High-throughput screening for antihypertensive prescribing cascades

抗高血压处方级联的高通量筛选

• 批准号: 10682502
• 负责人: Steven Michael Smith
• 金额: $ 11.44万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10682502
• 关键词: Accounting; Adherence; Adrenergic beta-Antagonists; Adult; Adverse drug event; Adverse effects; Adverse event; Age; American; Antihypertensive Agents; Biological; Blood Pressure; Calcium Channel Blockers; Cardiovascular system; Chronic; Classification; Clinical; Collection; Data; Data Analyses; Data Science; Data Sources; Databases; Detection; Disease; Disparity; Diuretics; Drug Prescriptions; Economics; Edema; Elderly; Ethnic Origin; Exposure to; Failure; Future; Generations; Goals; Guidelines; Hypertension; Individual; Insurance; Intervention Studies; Investigation; Knowledge; Label; Medicare; Medicine; Methodology; National Heart, Lung, and Blood Institute; Outcome; Patients; Pharmaceutical Preparations; Physicians; Polypharmacy; Prevention; Process; Quality of life; Race; Records; Regimen; Research; Resources; Signal Transduction; Subgroup; Symptoms; Testing; Time; Work; blood pressure control; candidate identification; cardiovascular risk factor; clinical decision support; clinically significant; cost; frontier; high throughput screening; human disease; innovation; novel; precision drugs; prevent; screening; sex; side effect; thiazide

PROJECT SUMMARY Hypertension (HTN) is prevalent in nearly half of U.S. adults and treated with >3 million antihypertensive prescription fills per day in the U.S. Although commonly-used antihypertensives are generally well-tolerated, their ubiquitous use exposes millions of adults to potentially treatment-limiting adverse events (AEs), some of which are well-known, but many are non-specific or indistinguishable from HTN-related symptoms and not easily attributed to the offending antihypertensive. Failure to associate these AEs with the causative agent may prompt additional therapy to treat the AE—known as a “prescribing cascade”—with potentially important implications regarding polypharmacy, unnecessary costs, exposure to additional side effects, treatment nonadherence, and reduced quality of life, especially in older adults. Most prescribing cascade studies to date have been narrowly focused on drugs with a well-known AE that is highly specific to the drug, severely limiting our understanding of prescribing cascades occurring due to less well-known or non-specific AEs. This approach has resulted in slow knowledge generation and missed opportunities for comprehensively assessing and discovering new prescribing cascades. In line with NHLBI Strategic Objective 7 to “leverage emerging opportunities in data science to open new frontiers in research,” this proposal seeks to develop and utilize a novel methodologic approach for high-throughput screening of prescribing cascades and discover novel antihypertensive prescribing cascades using a nationally-representative administrative claims data source. This goal will be achieved via the following Aims: 1) elucidate candidate antihypertensive-related prescribing cascades using the SIDe Effect Resource, a collection of prescription labeling which include drug AEs and drug indications; 2) identify prescribing cascade signals occurring during real world use of antihypertensives using a Medicare database; and, 3) classify cascade signal detection and prioritize further research via an expert panel. The proposed work is expected to 1) identify and characterize the magnitude of common antihypertensive prescribing cascades, including those previously unknown; 2) develop an efficient framework for wide-scale assessment of prescribing cascade detection; and, 3) establish the basis for a compendium of known cascades. This proposal also builds logically towards future research applying this framework for discovery of prescribing cascades with cardiovascular (and other) treatments, assessing downstream consequences of prescribing cascades, and testing clinical decision support aids to prevent prescribing cascades.

项目摘要 高血压（HTN）在几乎一半的美国成年人中普遍存在，并接受300万降压药治疗 尽管普遍使用的抗高血压剂通常是耐受性的，但在美国每天的处方填充 他们无处不在 这是众所周知的，但许多与与HTN相关的符号不是非特异性或无法区分的 很容易归因于有问题的降压。未能将这些AE与因果剂相关联 迅速治疗AE（称为“处方级联”）的及时疗法可能很重要 关于多药，不必要的成本，暴露于其他副作用的影响，治疗 不遵守和生活质量降低，尤其是在老年人中。迄今为止，大多数开处方的级联研究 狭窄地专注于具有高度特异性药物的知名AE的药物，严重限制 我们对处方级联的理解是由于不太知名或非特异性AE所致。这 方法导致知识产生缓慢，并错过了全面评估的机会 并发现新的处方级联。与NHLBI战略目标7一致，以“利用新兴 数据科学的机会开放研究中的新领域，”该提案旨在开发和利用 新颖的方法学方法，用于对开处方级联的高通量筛查并发现新颖的方法 使用全国代表性的行政索赔数据来源对级联的防潮性开处方。 该目标将通过以下目的实现：1）阐明候选人的抗高血压相关规定 使用副作用资源的级联反应，包括药物AES和 药物适应症； 2）确定在现实世界中使用抗高血压时发生的处方级联信号 使用Medicare数据库； 3）对级联信号检测进行分类，并通过 专家小组。预计拟议的工作将为1）识别和表征共同的大小 降压级别的降级，包括先前未知的级联； 2）开发一个有效的框架 用于大规模评估处方级联检测； 3）建立汇编的基础 已知的级联。该提案还逻辑地建立在将来的研究中，将此框架应用于 发现有心血管（和其他）治疗的处方级联的处方，评估下游 处方级联的后果和测试临床决策支持有助于防止开处方的后果 级联。