Strengthening the Evidence-Base for Drug-Disease Interactions in Older Adults

加强老年人药物与疾病相互作用的证据基础

基本信息

批准号：
10617649
负责人：
Tobias Gerhard
金额：
$ 47万
依托单位：
RUTGERS BIOMEDICAL AND HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-15 至 2025-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10617649
关键词：
Adherence Adrenal Cortex Hormones Adverse drug effect Adverse effects Affect Allopurinol Biological Biology Case Study Characteristics Chronic Disease Clinical Clinical Medicine Clinical Trials Data Data Set Databases Diabetes Mellitus Dialysis procedure Disease Dose Drug Evaluation Drug Interactions Drug Kinetics Drug usage Effectiveness Elderly Electronic Health Record Epidemiologic Methods Eszopiclone Evaluation Evidence based practice Exclusion Exclusion Criteria Expert Opinion Fright Gastrointestinal Hemorrhage Guidelines Hepatic Hip Fractures Impairment Individual Kidney Kidney Transplantation Label Lactic Acidosis Link Literature Measures Medicare Metformin Methodology Methods Modernization Osteoporosis Outcome Patient-Focused Outcomes Patients Peptic Ulcer Performance Pharmaceutical Preparations Pharmacodynamics Physicians Polypharmacy Population Study Predisposition Prevalence Process Public Health Recommendation Regimen Research Research Design Risk Risk Reduction Safety Severities Statistical Methods Subgroup Symptoms System Taxonomy Testing Therapeutic Work Zaleplon adverse drug reaction adverse outcome aging population clinical decision-making clinical practice clinically relevant comorbidity computerized data resource design drug action drug classification evidence base evidence based guidelines fall risk fracture risk health service use improved individualized medicine innovation mortality multiple chronic conditions novel personalized medicine pharmacologic predict clinical outcome prevent treatment effect treatment guidelines treatment planning virtual zolpidem

项目摘要

Drug-disease interactions (DDSIs) occur when drug effects, such as risks for rare but severe adverse effects, are altered by a preexisting disease. DDSIs affect up to 50% of older adults and have been associated with increased mortality and use of health services. DDSIs are of particular concern in older adults because both polypharmacy and chronic illness become progressively more prevalent with advanced age. Although drug labels, treatment guidelines, and drug information compendia include warnings and contraindications for many thousands of drug-disease combinations, extremely little evidence and research exists on their clinical relevance. DDSI guidance generally relies on case reports, pharmacological mechanism, or structural similarity to related drugs, and thus commonly represents untested hypotheses rather than evidence from well-designed population-based studies. As a result, physicians and their patients are often unable to distinguish between warnings for clinically relevant DDSIs that should be followed to avoid increased risk for adverse drug effects, and warnings for purely theoretical DDSIs that should be ignored in order to allow initiation of treatment with the otherwise indicated drug of choice. Better evidence on DDSIs is thus urgently needed to allow physicians to recommend evidence-based personalized therapy for their patients. Using existing data resources on millions of patients from Medicare (US) and the Clinical Practice Research Datalink (UK), the proposed study will use four carefully selected examples of highly prevalent drugs to demonstrate a new methodological framework for the systematic assessment of DDSIs from large observational datasets: Metformin and renal impairment increasing risk of lactic acidosis (Aim 1), Z-drugs and osteoporosis increasing risk of hip fracture (Aim 2), systemic corticosteroids and peptic ulcer disease increasing risk of gastrointestinal bleeding (Aim 3), and allopurinol and renal impairment reducing risk of dialysis or kidney transplant (Aim 4). These examples were selected considering a number of explicit criteria including severity of the adverse outcome, disagreement about relevance in the literature and clinical practice, ability to measure disease and adverse clinical outcome in the databases, and availability of therapeutic alternatives that do not share the hypothesized DDSI. We included interactions across a spectrum of prevalence and expected effect sizes to evaluate the performance of the proposed approach in different situations and sought some effects very likely to be absent (Aim 1) or present (Aim 2) to show we can reproduce expected findings, and uncertain effects (Aims 3 and 4). The proposed study puts forward a novel framework that comprehensively classifies DDSIs according to their underlying biological mechanisms and represents the first systematic attempt to apply modern epidemiological and statistical methods to the examination of DDSIs. Its results will begin a line of work that will ultimately enable physicians to practice evidence-based personalized medicine by providing reliable data on the effects of patient-specific comorbidities on the safety and effectiveness of their therapeutic regimens.

当药物作用时，例如罕见但严重不良反应的风险，就会发生药物与疾病相互作用 (DDSI) 的影响，因先前存在的疾病而改变。 DDSI 影响多达 50% 的老年人，并且与随着死亡率和卫生服务使用量的增加。 DDSI 在老年人中尤其令人关注，因为随着年龄的增长，多重用药和慢性疾病变得越来越普遍。虽然药物标签、治疗指南和药物信息汇编包括警告和禁忌症数千种药物与疾病的组合，其临床证据和研究极少关联。 DDSI 指导通常依赖于病例报告、药理学机制或结构相似性相关药物，因此通常代表未经检验的假设，而不是精心设计的证据基于人群的研究。因此，医生和患者常常无法区分应遵循的临床相关 DDSI 警告，以避免增加药物不良反应的风险，以及纯理论 DDSI 的警告，应忽略这些警告，以便开始治疗另有说明的选择药物。因此，迫切需要关于 DDSI 的更好证据，以便医生能够为患者推荐基于证据的个性化治疗。利用现有数据资源拟议的研究涉及来自医疗保险（美国）和临床实践研究数据链（英国）的数百万患者将使用四种精心挑选的高度流行药物的例子来证明一种新的方法从大型观察数据集中系统评估 DDSI 的框架：二甲双胍和肾脏损伤增加乳酸酸中毒（目标 1）、Z 药物和骨质疏松症的风险增加髋部骨折的风险（目标 2），全身性皮质类固醇和消化性溃疡病增加胃肠道出血的风险（目标 3），别嘌呤醇和肾功能损害降低透析或肾移植的风险（目标 4）。这些例子选择时考虑了一些明确的标准，包括不良结果的严重程度、分歧关于文献和临床实践的相关性、测量疾病和不良临床结果的能力数据库中的数据，以及不共享假设的 DDSI 的治疗替代方案的可用性。我们包括一系列流行率和预期效应大小的相互作用来评估绩效在不同情况下分析所提出的方法，并寻求一些很可能不存在的效果（目标 1）或呈现（目标 2）以表明我们可以重现预期的结果和不确定的影响（目标 3 和 4）。这拟议的研究提出了一个新的框架，根据 DDSI 的特征对 DDSI 进行全面分类潜在的生物学机制，代表了应用现代流行病学的首次系统尝试 DDSI 检查的统计方法。其结果将开始一系列工作，最终将通过提供可靠的效果数据，使医生能够实施基于证据的个性化医疗患者特异性合并症对其治疗方案的安全性和有效性的影响。