Section of Atherosclerosis and Vascular Medicine, Department of Medicine, Baylor College of Medicine, Houston, Texas 77030, USA.
J Am Coll Cardiol. 2010 Apr 13;55(15):1600-7. doi: 10.1016/j.jacc.2009.11.075.
We evaluated whether carotid intima-media thickness (CIMT) and the presence or absence of plaque improved coronary heart disease (CHD) risk prediction when added to traditional risk factors (TRF).
Traditional CHD risk prediction schemes need further improvement as the majority of the CHD events occur in the "low" and "intermediate" risk groups. On an ultrasound scan, CIMT and presence of plaque are associated with CHD, and therefore could potentially help improve CHD risk prediction.
Risk prediction models (overall, and in men and women) considered included TRF only, TRF plus CIMT, TRF plus plaque, and TRF plus CIMT plus plaque. Model predictivity was determined by calculating the area under the receiver-operating characteristic curve (AUC) adjusted for optimism. Cox proportional hazards models were used to estimate 10-year CHD risk for each model, and the number of subjects reclassified was determined. Observed events were compared with expected events, and the net reclassification index was calculated.
Of 13,145 eligible subjects (5,682 men, 7,463 women), approximately 23% were reclassified by adding CIMT plus plaque information. Overall, the CIMT plus TRF plus plaque model provided the most improvement in AUC, which increased from 0.742 (TRF only) to 0.755 (95% confidence interval for the difference in adjusted AUC: 0.008 to 0.017) in the overall sample. Similarly, the CIMT plus TRF plus plaque model had the best net reclassification index of 9.9% in the overall population. Sex-specific analyses are presented in the manuscript.
Adding plaque and CIMT to TRF improves CHD risk prediction in the ARIC (Atherosclerosis Risk In Communities) study.
我们评估了在加入传统危险因素 (TRF) 后,颈动脉内膜中层厚度 (CIMT) 和斑块的存在是否能改善冠心病 (CHD) 的风险预测。
传统的 CHD 风险预测方案需要进一步改进,因为大多数 CHD 事件发生在“低”和“中”风险组。在超声扫描中,CIMT 和斑块的存在与 CHD 相关,因此可能有助于改善 CHD 风险预测。
风险预测模型(总体模型以及男性和女性模型)仅考虑了 TRF、TRF 加 CIMT、TRF 加斑块以及 TRF 加 CIMT 加斑块。通过计算调整后乐观偏差的接收者操作特征曲线 (ROC) 下面积来确定模型的预测性。使用 Cox 比例风险模型来估计每个模型的 10 年 CHD 风险,并确定重新分类的人数。观察到的事件与预期事件进行比较,并计算净重新分类指数。
在 13145 名合格受试者中(5682 名男性,7463 名女性),约 23%的受试者通过加入 CIMT 加斑块信息被重新分类。总体而言,CIMT 加 TRF 加斑块模型在 AUC 方面提供了最大的改善,从仅 TRF 的 0.742 增加到整体样本的 0.755(调整后 AUC 差值的 95%置信区间:0.008 至 0.017)。同样,CIMT 加 TRF 加斑块模型在总体人群中的净重新分类指数最佳,为 9.9%。本文介绍了性别特异性分析。
在 ARIC(社区动脉粥样硬化风险)研究中,将斑块和 CIMT 添加到 TRF 中可改善 CHD 风险预测。