Xanthine oxidase inhibitors and risks of myocardial infarction and diabetes

 描述（由申请人提供）：痛风是高尿酸血症引起的最常见的炎性关节炎。 在过去的几十年里，越来越多的证据支持痛风和高尿酸血症与高血压、心血管疾病（包括心肌梗死（MI）和卒中）、代谢综合征（包括2型糖尿病（T2 DM））和死亡率的风险增加独立相关。一些研究表明，痛风患者的死亡率过高是由于心血管疾病。黄嘌呤氧化酶抑制剂（XOI），包括别嘌呤醇和非布司他，降低血清尿酸，是痛风的常用治疗方法。别嘌呤醇已被证明可以降低高血压青少年的血压，改善内皮功能。此外，动物模型显示别嘌呤醇对代谢综合征的有益作用。然而，迄今为止，XOI是否能降低痛风相关疾病（如MI和T2 DM）的风险仍是未知数。该提案的主要目的是提供高质量的证据，证明XOI在预防痛风患者MI和T2 DM方面的作用。该提案的具体目的是：1）检查XOI对痛风患者发生MI风险的影响，2）调查 XOI对痛风患者发生T2 DM的风险，3）评估XOI对MI和T2 DM的影响，并根据痛风患者的治疗依从性进行调整。拟议的研究将使用来自United HealthCare保险索赔数据库（2004-2013年）的数据与实验室检查结果相关联，并利用许多严格和创新的药物流行病学研究方法和因果关系推断来研究XOI对MI和T2 DM风险的影响。鉴于临床研究中对大数据和数据链接的兴趣日益增加，重要的是要了解使用与门诊实验室检测结果相关的索赔数据库进行药物流行病学研究的价值，并确定将实验室数据纳入进一步混杂控制的最佳策略。这项拟议的研究将做出重要贡献，因为它将是第一个也是最大规模的研究XOI对MI和T2 DM等主要疾病的影响，并根据依从性进行调整。此外，所提出的先进和创新的流行病学方法将扩展我们对如何处理药物流行病学研究中的适应症混杂、时变选择偏倚和实验室检测值缺失数据的理解。

 DESCRIPTION (provided by applicant): Gout is the most common inflammatory arthritis caused by hyperuricemia. Over the past few decades, growing evidence supports that gout and hyperuricemia are independently associated with an increased risk of hypertension, cardiovascular diseases including myocardial infarction (MI) and stroke, metabolic syndrome including type 2 diabetes mellitus (T2DM), and mortality. Several studies suggest that the excess mortality in gout patients is attributable to cardiovascular disease. Xanthine oxidase inhibitors (XOI), including allopurinol and febuxostat, lower serum uric acids and are common treatments for gout. Allopurinol has been shown to reduce blood pressure in hypertensive adolescents and improve endothelial function. Furthermore, an animal model showed a beneficial effect of allopurinol on metabolic syndrome. However, to date, it remains largely unknown whether XOIs decrease risks of gout-associated conditions such as MI and T2DM. The primary objective of this proposal is to produce high-quality evidence on the effect of XOI in preventing MI and T2DM in gout patients. The specific aims of this proposal are: 1) to examine the effect of XOI on the risk of incident MI in patients with gout, 2) to investigate the effect of XOI on the risk of incident T2DM in patients with gout and 3) to estimate the effect of XOI on MI and T2DM adjusted for treatment adherence in patients with gout. The proposed study will use data from the United HealthCare insurance claims databases (2004-2013) linked to laboratory test results, and utilize a number of rigorous and innovative approaches for pharmacoepidemiologic research and causal inference to study the effects of XOI on MI and T2DM risks. Given the increasing interest in big data and data linkage in clinical research, it is important to understand the value of using a claims database linked to outpatient lab test results for pharmacoepidemiologic research and to determine the best strategy to incorporate lab data for further confounding control. This proposed study will make an important contribution because it will be the first and largest to investigate the effects of XOI on major medical conditions such as MI and T2DM, adjusting for adherence. Furthermore, the proposed, advanced and innovative epidemiologic methods will extend our understanding of how to deal with confounding by indication, time-varying selection bias, and missing data on laboratory test values in pharmacoepidemiologic research.