Building Disease Prediction Models by Synthesis Analysis

描述(由申请人提供)：对一个人患冠心病(CHD)风险的估计在健康促进和临床医学的许多方面都很重要。通过纵向研究的多元回归分析，可以得到疾病结局的风险预测模型。例如，从弗雷明翰心脏研究得出的CHD预测模型已被广泛使用，并已被纳入最新的国家胆固醇教育计划成人治疗计划III高胆固醇血症管理指南。然而，这项研究早在许多目前已知的风险因素被怀疑之前就开始了。因此，新的危险因素如血清白蛋白、同型半胱氨酸、C反应蛋白等。荟萃分析的一种常见做法是结合关于风险因素对疾病结局的影响的大量研究的结果。如果这些综合相对风险中的几个是从医学文献中估计的特定疾病的，它们不能像在个别研究中经常做的那样，在多变量风险模型中组合，因为没有方法来克服不同队列的风险因素共线性和异质性的问题。在这项建议中，我们提出了一种新的方法，称为综合分析，将来自不同已发表研究的不同风险因素结合到多变量模型中。如果从医学文献中可以获得特定疾病的几个复合相对风险模型，则不能使用标准的荟萃分析技术将它们组合成一个多变量风险模型。在这项建议中，我们提出了一种新的方法，称为综合分析，将来自不同已发表研究的不同风险因素结合到多变量模型中。

DESCRIPTION (provided by applicant): An estimate of a person's risk for coronary heart disease (CHD) is important for many aspects of health promotion and clinical medicine. A risk prediction model on a disease outcome may be obtained through multivariate regression analysis of a longitudinal study. For example, the CHD prediction model derived from the Framingham Heart Study has been widely used and has been incorporated into the latest National Cholesterol Education Program Adult Treatment Plan III guidelines for the management of hypercholesterolemia. However, the study was started long before many currently known risk factors were suspected. Therefore, new risk factors such as serum albumin, homocysteine, C-reactive protein. A common practice of meta-analysis is combining the results of numerous studies on the effects of a risk factor on a disease outcome. If several of these composite relative risks are estimated from the medical literature for a specific disease, they cannot be combined in a multivariate risk model, as is often done in individual studies, because methods are not available to overcome the issues of risk factor colinearity and heterogeneity of the different cohorts. In this proposal, we propose new methods, called synthesis analysis, to combine different risk factors on a disease outcome from diverse published studies into multivariate models. If several composite relative risk models are available from the medical literature for a specific disease, they cannot be combined into a multivariate risk model using standard meth-analysis techniques. In this proposal, we propose new methods, called synthesis analysis, to combine different risk factors on a disease outcome from diverse published studies into multivariate models.