Coronary artery calcium synthetic cohort and lifetime percentile project (CACSC-LPP)

冠状动脉钙化(CAC)测试提供了个人动脉粥样硬化负担的直接测量， 与心血管疾病(CVD)风险密切相关。相应地，CAC评分具有IIa 2018年AHA/ACC胆固醇治疗和2019年ACC/AHA一级预防中的建议 准则，也被许多其他国家和国际准则推荐用于分配 初级预防药物。阿加特斯顿评分的临床意义可能因以下因素而显著不同 年龄、性别和种族/民族人口百分位数分数，这对于估计长期- 终身或终生心血管疾病风险，特别是对于阿加斯顿分数通常较低的年轻人 反映了过早的动脉粥样硬化并显著增加了终生风险。然而，目前的指导方针- 推荐的CAC百分位分数仅从一个NHLBI队列中得出，该队列包括 主要是中年参与者，没有集中的网站或资源提供所有可用的 帮助解释CAC分数的工具。因此，1)发展CAC的需求尚未得到满足 更能代表美国人口和更多样化的寿命的百分位数数据 少数族裔，特别是南亚人，他们的心血管疾病风险显著增加，但不是 包括在当前的百分位分数计算器中，以及2)创建一个集中的网站和移动应用程序，以帮助 从护理的角度解读CAC。因此，使用标准化的数据协调技术，我们 建议汇集来自7个NHBLI队列和3个真实世界临床队列的数据，以创建性别- 均衡、种族/民族多元化的CAC合成队列终身汇集项目(CACSC-LPP) 大约20,000名具有CAC数据的NHBLI参与者(年龄30-95岁)和 来自临床CAC队列的额外约90,000名参与者。协调个人参与者级别数据将 务实地利用NIH在这些群体中的巨额投资(金钱和时间)，创造一个新的 池化数据集，扩展了临床影响，超出了最初的预期。它还将创建一个 迭代扩展CACSC-LPP的理想基础，以确保更好地代表生活在 美国，最初的重点是南亚人。此外，我们还将构建我们的原型CAC-Tools网站 和配套应用程序，以便临床医生和患者可以输入CAC评分(加上任何其他可用的风险因素 数据)并检索其CAC百分位数。此网站/应用程序将作为所有与CAC相关的权威来源 工具，并将处于有利地位，以支持未来的国家心血管疾病指南(见LOS，劳埃德博士- Jones&Arnett)。通过创建1)CACSC-LPP，2)CAC全寿命百分位数计算器， 和3)集中的CAC网站/APP本项目将改进个性化的CVD风险预测、实施 执行ACC/AHA初级预防建议，同时也为多学科建立基础设施 以及跨机构合作，以进一步提高我们对心血管疾病风险预测的CAC的理解。

Coronary artery calcium (CAC) testing provides a direct measure of an individual’s atherosclerotic burden that is robustly associated with cardiovascular disease (CVD) risk. Accordingly, CAC scoring has a IIa recommendation in the 2018 AHA/ACC Cholesterol Treatment and 2019 ACC/AHA Primary Prevention Guidelines and is also recommended by many other national and international guidelines for the allocation of primary prevention medications. The clinical implications of the Agatston score can vary significantly based on the age, sex, and race/ethnicity population percentile score, which is particularly crucial for estimating long- term or lifetime CVD risk, especially for younger persons in whom a low Agatston score may commonly be reflective of premature atherosclerosis and significantly increased lifetime risk. However, current guideline- recommended CAC percentile scores were developed from only one NHLBI cohort comprised of predominantly middle-aged participants and there is no centralized website or resource with all the available tools to facilitate interpretation of the CAC score. Consequently, there is an unmet need to 1) develop CAC percentile data across the lifespan that is more representative of the US population and more diverse across racial/ethnic minorities, particularly South Asians, who have a significantly increased CVD risk yet are not included in current percentile score calculators and 2) create a centralized website and mobile app to aid in the interpretation of CAC at the point of care. Therefore, using standardized data harmonization techniques, we propose to pool data from 7 NHBLI cohorts and 3 real-world clinically-derived cohorts to create the gender- balanced, racially/ethnically diverse CAC Synthetic Cohort Lifetime Pooling Project (CACSC-LPP) of approximately 20,000 NHBLI participants with CAC data across the lifespan (age 30-95 years old) and an additional ~90,000 participants from clinical CAC cohorts. Harmonizing the individual participant level data will pragmatically leverage the enormous NIH investment (monetary and time) in these cohorts to create a new pooled dataset that expands the clinical impact beyond what was originally envisioned. It will also create an ideal foundation to iteratively expand the CACSC-LPP to ensure better representation for all persons living in the US, with an initial focus on South Asians. Additionally, we will build upon our prototype CAC-tools website and companion app so that clinicians and patients can enter a CAC score (plus any other available risk factor data) and retrieve their CAC percentile. This website/app will serve as the definitive source for all CAC related tools and would be well positioned to be endorsed by future national CVD guidelines (see LOS, Drs. Lloyd- Jones & Arnett). Through the creation of the 1) CACSC-LPP, 2) CAC percentile calculator across the lifespan, and 3) centralized CAC website/app this project will improve personalized CVD risk prediction, implementation of ACC/AHA primary prevention recommendations, while also creating the infrastructure for multidisciplinary and cross-institutional collaborations to further improve our understanding of CAC for CVD risk prediction.