High-throughput screening for antihypertensive prescribing cascades

抗高血压处方级联的高通量筛选

基本信息

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
项目类别：
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

项目摘要

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.

项目概要近一半的美国成年人患有高血压 (HTN)，并接受超过 300 万抗高血压药物治疗尽管常用的抗高血压药物通常耐受性良好，但在美国每天都会开处方药，它们的普遍使用使数百万成年人面临潜在的限制治疗的不良事件（AE），其中一些这些都是众所周知的，但许多都是非特异性的或与高血压相关症状无法区分，并且不是未能将这些不良事件与致病因素联系起来可能很容易归因于不良抗高血压药物。提示额外的治疗来治疗 AE（称为“处方级联”），具有潜在的重要作用有关多重用药、不必要的费用、额外副作用、治疗的影响不依从，并降低生活质量，尤其是迄今为止大多数处方级联研究。狭隘地集中于具有众所周知的 AE 的药物，该 AE 对该药物具有高度特异性，严重限制了我们对由于不太知名或非特异性不良事件而发生的处方级联的理解。这种方法导致知识生成缓慢并错失了全面评估的机会并发现新的处方级联，符合 NHLBI 战略目标 7“利用新兴市场”。数据科学中开辟研究新领域的机会”，该提案旨在开发和利用用于高通量筛选处方级联的新方法学方法并发现新的使用具有全国代表性的行政索赔数据源进行抗高血压处方级联。这一目标将通过以下目标实现：1）阐明候选抗高血压相关处方使用 SIDe Effect Resource 进行级联，该资源是处方标签的集合，其中包括药物 AE 和药物适应症；2) 识别现实世界使用抗高血压药期间发生的处方级联信号使用医疗保险数据库；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 1) 确定并描述共同的程度。抗高血压处方级联，包括以前未知的处方 2) 制定有效的框架；对处方级联检测进行大规模评估；3) 为处方级联检测奠定基础；该提案还逻辑地构建了应用该框架的未来研究。发现心血管（和其他）治疗的级联处方，评估下游处方级联的后果，并测试临床决策支持辅助工具以防止处方级联。