Division of Nutrition and Metabolic Diseases, Department of Internal Medicine, Center for Human Nutrition, UT Southwestern Medical Center, Dallas, TX, USA.
Clin Endocrinol (Oxf). 2011 Sep;75(3):289-93. doi: 10.1111/j.1365-2265.2011.04045.x.
Predictive models for future risk of coronary heart disease (CHD) based on traditional risk factors, such as age, male gender, LDL cholesterol, HDL cholesterol, diabetes mellitus, hypertension, smoking and family history of premature CHD, are quite robust but leave room for further improvement. Thus, efforts are being made to assess additional biomarkers for CHD, such as, lipoprotein (a), C-reactive protein, fibrinogen, lipoprotein-associated phospholipase A2, homocysteine and others. However, none of the novel biomarkers has demonstrated improved prediction beyond traditional risk factor models in a consistent fashion across multiple cohorts. Many criteria have to be fulfilled before a biomarker can be considered clinically relevant. Another way is to develop new models predicting long-term or life-time risk of CHD. Further research using novel biomarkers and long-term predictive models has the potential to improve CHD risk prediction.
基于传统危险因素(如年龄、男性性别、LDL 胆固醇、HDL 胆固醇、糖尿病、高血压、吸烟和早发冠心病家族史)的未来冠心病(CHD)风险预测模型相当可靠,但仍有改进空间。因此,人们正在努力评估其他冠心病生物标志物,如脂蛋白(a)、C 反应蛋白、纤维蛋白原、脂蛋白相关磷脂酶 A2、同型半胱氨酸等。然而,在多个队列中,没有一种新型生物标志物在传统危险因素模型的基础上表现出一致的改善预测能力。在一个生物标志物被认为具有临床相关性之前,需要满足许多标准。另一种方法是开发新的模型来预测 CHD 的长期或终身风险。使用新型生物标志物和长期预测模型的进一步研究有可能改善 CHD 风险预测。