coronary heart disease and 81 stroke events). Compared to the PCE, each biomarker improved risk prediction. The largest improvement in risk prediction metrics was with the addition of all 3 biomarkers (ΔAUC 0.103; continuous NRI 0.484). The lab model also performed better than the PCE model (ΔAUC 0.091, continuous NRI 0.355).
Adding biomarkers to the PCE or a simpler "lab model" improves short-term global CVD risk prediction and may be useful to inform short-term preventive strategies in older adults. |
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| AbstractList | Current prevention guidelines recommend using the Pooled Cohort Equation (PCE) for 10-year atherosclerotic cardiovascular disease (CVD) risk assessment. However, the PCE has serious limitations in older adults: it excludes heart failure (HF) hospitalization, estimates 10-year risk, which may not be the most relevant time frame, and is not indicated for individuals age >79 years.BACKGROUNDCurrent prevention guidelines recommend using the Pooled Cohort Equation (PCE) for 10-year atherosclerotic cardiovascular disease (CVD) risk assessment. However, the PCE has serious limitations in older adults: it excludes heart failure (HF) hospitalization, estimates 10-year risk, which may not be the most relevant time frame, and is not indicated for individuals age >79 years.This study sought to determine whether adding biomarkers to PCE variables improves global CVD (coronary heart disease, stroke, and HF) risk prediction in older adults over a shorter time period.OBJECTIVESThis study sought to determine whether adding biomarkers to PCE variables improves global CVD (coronary heart disease, stroke, and HF) risk prediction in older adults over a shorter time period.Atherosclerosis Risk in Communities study participants without prevalent CVD including HF (n = 4,760; age 75.4 ± 5.1 years) were followed for incident global CVD events. Adding N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponin T, and high-sensitivity C-reactive protein to the PCE and a "lab model" with the biomarkers, age, race, and gender were assessed for prediction improvement. Area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI) were calculated.METHODSAtherosclerosis Risk in Communities study participants without prevalent CVD including HF (n = 4,760; age 75.4 ± 5.1 years) were followed for incident global CVD events. Adding N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponin T, and high-sensitivity C-reactive protein to the PCE and a "lab model" with the biomarkers, age, race, and gender were assessed for prediction improvement. Area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI) were calculated.Over median follow-up of ∼4 years, incident HF was the leading CVD event (n = 193 vs. 118 coronary heart disease and 81 stroke events). Compared to the PCE, each biomarker improved risk prediction. The largest improvement in risk prediction metrics was with the addition of all 3 biomarkers (ΔAUC 0.103; continuous NRI 0.484). The lab model also performed better than the PCE model (ΔAUC 0.091, continuous NRI 0.355).RESULTSOver median follow-up of ∼4 years, incident HF was the leading CVD event (n = 193 vs. 118 coronary heart disease and 81 stroke events). Compared to the PCE, each biomarker improved risk prediction. The largest improvement in risk prediction metrics was with the addition of all 3 biomarkers (ΔAUC 0.103; continuous NRI 0.484). The lab model also performed better than the PCE model (ΔAUC 0.091, continuous NRI 0.355).Adding biomarkers to the PCE or a simpler "lab model" improves short-term global CVD risk prediction and may be useful to inform short-term preventive strategies in older adults.CONCLUSIONSAdding biomarkers to the PCE or a simpler "lab model" improves short-term global CVD risk prediction and may be useful to inform short-term preventive strategies in older adults. Current prevention guidelines recommend using the Pooled Cohort Equation (PCE) for 10-year atherosclerotic cardiovascular disease (CVD) risk assessment. However, the PCE has serious limitations in older adults: it excludes heart failure (HF) hospitalization, estimates 10-year risk, which may not be the most relevant time frame, and is not indicated for individuals age >79 years. This study sought to determine whether adding biomarkers to PCE variables improves global CVD (coronary heart disease, stroke, and HF) risk prediction in older adults over a shorter time period. Atherosclerosis Risk in Communities study participants without prevalent CVD including HF (n = 4,760; age 75.4 ± 5.1 years) were followed for incident global CVD events. Adding N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponin T, and high-sensitivity C-reactive protein to the PCE and a "lab model" with the biomarkers, age, race, and gender were assessed for prediction improvement. Area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI) were calculated. Over median follow-up of ∼4 years, incident HF was the leading CVD event (n = 193 vs. 118 coronary heart disease and 81 stroke events). Compared to the PCE, each biomarker improved risk prediction. The largest improvement in risk prediction metrics was with the addition of all 3 biomarkers (ΔAUC 0.103; continuous NRI 0.484). The lab model also performed better than the PCE model (ΔAUC 0.091, continuous NRI 0.355). Adding biomarkers to the PCE or a simpler "lab model" improves short-term global CVD risk prediction and may be useful to inform short-term preventive strategies in older adults. |
| Author | Deswal, Anita Hoogeveen, Ron Selvin, Elizabeth Coresh, Josef de Lemos, James A Nambi, Vijay Wagenknecht, Lynne E Ballantyne, Christie M Virani, Salim S Taffet, George E Saeed, Anum Sun, Wensheng Matsushita, Kunihiro |
| Author_xml | – sequence: 1 givenname: Anum surname: Saeed fullname: Saeed, Anum organization: Baylor College of Medicine, Houston, Texas – sequence: 2 givenname: Vijay surname: Nambi fullname: Nambi, Vijay organization: Baylor College of Medicine, Houston, Texas; Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas – sequence: 3 givenname: Wensheng surname: Sun fullname: Sun, Wensheng organization: Baylor College of Medicine, Houston, Texas – sequence: 4 givenname: Salim S surname: Virani fullname: Virani, Salim S organization: Baylor College of Medicine, Houston, Texas; Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas – sequence: 5 givenname: George E surname: Taffet fullname: Taffet, George E organization: Baylor College of Medicine, Houston, Texas – sequence: 6 givenname: Anita surname: Deswal fullname: Deswal, Anita organization: Baylor College of Medicine, Houston, Texas – sequence: 7 givenname: Elizabeth surname: Selvin fullname: Selvin, Elizabeth organization: Johns Hopkins University, Baltimore, Maryland – sequence: 8 givenname: Kunihiro surname: Matsushita fullname: Matsushita, Kunihiro organization: Johns Hopkins University, Baltimore, Maryland – sequence: 9 givenname: Lynne E surname: Wagenknecht fullname: Wagenknecht, Lynne E organization: Wake Forest University, Winston-Salem, North Carolina – sequence: 10 givenname: Ron surname: Hoogeveen fullname: Hoogeveen, Ron organization: Baylor College of Medicine, Houston, Texas – sequence: 11 givenname: Josef surname: Coresh fullname: Coresh, Josef organization: Johns Hopkins University, Baltimore, Maryland – sequence: 12 givenname: James A surname: de Lemos fullname: de Lemos, James A organization: University of Texas-Southwestern Medical Center, Dallas, Texas – sequence: 13 givenname: Christie M surname: Ballantyne fullname: Ballantyne, Christie M email: cmb@bcm.edu organization: Baylor College of Medicine, Houston, Texas. Electronic address: cmb@bcm.edu |
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| Title | Short-Term Global Cardiovascular Disease Risk Prediction in Older Adults |
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