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Biomarkers add little to cardiovascular risk prediction
1 July 2009
MedWire News: Biomarkers are of limited value in cardiovascular risk prediction, researchers claim.
“Use of multiple biomarkers minimally improved the accuracy of risk prediction models over and above conventional cardiovascular risk factors and did not reclassify a substantial proportion of individuals to higher or lower risk categories,” they report in the Journal of the American Medical Association.
The team, led by Olle Melander (Lund University, Malmö, Sweden), used novel statistical measures designed specifically to evaluate risk prediction models to assess the ability of a range of cardiovascular disease biomarkers to accurately predict risk, both individually and in combination, in 5067 individuals enrolled in a population-based study (the Malmö Diet and Cancer study).
Participants’ levels of the “older” biomarkers C-reactive protein (CRP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP), as well as the more recently identified biomarkers cystatin C, lipoprotein-associated phospholipase-2 (Lp-PLA2), midregional proadrenomedullin (MR-proADM), and midregional proatrial natriuretic peptide (MR-proANP), were measured at the beginning of the study in 1991-1994.
Over a median follow-up of 12.8 years, there were 418 cardiovascular events and 230 coronary events.
Individually, five of the six biomarkers (all except Lp-PLA2) proved significant predictors of future cardiovascular events, as did three (cystatin C, MR-proADM, and NT-proBNP) of coronary events, Melander and co-workers report.
Risk prediction models including conventional risk factors had a C statistic of 0.758 for cardiovascular and 0.760 for coronary events.
In backward elimination models, CRP and NT-proBNP were retained for predicting cardiovascular events, and MR-proADM and NT-proBNP for coronary event prediction, and adding these biomarkers to the respective risk models improved the C statistic by 0.007 (p=0.04) and 0.009 (p=0.08).
More importantly, according to the authors, only 7.5% of patients overall would be reclassified using the additional biomarkers for prediction of cardiovascular events, and 5% for coronary events.
And although the biomarkers resulted in significant reclassification improvement in analyses restricted to intermediate-risk patients, the authors say that “correct reclassification was almost entirely confined to down-classification of individuals without events rather than up-classification of those with events.”
Melander and team comment that their study “provides a clearer picture of the strengths and limitations of potential biomarker strategies in primary prevention.”
They conclude: “The challenge will be to find a new cardiovascular biomarkers that alone or in combination with existing biomarkers can bring about improvements in risk assessment that are not just statistically significant but clinically significant as well.”
Commenting on the study in a related editorial, Svati Shah (Duke University Medical Center, Durham, North Carolina) and James de Lemos (University of Texas Southwestern Medical Center, Dallas) note that "the largely null conclusions of this study are consistent with some, but in sharp distinction to other, population-based studies."
Possible reasons for divergence, they say, include that the current study population was largely low risk, as biomarkers perform less well in such populations, and that the biomarkers may be less able to predict the endpoints of nonfatal ischemic events and stroke used here than they are mortality and heart failure.
But the editorialists agree that, “in the future, better biomarkers and more creative strategies for combining them will be needed, along with comprehensive statistical and functional evaluation of causality, to fulfill the promise of biomarkers for personalized medicine.”
