Using Claims-Based Signatures of Frailty to Support Individualized Treatment of Aortic Valve Stenosis and Coronary Artery Disease

项目摘要/摘要 严重的主动脉瓣狭窄和冠状动脉疾病在全球范围内困扰着大量患者。 在各种备选方案中选择最佳管理策略需要考虑 最能确定其潜在益处或危害的个人特征和共病 不同的治疗方法。然而，随机试验通常不会收集到必要的信息 告知个性化治疗决定--尤其是，通常不会捕获有关患者虚弱程度的数据。在这 格兰特，我们将利用两个试验项目之间的联系，双重抗血小板治疗研究 (比较冠状动脉支架术后较短和较长时间的抗血小板治疗)和美国CoreValve 计划(比较手术和经导管主动脉瓣置换术)，数据来自Medicare Claims 作为NHLBI赞助的扩展基于试验的医疗疗法评估的一部分，使用NOVICE 数据来源(扩展)研究以回答这些额外的问题。首先，我们将确定变量 可用于与接受主动脉瓣手术的个体的虚弱相关的行政索赔 或冠状动脉支架置入术，并评估它们是否预测长期心血管不良 在试验中确定了高于传统风险因素的结果。接下来，我们将确定基于索赔的 从这些非试验数据得出的脆弱性指数可以识别不同的治疗效果--即治疗 根据个人特征不同的影响-在随机试验的范围内 人口。根据这些结果，我们将创建并试点实施量化决策 支持需要主动脉瓣的主动脉瓣狭窄患者个体化治疗方法的工具 冠状动脉支架置入术后需要双重抗血小板治疗的患者。结果是 这项研究将极大地提高我们对行政索赔数据是否可以用于 在临床试验中加强对患者虚弱的评估，并确定虚弱的患者是否具有 心血管疾病需要不同的治疗策略。这一结果还可能极大地提高 确定个别患者从两种不同的治疗方法中获益最多或最少 常见且高度病态的心血管疾病。最后，拟议的研究将有助于创造证据-- 基于决策工具，可用于支持临床医生和患者之间的共享决策 主动脉瓣狭窄和冠状动脉疾病。

PROJECT SUMMARY/ABSTRACT Severe aortic valve stenosis and coronary artery disease afflict a large number of patients worldwide. Choosing the optimal management strategies among various alternatives requires accounting for the characteristics and comorbidities of individuals that best determine the potential benefits or harms from different treatment approaches. However, randomized trials often do not collect the information necessary to inform individualized treatment decisions – in particular, data on patient frailty is typically not captured. In this grant, we will take advantage of linkages between two trial programs, the Dual Antiplatelet Therapy Study (comparing shorter vs. longer duration of antiplatelet therapy after coronary stenting) and the US CoreValve Program (comparing surgical versus transcatheter aortic valve replacement), with data from Medicare claims as part of the NHLBI-sponsored Extending Trial-Based Evaluations of Medical Therapies Using Novel Sources of Data (EXTEND) Study to answer these additional questions. First, we will identify variables available in administrative claims that correlate with frailty among individuals undergoing aortic valve replacement or coronary artery stenting and assess whether they predict long-term adverse cardiovascular outcomes above traditional risk factors ascertained in trials. Next, we will determine whether claims-based frailty indices derived from these non-trial data can identify heterogeneous treatment effects – i.e. treatment effects that differ between individuals based on their personal characteristics – within the trials' randomized populations. Based on these results, we will then create and pilot the implementation of quantitative decision tools to support individualized treatment approaches for patients with aortic stenosis requiring aortic valve replacement and those who require dual antiplatelet therapy after coronary stent procedures. The results of this research will greatly enhance our understanding of whether administrative claims data can be used to augment the evaluation of patient frailty within clinical trials, and determine whether frail patients with cardiovascular disease require different treatment strategies. The results may also greatly improve the ability to identify individual patients who have the most or least to gain from different treatment approaches for two common and highly morbid cardiovascular conditions. Finally, the proposed research will help create evidence- based decision tools that can be used to support shared decision making between clinicians and patients with aortic valve stenosis and coronary artery disease.