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：
10115556
负责人：
Tobias Gerhard
金额：
$ 56.24万
依托单位：
RUTGERS, THE STATE UNIV OF N.J.
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 2024-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10115556
关键词：
Adherence Adrenal Cortex Hormones Adverse drug effect Adverse effects Affect Allopurinol Biological Biology Case Study Characteristics Chronic Chronic Disease Clinical Clinical Medicine Clinical Trials Data Data Set Databases Diabetes Mellitus Dialysis procedure Disease Disease Outcome Dose Drug Evaluation Drug Interactions Drug Kinetics Drug usage Effectiveness Elderly Electronic Health Record Epidemiologic Methods Eszopiclone Evaluation Evidence based practice Exclusion Criteria Expert Opinion Fright Gastrointestinal Hemorrhage Guidelines Hepatic Hip Fractures Impairment Individual Kidney Kidney Transplantation Label Lactic Acidosis Literature Measures Medicare Metformin Methodology Methods Modernization Osteoporosis Outcome Patient-Focused Outcomes Patients Peptic Ulcer Performance Pharmaceutical Preparations Pharmacodynamics Pharmacology Physicians Polypharmacy Population Study Predisposition Prevalence Process Public Health Recommendation Regimen Research Research Design Risk Risk Reduction Safety Severities Statistical Methods Structure Subgroup Symptoms System Taxonomy Testing Therapeutic Work Zaleplon adverse drug reaction adverse outcome aging population base clinical decision-making clinical practice clinically relevant comorbidity computerized data resource design drug action evidence base evidence based guidelines fall risk fracture risk health service use improved individualized medicine innovation mortality novel personalized medicine 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（例如罕见但严重不良的风险）时，会发生药物疾病互动相互作用（DDSI）效果会因先前存在的疾病而改变。 DDSI会影响多达50％的老年人，并且已经关联随着死亡率增加和使用健康服务。 DDSI在老年人中特别关注随着年龄的增长，多药和慢性疾病都变得越来越普遍。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成千上万的药物疾病组合，几乎没有证据和研究的研究关联。 DDSI指导通常依赖于病例报告，药理机制或结构相似性相关药物，因此通常代表未经测试的假设，而不是精心设计的证据基于人群的研究。结果，医生及其患者通常无法区分应遵循临床相关DDSI的警告，以避免增加药物不良影响的风险，并警告纯粹的理论DDSI，应忽略，以便开始治疗原本指定的选择药物。因此，迫切需要关于DDSI的更好的证据以允许医生为患者推荐基于证据的个性化治疗。在现有的数据资源上使用拟议的研究将使用四个精心选择的高度普遍药物的例子来证明一种新的方法论从大型观察数据集对DDSIS进行系统评估的框架：二甲双胍和肾脏损伤增加了乳酸酸中毒的风险（AIM 1），Z-药物和骨质疏松症增加了髋部骨折的风险（AIM 2），全身性皮质类固醇和消化性溃疡疾病增加了胃肠道出血的风险（AIM 3），别嘌呤醇和肾功能减少透析或肾脏移植的风险（AIM 4）。这些例子选择了许多明确的标准，包括不良结果的严重性，分歧关于文献和临床实践中的相关性，测量疾病的能力和不良临床结果在数据库中，以及不共享假设DDSI的治疗替代方案的可用性。我们包括各种患病率和预期效应大小以评估性能的相互作用在不同情况下拟议的方法中，很可能缺乏某些影响（AIM 1）或现在（目标2）表明我们可以复制预期的发现和不确定的效果（目标3和4）。这拟议的研究提出了一个新颖的框架，根据他们的DDSIS对DDSIS进行了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和DDSIS检查的统计方法。它的结果将开始一系列工作，最终将使医生能够通过提供有关影响的可靠数据来实践基于证据的个性化医学有关其治疗方案的安全性和有效性的患者特异性合并症。