Scheuner Maren T, Setodji Claude Messan, Pankow James S, Blumenthal Roger S, Keeler Emmett
RAND Corporation, Santa Monica, CA 90407-2138, USA.
Circ Cardiovasc Genet. 2010 Feb;3(1):97-105. doi: 10.1161/CIRCGENETICS.109.894527. Epub 2009 Dec 14.
The General Cardiovascular Risk Profile is a multivariable model that predicts global cardiovascular disease risk. Our goal was to assess the ability of the General Cardiovascular Risk Profile to identify individuals with advanced coronary artery calcification (CAC) and determine whether identification is improved with family history.
Using data from the Multiethnic Study of Atherosclerosis, 3 sex-specific models were developed with ordinal logistic regressions to relate risk factors to CAC scores. Model 1 included covariates in the General Cardiovascular Risk Profile. Then family history was added, defined as having at least 1 first-degree relative with premature coronary heart disease (model 2) or as a weak, moderate, or strong family history based on number of relatives with coronary heart disease, age at onset, and the presence of stroke or diabetes in the family (model 3). For each model, we estimated mathematical CAC risk functions, derived CAC score sheets, evaluated the ability to discriminate persons having positive CAC scores, and assessed reclassification of individuals with low, intermediate, or high probability of CAC >300. Model 1 worked well to identify women and men with positive CAC scores; c-statistics were 0.752 and 0.718 and chi(2) values were 821.2 (P<0.0001) and 730.6 (P<0.0001), respectively. Addition of family history improved discrimination and fit of model 1. However, reclassification of participants with advanced CAC was significantly improved with model 3 only.
The General Cardiovascular Risk Profile identifies advanced CAC, an emerging indication for aggressive risk factor modification. Incorporation of family history, especially comprehensive familial risk stratification, provides incremental prognostic value.
综合心血管风险概况是一种预测全球心血管疾病风险的多变量模型。我们的目标是评估综合心血管风险概况识别患有严重冠状动脉钙化(CAC)个体的能力,并确定家族史是否能改善这种识别能力。
利用动脉粥样硬化多民族研究的数据,通过有序逻辑回归建立了3个性别特异性模型,以将风险因素与CAC评分相关联。模型1纳入了综合心血管风险概况中的协变量。然后加入家族史,定义为至少有1名患有早发性冠心病的一级亲属(模型2),或根据患有冠心病的亲属数量、发病年龄以及家族中是否存在中风或糖尿病定义为弱、中或强家族史(模型3)。对于每个模型,我们估计了数学CAC风险函数,推导了CAC评分表,评估了区分CAC评分阳性者的能力,并评估了CAC>300低、中或高概率个体的重新分类。模型1在识别CAC评分阳性的女性和男性方面效果良好;c统计量分别为0.752和0.718,卡方值分别为821.2(P<0.0001)和730.6(P<0.0001)。加入家族史改善了模型1的区分能力和拟合度。然而,仅模型3能显著改善患有严重CAC参与者的重新分类。
综合心血管风险概况可识别严重CAC,这是积极进行风险因素修正的一个新指征。纳入家族史,尤其是全面的家族风险分层,可提供额外的预后价值。