首页> 美国卫生研究院文献>other >An Application of the Patient Rule-Induction Method for Evaluating the Contribution of the Apolipoprotein E and Lipoprotein Lipase Genes to Predicting Ischemic Heart Disease
【2h】

An Application of the Patient Rule-Induction Method for Evaluating the Contribution of the Apolipoprotein E and Lipoprotein Lipase Genes to Predicting Ischemic Heart Disease

机译:患者规则归纳法在评估载脂蛋白E和脂蛋白脂肪酶基因在预测缺血性心脏病中的作用的应用

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Different combinations of genetic and environmental risk factors are known to contribute to the complex etiology of ischemic heart disease (IHD) in different subsets of individuals. We employed the Patient Rule-Induction Method (PRIM) to select the combination of risk factors and risk factor values that identified each of 16 mutually exclusive partitions of individuals having significantly different levels of risk of IHD. PRIM balances two competing objectives: (1) finding partitions where the risk of IHD is high and (2) maximizing the number of IHD cases explained by the partitions. A sequential PRIM analysis was applied to data on the incidence of IHD collected over 8 years for a sample of 5,455 unrelated individuals from the Copenhagen City Heart Study (CCHS) to assess the added value of variation in two candidate susceptibility genes beyond the traditional, lipid and body mass index risk factors for IHD. An independent sample of 362 unrelated individuals also from the city of Copenhagen was used to test the model obtained for each of the hypothesized partitions.
机译:已知遗传和环境危险因素的不同组合可导致个体不同亚组中缺血性心脏病(IHD)的复杂病因。我们采用患者规则归纳法(PRIM)来选择风险因素和风险因素值的组合,以识别IHD风险水平显着不同的16个互斥分区。 PRIM平衡了两个相互竞争的目标:(1)在IHD风险高的地方找到分区;(2)最大化由分区解释的IHD案例数。对来自哥本哈根市心脏研究(CCHS)的5455名无关亲戚的样本进行了连续PRIM分析,以收集8年多来的IHD发生率数据,以评估传统脂质之外的两个候选易感基因的变异附加值和体重指数的危险因素。来自哥本哈根市的362名无关亲戚的独立样本用于测试针对每个假设分区获得的模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号