Novel Applications of Risk Reclassification Methods in CVD Risk Prediction

描述（由申请人提供）：风险预测方程广泛应用于心血管医学，用于风险分层和确定成本效益和适当的治疗方案。新的预测指标是否能给弗雷明汉风险评分等已建立的模型增加临床效用是一个重要的问题。这些研究人员之前的工作已经引入了比较风险预测模型的新方法，包括风险重新分类，评估新模型更准确地将个体划分为高风险或低风险阶层的能力。该建议提供了这些方法的几个新的扩展，特别是与校准相关的，直接比较预测和观察到的风险。这种校准对于估计个人风险和计算绝对风险的差异是必不可少的。虽然在歧视的改进措施是可用的，本应用程序提出了一个综合的方法来检查改进的校准。此外，由于并非所有应用都能识别预先指定的风险层，因此提出了一种无类别的重新分类校准方法。第二个感兴趣的领域是将重新分类校准方法扩展到其他研究设计。虽然生存数据的方法可用于判别措施，但校准措施，特别是重新分类卡方统计量，扩展到生存设置的效果如何尚不清楚。此外，病例队列和匹配病例对照研究广泛应用于心血管研究，特别是生物标志物评估。目前尚不清楚重新分类措施如何很好地转化为这些设计。最后，为了限制费用，临床医生通常对疾病的多阶段筛查感兴趣。对那些处于中等风险的人进行重新分类是最有趣的，“临床NRI”一直是

DESCRIPTION (provided by applicant): Risk prediction equations are widely used in cardiovascular medicine for risk stratification and to determine cost-effective and appropriate courses of treatment. Whether new predictors can add clinical utility to established models such as the Framingham risk score is an important question. Previous work by these investigators has introduced new methods for comparing risk prediction models, including risk reclassification, which assesses the ability of new models to more accurately classify individuals into higher or lower risk strata. This proposal offers several novel extensions of these methods, particularly related to calibration, which directly compares the predicted to the observed risk. Such calibration is essential for estimating risk for the individual and computing differences in absolute risk. While measures of improvement in discrimination are available, this application proposes an integrated approach examining improvement in calibration. Also, since pre-specified risk strata are not identified for all applications, a category-free measure of reclassification calibration is proposed. A second area of interest is extending methods for reclassification calibration to other study designs. While methods for survival data are available for discrimination measures, how well measures of calibration, particularly the reclassification chi-square statistic, extend to survival settings is not yet known. In addition, case-cohort and matched case-control studies are widely used in cardiovascular research, especially for biomarker assessment. It is not known how well reclassification measures translate to these designs. Finally, to limit costs, clinicians are often interested in multi-stage screening of diseae. Reclassification of those at intermediate risk is of most interest, and the 'clinical NRI' has been introduced to assess reclassification in this group. How well this new method performs in practice remains to be determined. We propose to conduct a portfolio of research projects regarding the comparison of predictive models in general, and reclassification calibration specifically, that will further the development of these methods and their clinical utility. We wil examine the characteristics of the new measures in data on cardiovascular disease from the Women's Health Study, in simulations, and in existing case-control and case-cohort data on CVD outcomes. Extensions to these novel applications would be highly innovative and directly and immediately applicable to clinical risk prediction for cardiovascular disease.