Department of Medicine II, University Medical Center of the Johannes Gutenberg-University Mainz, Langenbeckstr. 1, 55131 Mainz, Germany.
Eur Heart J. 2010 Dec;31(24):3024-31. doi: 10.1093/eurheartj/ehq322. Epub 2010 Sep 18.
multimarker approaches for risk prediction in coronary artery disease have remained inconsistent. We assessed multiple biomarkers representing distinct pathophysiological pathways in relation to cardiovascular events in stable angina.
we investigated 12 biomarkers reflecting inflammation [C-reactive protein, growth-differentiation factor (GDF)-15, neopterin], lipid metabolism (apolipoproteins AI, B100), renal function (cystatin C, serum creatinine), and cardiovascular function and remodelling [copeptin, C-terminal-pro-endothelin-1, mid-regional-pro-adrenomedullin (MR-proADM), mid-regional-pro-atrial natriuretic peptide (MR-proANP), N-terminal-pro-B-type natriuretic peptide (Nt-proBNP)] in 1781 stable angina patients in relation to non-fatal myocardial infarction and cardiovascular death (n = 137) over 3.6 years. Using Cox proportional hazards models and C-indices, the strongest association with outcome for log-transformed biomarkers in multivariable-adjusted analyses was observed for Nt-proBNP [hazard ratio (HR) for one standard deviation increase 1.65, 95% confidence interval (CI) 1.28-2.13, C-index 0.686], GDF-15 (HR 1.59, 95% CI 1.25-2.02, C-index 0.681), MR-proANP (HR 1.46, 95% CI 1.14-1.87, C-index 0.673), cystatin C (HR 1.39, 95% CI 1.10-1.75, C-index 0.671), and MR-proADM (HR 1.63, 95% CI 1.21-2.20, C-index 0.668). Each of these top single markers and their combination (C-index 0.690) added predictive information beyond the baseline model consisting of the classical risk factors assessed by C-index and led to substantial reclassification (P-integrated discrimination improvement <0.05).
comparative analysis of 12 biomarkers revealed Nt-proBNP, GDF-15, MR-proANP, cystatin C, and MR-proADM as the strongest predictors of cardiovascular outcome in stable angina. All five biomarkers taken separately offered incremental predictive ability over established risk factors. Combination of the single markers slightly improved model fit but did not enhance risk prediction from a clinical perspective.
用于冠心病风险预测的多标志物方法一直不一致。我们评估了多个代表不同病理生理途径的生物标志物与稳定型心绞痛的心血管事件的关系。
我们研究了 1781 例稳定型心绞痛患者的 12 种生物标志物，这些标志物反映了炎症[C 反应蛋白、生长分化因子（GDF）-15、新蝶呤]、脂代谢（载脂蛋白 AI、B100）、肾功能（胱抑素 C、血清肌酐）和心血管功能及重塑[ copeptin、C 端-内皮素-1、中段-促肾上腺皮质素释放肽（MR-proADM）、中段-心房利钠肽（MR-proANP）、N 端-脑利钠肽前体（Nt-proBNP）]，与非致命性心肌梗死和心血管死亡（n=137）有关，随访时间为 3.6 年。使用 Cox 比例风险模型和 C 指数，在多变量调整分析中，与结局相关性最强的是对数转换生物标志物的 Nt-proBNP[一个标准差增加的风险比（HR）为 1.65，95%置信区间（CI）为 1.28-2.13，C 指数为 0.686]、GDF-15（HR 1.59，95%CI 1.25-2.02，C 指数 0.681）、MR-proANP（HR 1.46，95%CI 1.14-1.87，C 指数 0.673）、胱抑素 C（HR 1.39，95%CI 1.10-1.75，C 指数 0.671）和 MR-proADM（HR 1.63，95%CI 1.21-2.20，C 指数 0.668）。这些顶级单标志物中的每一个及其组合（C 指数 0.690）都提供了超越由 C 指数评估的经典风险因素的预测信息，并导致了实质性的重新分类（P 综合判别改善<0.05）。
对 12 种生物标志物的比较分析显示，Nt-proBNP、GDF-15、MR-proANP、胱抑素 C 和 MR-proADM 是稳定型心绞痛心血管结局的最强预测因子。这五个生物标志物单独使用都提供了比既定风险因素更好的预测能力。单个标志物的组合略微提高了模型拟合度，但从临床角度来看并没有提高风险预测。
