Causal Inference for Better Understanding Clinical Trials Results: Reconciling Discrepant Comparative Evidence from Two Major Cardiovascular Safety Trials of Urate-Lowering Therapy

项目摘要/摘要 临床试验是因果推断的金标准。然而，通常在临床试验中使用的分析 无法回答涉及调解机制的微妙问题。因此，关于 痛风药物对心血管的影响，例如降低尿酸的治疗，以及越来越多的秋水仙碱， 尽管在痛风患者中进行了两项主要的心血管试验：非布索他汀的心血管安全性和 痛风和心血管疾病(CARE)患者的别嘌醇和非布索坦与别嘌醇的比较 简化了试用(快速)。CARE显示，非布索斯特使用者的死亡人数有所增加。然而，它有一个很高的 随访率损失。另一方面，FAST中的一些效果估计有利于非布索斯特。然而，在那里 在FAST中有区别地停止降尿酸治疗和不同程度地使用秋水仙碱。这些 个性导致了挥之不去的问题。 1.在非痛风试验中增加使用秋水仙碱(在非痛风试验中具有心脏保护作用)是否会影响 快速的结果有利于非布索斯特？ 2.非布索他汀组停药次数多，停药时间快，失访次数多，对别嘌醇的影响较大 团体在关心他们的结果有偏差吗？ 在这项拟议的研究中，我们将使用先进的因果推理方法通过并行方式来解决这些问题 对FAST和CARE的分析。在目标1中，我们将首先进行秋水仙碱的比较有效性研究。 在FAST和CARE中，预防与没有预防或非类固醇抗炎药物预防相比。 然后我们将进行因果调解分析，以量化秋水仙素的使用在多大程度上解释了 点数估计在FAST中支持非布索斯特。在目标2中，我们将评估非布索他汀的“按方案效应” 与别嘌醇相比，对心血管结果的影响。这种方法估计了这些药物的效果。 在完全遵守和跟进的因果情况下，降低这些 审判。我们的方法创新项目有望帮助协调来自FAST的不一致结果 并关心他们。PI还将开发一个有价值的合作网络和初步数据，展示 因果推断方法在临床试验分析中的有用性。我们将进一步传播这些先进的 方法通过线上和线下方法教程。

Project Summary / Abstract Clinical trials are the gold standard of causal inference. However, analyses typically employed in clinical trials cannot answer nuanced questions involving mediating mechanisms. As a result, debate continues regarding the cardiovascular implications of gout medications, such as urate-lowering therapy and, increasingly, colchicine, despite the two major cardiovascular trials among gout patients: Cardiovascular Safety of Febuxostat and Allopurinol in Patients with Gout and Cardiovascular Morbidities (CARES) and Febuxostat versus Allopurinol Streamlined Trial (FAST). CARES showed an increase in deaths among febuxostat users. However, it had a high loss to follow-up rate. On the other hand, some of the effect estimates in FAST favored febuxostat. However, there were differential discontinuation of urate-lowering therapy and differential use of colchicine in FAST. These idiosyncrasies have led to lingering questions. 1. Did the increased use of colchicine (cardio-protective in non-gout trials) among the febuxostat group affect FAST results in favor of febuxostat? 2. Did higher drug discontinuation in the febuxostat group in FAST and higher loss to follow-up in the allopurinol group in CARES bias their results? In this proposed study, we will use advanced causal inference methods to address these questions via parallel analyses of FAST and CARES. In Aim 1, we will first conduct a comparative effectiveness study of colchicine prophylaxis compared to no prophylaxis or non-steroidal anti-inflammatory drug prophylaxis in FAST and CARES. We will then conduct causal mediation analysis to quantify the extent to which colchicine use explains the protective point estimates favoring febuxostat in FAST. In Aim 2, We will estimate the "per-protocol effect" of febuxostat compared to allopurinol on cardiovascular outcomes. This approach estimates the effect of these medications under a causal scenario of full adherence and follow-up, reducing this significant interpretability difficulty of these trials. Our methodologically innovative project is expected to help to reconcile the discrepant results from FAST and CARES. PI will also develop a valuable collaboration network and preliminary data demonstrating the usefulness of causal inference methods in clinical trial analysis. We will further disseminate these advanced methods via online and offline methodology tutorials.