Novel and conventional biomarkers for the prediction of incident cardiovascular events in the community - Melander, Olle (2009)
CONTEXT: Prior studies have conflicted regarding how much information novel biomarkers add to cardiovascular risk assessment. OBJECTIVE: To evaluate the utility of biomarkers for predicting cardiovascular risk when added to conventional risk factors, using contemporary biomarkers and newer statistical approaches. DESIGN, SETTING, PARTICIPANTS: Between 1991 and 1994, 5067 participants (mean age 58, 60% women) without cardiovascular disease from a prospective cohort in Malmö, Sweden underwent measurement of C-reactive protein (CRP), mid-regional-pro-atrial natriuretic peptide, N-terminal pro-B-type natriuretic peptide (N-BNP), mid-regional-pro-adrenomedullin (MR-proADM), lipoprotein-associated phospholipase-2, and cystatin C. Participants were followed until 2006. First cardiovascular events (myocardial infarction, stroke, coronary death) were ascertained using the Swedish national hospital discharge and cause-of-death registers. Low-, intermediate-, and high-risk were defined as 10-year risks of <6%, 6–19%, or ≥20%, respectively. 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], 0.734–0.781) and 0.760 (0.730–0.789) for cardiovascular and coronary events. Biomarkers retained in backward-elimination models were N-BNP and CRP for cardiovascular events, and N-BNP and MR-proADM for coronary events, which raised the c-statistic by 0.007 (p=0.04) and 0.009 (p=0.08), respectively. The proportion of participants reclassified was modest (8% for cardiovascular risk, 5% for coronary risk). The net reclassification improvement (NRI) was non-significant for cardiovascular events (0.0%, 95%CI, −4.3%–4.3%) and coronary events (4.7%, −0.76%–10.1%). Greater improvements were observed in analyses restricted to intermediate-risk individuals (cardiovascular events: 7.4%, 95%CI, 0.7%–14.1% [p=0.03]; coronary events: 14.6%, 5.0%–24.2% [p=0.003]). However, correct re-classification was almost entirely confined to down-classification of individuals without events, rather than up-classification of those with events. CONCLUSION: 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.