One strategy that has been proposed to improve on the limitations of individual biomarkers is to combine multiple biomarkers into an integrated score or algorithm. But the effects of multiple biomarkers in addition to the TRFs have been nonsignificant or minimal in many studies. In the Framingham Heart Study, a multimarker score (combining B-type natriuretic propeptide, CRP, urinary albumin/creatinine ratio, homocysteine, and renin) moderately improved the C-statistic by 0.02 in CVD death prediction and by 0.01 in CVD event prediction (13). In the Cardiovascular Health Study, the addition of 6 biomarkers (CRP, fibrinogen, factor VIIIc, interleukin-6, lipoprotein[a], and hemoglobin) did not improve discrimination beyond established risk factors among subjects with (difference = 0.01, p = 0.15) or without (difference = 0.01, p = 0.72) chronic kidney disease (32). In the Quebec Cardiovascular Study, an inflammation score based on interleukin-6 and fibrinogen levels moderately improved C-statistics (difference = 0.008, p = 0.03) for a CHD prediction model (33). Ridker et al. (15,34) proposed the “Reynolds risk score,” which included CRP, glycosylated hemoglobin (in women), and parental history of myocardial infarction in women (15) and men (34). The incremental C-statistic was 0.017 compared with the risk predicted by Framingham covariates and 0.003 when compared with the risk predicted by Adult Treatment Panel III covariates. Including more biomarkers, such as apolipoprotein A-I, apolipoprotein B-100, and lipoprotein(a), did not improve the C-statistic further (15). In a Swedish cohort study, the addition of multiple biomarkers improved the C-statistic for CVD prediction by 0.007 (p = 0.04) and for CHD prediction by 0.009 (p = 0.08) (35). In the present study among post-menopausal women, 5 ABMs improved the C-statistic for CHD prediction by 0.022 (p = 0.001) in all women and by 0.016 (p = 0.027) in a subgroup without CVD history. In contrast, in an elderly male cohort study (the Uppsala Longitudinal Study of Adult Men), the C-statistic for CVD death prediction increased by 0.11 (p < 0.001) when 4 markers (troponin I, N-terminal pro-brain natriuretic peptide, cystatin C, and CRP) were added to established markers in all participants and by 0.06 (p = 0.03) in the subgroup that was free of CVD at baseline (16). This large improvement in the Uppsala study might be explained at least in part by the fact that the investigators included cystatin C, troponins, and pro-brain natriuretic peptide, which reflect existing cardiac or renal damage (16,36).