Tzoulaki et al examined 56 meta-analyses of emerging cardiovascular biomarkers and evaluated whether there is evidence for biases favoring statistically significant results. In 29 meta-analyses (52%) there was a significant excess of studies with statistically significant results. Only 13 of the statistically significant meta-analyses had more than 1000 cases, no hints of very large heterogeneity, small-study effects, or excess significance. These included the associations of glomerular filtration rate and albumin to creatinine ratio in general and high-risk populations with cardiovascular disease mortality and of non–high-density lipoprotein cholesterol, serum albumin, Chlamydia pneumoniae IgG, glycosylated hemoglobin, nonfasting insulin, apolipoprotein B/AI ratio, erythrocyte sedimentation rate, and lipoprotein-associated phospholipase mass or activity with coronary heart disease. These findings suggest that most of the proposed associations of these biomarkers may be inflated.