Folsom Aaron R, Chambless Lloyd E, Ballantyne Christie M, Coresh Josef, Heiss Gerardo, Wu Kenneth K, Boerwinkle Eric, Mosley Thomas H, Sorlie Paul, Diao Guoqing, Sharrett A Richey
Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55454-1015, USA.
Arch Intern Med. 2006 Jul 10;166(13):1368-73. doi: 10.1001/archinte.166.13.1368.
There has been interest in recent years in whether additional, and in particular novel, risk factors or blood markers, such as C-reactive protein, can enhance existing coronary heart disease (CHD) prediction models.
Using a series of case-cohort studies, the prospective Atherosclerosis Risk in Communities (ARIC) Study assessed the association of 19 novel risk markers with incident CHD in 15,792 adults followed up since 1987-1989. Novel markers included measures of inflammation, endothelial function, fibrin formation, fibrinolysis, B vitamins, and antibodies to infectious agents. Change in the area under the receiver operating characteristic curve (AUC) was used to assess the additional contribution of novel risk markers to CHD prediction beyond that of traditional risk factors.
The basic risk factor model, which included traditional risk factors (age, race, sex, total and high-density lipoprotein cholesterol levels, systolic blood pressure, antihypertensive medication use, smoking status, and diabetes), predicted CHD well, as evidenced by an AUC of approximately 0.8. The C-reactive protein level did not add significantly to the AUC (increase in AUC of 0.003), and neither did most other novel risk factors. Of the 19 markers studied, lipoprotein-associated phospholipase A(2), vitamin B(6), interleukin 6, and soluble thrombomodulin added the most to the AUC (range, 0.006-0.011).
Our findings suggest that routine measurement of these novel markers is not warranted for risk assessment. On the other hand, our findings reinforce the utility of major, modifiable risk factor assessment to identify individuals at risk for CHD for preventive action.
近年来,人们一直关注是否有其他风险因素,尤其是新的风险因素或血液标志物,如C反应蛋白,能够增强现有的冠心病(CHD)预测模型。
通过一系列病例队列研究,前瞻性社区动脉粥样硬化风险(ARIC)研究评估了19种新的风险标志物与自1987 - 1989年以来随访的15792名成年人中冠心病发病的关联。新的标志物包括炎症、内皮功能、纤维蛋白形成、纤维蛋白溶解、B族维生素以及针对感染因子的抗体的测量指标。采用受试者工作特征曲线(AUC)下面积的变化来评估新的风险标志物相对于传统风险因素对冠心病预测的额外贡献。
包含传统风险因素(年龄、种族、性别、总胆固醇和高密度脂蛋白胆固醇水平、收缩压、使用抗高血压药物、吸烟状况和糖尿病)的基本风险因素模型对冠心病有较好的预测能力,AUC约为0.8即可证明。C反应蛋白水平对AUC没有显著增加(AUC增加0.003),大多数其他新的风险因素也是如此。在研究的19种标志物中,脂蛋白相关磷脂酶A2、维生素B6、白细胞介素6和可溶性血栓调节蛋白对AUC增加最多(范围为0.006 - 0.011)。
我们的研究结果表明,对于风险评估而言,常规检测这些新的标志物并无必要。另一方面,我们的研究结果强化了主要的、可改变的风险因素评估在识别冠心病高危个体以采取预防措施方面的作用。