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Melander O, Newton-Cheh C, Almgren P, et al. Novel and Conventional Biomarkers for Prediction of Incident Cardiovascular Events in the Community. JAMA. 2009;302(1):49–57. doi:10.1001/jama.2009.943
Author Affiliations: Department of Clinical Sciences, Lund University, Malmö, Sweden (Drs Melander, Hedblad, Berglund, Engström, Persson, Smith, Magnusson, and Christensson and Mr Almgren); Cardiology Division (Drs Newton-Cheh and Wang), Center for Human Genetic Research (Dr Newton-Cheh), and Cardiovascular Research Center (Drs Newton-Cheh and Wang), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute ofHarvard and MIT, Cambridge, Massachusetts (Drs Newton-Cheh and Smith); Research Department, BRAHMS AG, Hennigsdorf, Germany (Drs Struck, Morgenthaler, and Bergmann); and Department of Biostatistics, Boston University, Boston (Dr Pencina).
Context Prior studies have demonstrated conflicting results regarding how much information novel biomarkers add to cardiovascular risk assessment.
Objective To evaluate the utility of contemporary biomarkers for predicting cardiovascular risk when added to conventional risk factors.
Design, Setting, and Participants Cohort study of 5067 participants (mean age, 58 years; 60% women) without cardiovascular disease from Malmö, Sweden, who attended a baseline examination between 1991 and 1994. Participants underwent measurement of C-reactive protein (CRP), cystatin C, lipoprotein-associated phospholipase 2, midregional proadrenomedullin (MR-proADM), midregional proatrial natriuretic peptide, and N-terminal pro-B-type natriuretic peptide (N-BNP) and underwent follow-up until 2006 using the Swedish national hospital discharge and cause-of-death registers and the Stroke in Malmö register for first cardiovascular events (myocardial infarction, stroke, coronary death).
Main Outcome Measures Incident cardiovascular and coronary events.
Results During median follow-up of 12.8 years, there were 418 cardiovascular and 230 coronary events. Models with conventional risk factors had C statistics of 0.758 (95% confidence interval [CI], 0.734 to 0.781) and 0.760 (0.730 to 0.789) for cardiovascular and coronary events, respectively. Biomarkers retained in backward-elimination models were CRP and N-BNP for cardiovascular events and MR-proADM and N-BNP for coronary events, which increased the C statistic by 0.007 (P = .04) and 0.009 (P = .08), respectively. The proportion of participants reclassified was modest (8% for cardiovascular risk, 5% for coronary risk). Net reclassification improvement was nonsignificant for cardiovascular events (0.0%; 95% CI, −4.3% to 4.3%) and coronary events (4.7%; 95% CI, −0.76% to 10.1%). Greater improvements were observed in analyses restricted to intermediate-risk individuals (cardiovascular events: 7.4%; 95% CI, 0.7% to 14.1%; P = .03; coronary events: 14.6%; 95% CI, 5.0% to 24.2%; P = .003). However, correct reclassification was almost entirely confined to down-classification of individuals without events rather than up-classification of those with events.
Conclusions Selected biomarkers may be used to predict future cardiovascular events, but the gains over conventional risk factors are minimal. Risk classification improved in intermediate-risk individuals, mainly through the identification of those unlikely to develop events.
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