Personalizing Angiotensin-Converting Enzyme Inhibitor and Angiotensin Receptor Blocker Therapy in Chronic Kidney Disease

项目摘要/摘要 血管紧张素转换酶抑制剂(ACEI)和血管紧张素受体阻滞剂(ARB)是指南- 预防终末期肾病(ESKD)和心血管疾病(CVD)的推荐疗法 慢性肾脏病患者的事件。然而，在现实世界的实践中，ACEI/ARB经常被 在急性肾损伤(AKI)、肾功能迅速下降或晚期CKD的背景下提供服务。 过早停用ACEIs/ARB可导致CKD患者的不良临床结局。 然而，对于某些风险较高的CKD亚组，停用这些药物可能是合适的 与试验人群相比，这些人从这些药物中获得的好处可能更少。尽管指导方针支持 在CKD患者中使用ACEI/ARB，它们还允许围绕其 使用。然而，随着慢性肾脏病的进展以优化肾脏，目前尚不清楚如何最好地使这些决定个体化。 以及心血管方面的结果。 这项建议的总体目标是使CKD患者的ACEI/ARB治疗个性化 个体对ESKD和CVD的危险因素。为了做到这一点，我们将使用慢性肾脏疾病的数据 不充分队列(CRIC)研究。我们将首先查明导致ACEI/ARB停产的因素 (目标1)。接下来，我们将构建两个临床工具来模拟ACEI/ARB停用之间的关系 CKD患者发生ESKD(目标2)或CVD事件(目标3)的风险。我们的长期目标是减少 通过在慢性肾脏病中个体化用药，减轻肾脏疾病的负担，改善患者的预后。我们预计 完成这些目标将导致开发两种可进一步改进的预测工具 并作为职业发展奖申请的一部分在现实世界的临床实践中实施。 建议的目标被整合到一个全面的培训计划中，该计划包括 临床研究和实践指导经验。通过这个培训计划，陈博士将拥有 1)学习和应用先进的生物统计和流行病学方法知识的机会，包括 边缘结构建模；2)熟悉CRIC研究数据库；3)应用机器学习 算法用于临床预测工具的开发，4)提高科学写作和演示的技能 研究，以及5)迈向职业发展奖和作为临床研究员的独立性。

PROJECT SUMMARY/ABSTRACT Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) are guideline- recommended therapies for preventing end-stage kidney disease (ESKD) and cardiovascular disease (CVD) events in patients with CKD. However, in real-world practice, ACEIs/ARBs are frequently discontinued by providers in the setting of acute kidney injury (AKI), rapid declines in kidney function, or advanced CKD. Premature discontinuation of ACEIs/ARBs can lead to adverse clinical outcomes among patients with CKD. However, discontinuation of these agents may be appropriate for certain CKD subgroups who are at higher risk of AKI and who may derive less benefit from these agents than trial populations. Although guidelines support the use of ACEIs/ARBs in patients with CKD, they also allow for individualization of decisions surrounding their use. However, it is unclear how to best individualize these decisions as CKD progresses to optimize kidney and cardiovascular outcomes. The overall objective of this proposal is to personalize ACEI/ARB therapy for patients with CKD based on each individual's risk factors for ESKD and CVD. To accomplish this, we will use data from the Chronic Renal Insufficiency Cohort (CRIC) Study. We will first identify factors that drive the discontinuation of ACEIs/ARBs (Aim 1). Next, we will build two clinical tools that model the relationship between ACEI/ARB discontinuation and risk of ESKD (Aim 2) or CVD events (Aim 3) in individuals with CKD. Our long-term goal is to reduce the burden of kidney disease and improve patient outcomes by individualizing medication use in CKD. We expect that completion of these aims will result in the development of two prediction tools that can be further refined and implemented in real-world clinical practice as part of a career development award application. The proposed aims are integrated into a comprehensive training plan that includes a Master's Degree in Clinical Research and practical mentored experiences. Through this training plan, Dr. Chen will have the opportunity to 1) learn and apply knowledge in advanced biostatistical and epidemiological methods, including marginal structural modeling; 2) gain familiarity with the CRIC Study database, 3) apply machine learning algorithms to the development of clinical prediction tools, 4) refine skills in scientific writing and presenting research, and 5) advance towards a career development award and independence as a clinical investigator.