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Multiple biomarkers for the prediction of first major cardiovascular events and death
Thomas J Wang1, Philimon Gona, Martin G Larson
1Framingham Heart Study, Framingham, MA, USA. tjwang@partners.org
Insights
This study found that while multiple biomarkers can predict cardiovascular events, they offer only a moderate improvement over standard risk factors for individual risk assessment.
Area of Science:
- Cardiovascular disease research
- Biomarker discovery
- Risk prediction modeling
Background:
- Limited research on combined biomarker utility for cardiovascular event risk.
- Need for evaluating distinct biologic pathways in risk prediction.
Purpose of the Study:
- To assess the incremental value of 10 biomarkers in predicting cardiovascular events.
- To determine the predictive power of individual and combined biomarkers beyond conventional risk factors.
Main Methods:
- Measured 10 biomarkers (e.g., C-reactive protein, BNP, hs-cTnT, hs-cTnI, NT-proBNP, aldosterone, renin, fibrinogen, D-dimer, PAI-1, homocysteine, UACR) in 3209 Framingham Heart Study participants.
- Utilized Cox proportional-hazards models adjusting for traditional cardiovascular risk factors.
- Developed multimarker scores based on significant biomarkers.
Main Results:
- B-type natriuretic peptide, C-reactive protein, urinary albumin-to-creatinine ratio, homocysteine, and renin were significant predictors of mortality.
- B-type natriuretic peptide and urinary albumin-to-creatinine ratio were strongest predictors of major cardiovascular events.
- Highest quintile of multimarker scores showed significantly elevated risks for death and cardiovascular events compared to the lowest two quintiles.
Conclusions:
- The 10 contemporary biomarkers studied offer only a moderate improvement in risk classification when added to standard risk factors.
- Multimarker scores enhance risk prediction but with limited incremental benefit for individual assessment.
Background:
Few investigations have evaluated the incremental usefulness of multiple biomarkers from distinct biologic pathways for predicting the risk of cardiovascular events.
Methods:
We measured 10 biomarkers in 3209 participants attending a routine examination cycle of the Framingham Heart Study: the levels of C-reactive protein, B-type natriuretic peptide, N-terminal pro-atrial natriuretic peptide, aldosterone, renin, fibrinogen, D-dimer, plasminogen-activator inhibitor type 1, and homocysteine; and the urinary albumin-to-creatinine ratio.
Results:
During follow-up (median, 7.4 years), 207 participants died and 169 had a first major cardiovascular event. In Cox proportional-hazards models adjusting for conventional risk factors, the following biomarkers most strongly predicted the risk of death (each biomarker is followed by the adjusted hazard ratio per 1 SD increment in the log values): B-type natriuretic peptide level (1.40), C-reactive protein level (1.39), the urinary albumin-to-creatinine ratio (1.22), homocysteine level (1.20), and renin level (1.17). The biomarkers that most strongly predicted major cardiovascular events were B-type natriuretic peptide level (adjusted hazard ratio, 1.25 per 1 SD increment in the log values) and the urinary albumin-to-creatinine ratio (1.20). Persons with "multimarker" scores (based on regression coefficients of significant biomarkers) in the highest quintile as compared with those with scores in the lowest two quintiles had elevated risks of death (adjusted hazard ratio, 4.08; P<0.001) and major cardiovascular events (adjusted hazard ratio, 1.84; P=0.02). However, the addition of multimarker scores to conventional risk factors resulted in only small increases in the ability to classify risk, as measured by the C statistic.
Conclusions:
For assessing risk in individual persons, the use of the 10 contemporary biomarkers that we studied adds only moderately to standard risk factors.
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