Determining medications associated with drug-induced pancreatic injury through novel pharmacoepidemiology techniques that assess causation

项目总结 在美国，急性胰腺炎每年导致近30万人住院，而且其发病率还在上升。 三分之一的病例被归类为原因不明，使患者容易反复发作 因为他们不知道如何改变自己的生活方式。处方药的意外副作用可能 负责原因不明的急性胰腺炎病例。这种情况被称为药物诱导。 胰腺损伤(DIPI)。不幸的是，医疗保健提供者和医学研究人员不知道 药物会导致DIPI。这是因为大多数关于DIPI的研究都来自于对 个别病人的经验。虽然这些对于提供有关药物的线索是有价值的， 引起DIPI，它们没有考虑到其他可能导致急性胰腺炎的因素。因此， 这类研究的结论可能会错误地将特定药物贴上危险的标签。这可能会导致 减少对所治疗的疾病有效的药物的使用，导致更糟糕的结果 病人。迫切需要确定哪些药物能引起DIPI，哪些不能引起DIPI，以便预防 治疗急性胰腺炎，并继续给患者服用安全的基本药物。最近推出的 具有健康信息和强大的计算机处理能力的电子数据库使研究成为可能 数以千计的药物的效果。此外，一种名为药典范围的新数据分析技术 联合研究(PWAS)提高了这些研究的效率。此外，PWA还可以 结合基本的流行病学原则来确定一项研究结果是否表明 用药副作用是真是假。这项提案的总体目标是确定导致 DIPI通过将PWAS应用于两个大型患者健康信息数据库。此外，这项提案将 将PWAS与称为Bradford Hill标准的研究框架相结合，以区分 由错误的结果导致DIPI。这项提案的具体目标是(1)确定符合以下条件的药物 与DIPI密切相关，表现出剂量反应，并通过应用 病例对照研究的PWAS框架；(2)确定显示一致暂时性的药物 通过PWAS框架的新应用与DIPI的特异性；(3)确定可复制的 药物--利用第二个数据库重复目标1和目标2的DIPI关联；以及(4)开发和 传播一个交互式数据库，为临床医生和研究人员整合研究结果。这 研究意义重大，因为它将通过解决临床上对哪种疾病的不确定性来改善患者的预后 急性胰腺炎后应停止用药，哪些基本药物可以安全继续使用。 这项研究具有创新性，因为它结合了尖端数据分析技术和基本原理 全面识别引起DIPI的药物的研究原则。这些技术将被应用于 到未来的研究，目的是确定导致其他医疗条件的药物。

PROJECT SUMMARY Acute pancreatitis causes nearly 300,000 hospitalizations per year in the United States, and its rates are rising. One-third of cases are classified as having unknown cause, leaving patients vulnerable to repeated episodes because they do not know how to alter their lifestyles. Unexpected side effects of prescription medications may be responsible for acute pancreatitis cases with unknown cause. This situation is called drug-induced pancreatic injury (DIPI). Unfortunately, healthcare providers and medical researchers do not know which medications cause DIPI. This is because the majority of research about DIPI comes from descriptions of the experience of individual patients. While these are valuable for providing clues about medications that might cause DIPI, they do not account for other factors that could contribute to acute pancreatitis. Therefore, conclusions from this type of study may falsely label particular medications as dangerous. This may lead to reduced use of medications that are effective for the conditions that they treat, resulting in worse outcomes for patients. There is a critical need to determine which medications do and do not cause DIPI in order to prevent cases of acute pancreatitis and to continue patients on safe essential medications. The recent availability of electronic databases with health information and powerful computer processing has made it possible to study the effects of thousands of medications. Additionally, a new data analysis technique called pharmacopeia-wide association studies (PWAS) has improved the efficiency of these studies. Furthermore, PWAS can be combined with fundamental epidemiology principles to determine whether a study finding demonstrating a medication side effect is true or false. The overall objective of this proposal is to identify medications that cause DIPI by applying PWAS to two large databases of patient health information. Additionally, this proposal will combine PWAS with a research framework called the Bradford Hill criteria to distinguish medications that cause DIPI from false results. The specific aims of this proposal are (1) To identify medications that are strongly associated with DIPI, demonstrate dose response, and exhibit biologic plausibility by applying the PWAS framework to case-control studies; (2) To identify medications that demonstrate consistent temporality and specificity with DIPI through novel applications of the PWAS framework; (3) To identify replicable medication-DIPI associations by repeating Aims 1 and 2 using a second database; and (4) To develop and disseminate an interactive database to integrate the study findings for clinicians and investigators. This research is significant because it will improve patient outcomes by resolving clinical uncertainty about which medications should be stopped after acute pancreatitis and which essential medications are safe to continue. This research is innovative because it combines cutting-edge data analysis techniques with fundamental research principles to comprehensively identify medications that cause DIPI. These techniques will be applied to future studies that aim to identify medications that contribute to other medical conditions.