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

通过评估因果关系的新型药物流行病学技术确定与药物引起的胰腺损伤相关的药物

• 批准号: 10638247
• 负责人: Ravy Kuppalapalle Vajravelu
• 金额: $ 38.29万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10638247
• 关键词: Accounting; Address; Biological; Biometry; Case Study; Case/Control Studies; Classification; Clinical; Clostridium difficile; Computers; Controlled Study; Dangerousness; Data; Data Analyses; Data Mart; Data Science; Databases; Dose; Drug Prescriptions; Electronic Health Record; Electronics; Epidemiology; Etiology; Exhibits; Exposure to; Future; Genomics; Goals; Health; Health Personnel; Hospitalization; Incidence; Individual; Infection; Label; Life Style; Linear Regressions; Logistic Regressions; Medical; Medication Management; Methodology; Methods; Modernization; National Institute of Diabetes and Digestive and Kidney Diseases; Observational Study; Outcome; Pancreatic Injury; Pancreatitis; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Pharmacodynamics; Pharmacoepidemiology; Pharmacopoeias; Procedures; Public Health; Randomized, Controlled Trials; Recurrence; Reporting; Research; Research Design; Research Personnel; Retrospective cohort study; Specificity; Strategic Planning; Techniques; Time; Uncertainty; United States; Update; Veterans Health Administration; acute pancreatitis; chronic pancreatitis; clinical data warehouse; design; evidence base; experience; fundamental research; gastrointestinal; improved; individual patient; innovation; insight; interest; novel; patient health information; pharmacologic; pilot test; post-market; prevent; response; side effect; time use; usability

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.

项目概要 在美国，急性胰腺炎每年导致近 30 万人住院，而且发病率还在上升。 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。处方药可能会出现意想不到的副作用 负责不明原因的急性胰腺炎病例。这种情况称为药物引起的 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哪些 药物引起 DIPI。这是因为关于 DIPI 的大部分研究都来自于对 DIPI 的描述。 个别患者的经验。虽然这些对于提供有关可能的药物的线索很有价值 导致 DIPI 的原因，他们没有考虑可能导致急性胰腺炎的其他因素。所以， 此类研究的结论可能会将特定药物错误地标记为危险药物。这可能会导致 减少对所治疗疾病有效的药物的使用，导致更糟糕的结果 患者。迫切需要确定哪些药物会引起 DIPI，哪些药物不会引起 DIPI，以预防 急性胰腺炎病例，并继续让患者接受安全的基本药物治疗。最近的可用性 具有健康信息的电子数据库和强大的计算机处理能力使研究成为可能 数千种药物的作用。此外，一种称为全药典的新数据分析技术 关联研究（PWAS）提高了这些研究的效率。此外，PWAS 可以 结合基本的流行病学原理来确定研究结果是否证明 药物副作用是真是假。该提案的总体目标是确定导致 DIPI 将 PWAS 应用于两个大型患者健康信息数据库。此外，该提案将 将 PWAS 与称为 Bradford Hill 标准的研究框架相结合，以区分以下药物： 导致 DIPI 的错误结果。该提案的具体目标是 (1) 确定适合的药物 与 DIPI 密切相关，证明剂量反应，并通过应用 病例对照研究的 PWAS 框架； (2) 识别表现出一致时间性的药物 通过 PWAS 框架的新颖应用来实现 DIPI 的特异性； (3) 识别可复制的 通过使用第二个数据库重复目标 1 和 2 来建立药物-DIPI 关联； (4) 开发和 传播交互式数据库，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不确定性来改善患者的治疗结果 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，因为它结合了尖端的数据分析技术和基础知识 全面识别导致 DIPI 的药物的研究原则。这些技术将被应用 未来的研究旨在确定导致其他医疗状况的药物。