A Big Data Research Study on the Relationship Between Metformin Use and Dementia

二甲双胍使用与痴呆症关系的大数据研究

• 批准号: 9289078
• 负责人: Jeffrey F. Scherrer
• 金额: $ 20.63万
• 依托单位: SAINT LOUIS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-15 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9289078
• 关键词: Accounting; Address; African American; Age-Years; Aging; Amyloid beta-Protein; Animal Model; Antidiabetic Drugs; Big Data; Blood - brain barrier anatomy; Characteristics; Clinical; Cognitive; Comorbidity; Consensus; Data; Data Sources; Dementia; Diabetes Mellitus; Diagnosis; Dose; Electronic Health Record; Eligibility Determination; Ensure; Exclusion Criteria; Family; Gender; Glucose; Glycosylated hemoglobin A; Health; Healthcare Systems; Hispanics; Human; Insulin; Laboratories; Literature; Measures; Medical; Memory; Mentally Ill Persons; Metformin; Methods; Non-Insulin-Dependent Diabetes Mellitus; Observational Study; Oxidative Stress; Patients; Persons; Pharmaceutical Preparations; Pharmacology; Population; Prevalence; Probability; Procedures; Provider; Public Health; Randomized Controlled Trials; Recording of previous events; Reporting; Retrospective cohort; Retrospective cohort study; Risk; Risk Factors; Rodent Model; Sampling; Series; Severities; Societies; Sulfonylurea Compounds; System; Testing; Time; United States; United States Department of Veterans Affairs; Veterans; Weight; age group; analytical method; base; clinical practice; cohort; conditioned fear; cost; cost efficient; data resource; design; diabetic; epidemiology study; evidence base; follow-up; hazard; health administration; health care delivery; health data; high risk; improved; modifiable risk; novel; older patient; patient population; premature; prevent; protective effect; research study; volunteer

Dementia is a common and greatly feared condition associated with aging. In the United States, the prevalence of dementia is expected to nearly triple to 13 million persons by 2050. Type 2 diabetes mellitus (T2DM), a risk factor for dementia, is also rapidly increasing. Emerging data suggests the first line treatment for T2DM, metformin, may decrease dementia risk. In animal models, metformin improves memory and appears to protect against dementia. If this finding is established in humans, it could inform clinical decisions including how early in the course of diabetes to initiate metformin and whether to continue metformin when patients transition to insulin. However, definitive data are lacking. Randomized controlled trials (RCTs) have not been conducted to study whether metformin prevents dementia in humans. It would be premature to conduct an RCT given the current state of the literature and the high cost and long follow-up time required. Inconsistent results from extant observational studies may be due to inadequate control for confounding. The current proposal uses rich electronic health data resources from the Veterans Health Administration (VA) and Group Health (GH), an integrated healthcare system in the Northwest United States, to conduct a rigorous retrospective cohort study of the association between metformin use and incident dementia. We will use electronic health records (EHR) to identify a cohort of about 100,000 VA patients and 20,000 GH patients who have T2DM and are free of dementia and not taking diabetes medications at baseline. We will use a new user design and state of the art analytic methods including propensity scores and inverse probability of treatment weighting to control for potential confounding factors including diabetes severity. The long observation periods (17 years in VA and 20 years in GH) will ensure adequate power. The rich EHR data including diagnoses, procedures, laboratory and vital signs measures will enable us to control for many potential confounding factors such as hemoglobin A1c levels, medical and psychiatric comorbidities, and the use of concomitant medications. The primary analysis will use VA data, and findings will be replicated using GH data; independent replication in two unique large healthcare systems will improve the validity of our findings. We will address the following specific aims: 1. Compare risk of dementia in people initiating metformin for T2DM versus those initiating a sulfonylurea. 2. Compare risk of dementia in people initiating metformin vs. those delaying initial pharmacologic therapy, 3. Determine if the metformin – dementia association varies by age groups (50-65 vs. >65 years of age) and by gender. Exploratory analysis will investigate metformin dose and duration and risk of dementia. By using the same measures and methods to replicate results in very different patient populations, we will generate the strongest evidence to date regarding metformin’s potential to reduce risk of dementia. Results will inform provider-patient discussions about metformin use and could guide design of a subsequent, efficient RCT that targets people most likely to benefit from metformin.

痴呆症是与衰老相关的常见且极大的疾病。在美国， 到2050年，痴呆症的患病率预计将近三倍至1300万人。2型糖尿病 （T2DM）是痴呆症的危险因素，也正在迅速增加。新兴数据表明第一行处理 对于T2DM，二甲双胍可能会降低痴呆症风险。在动物模型中，二甲双胍可改善记忆力和 预防痴呆症的明显。如果该发现是在人类中建立的，则可以为临床决定提供信息 包括糖尿病启动二甲双胍的早期以及是否继续二甲双胍 患者过渡到胰岛素。但是，缺乏确定的数据。随机对照试验（RCT）具有 不再研究二甲双胍是否阻止人类痴呆症还为时过早。 鉴于文献的当前状态以及所需的高成本和较长的随访时间，进行RCT。 广泛的观察性研究的结果不一致可能是由于无法控制的混淆。 当前的提案使用退伍军人健康的丰富电子健康数据资源 美国西北部的综合医疗系统（VA）和集团健康（GH）， 进行严格的回顾性队列研究，对二甲双胍和入射之间的关联 失智。我们将使用电子健康记录（EHR）来确定大约100,000名VA患者的队列 有20,000名具有T2DM并且不含痴呆症的GH患者，并且在基线时不服用糖尿病药物。 我们将使用新的用户设计和最先进的分析方法，包括倾向分数和倒数 治疗加权的概率可以控制潜在的混杂因素，包括糖尿病严重程度。这 长时间的观察期（VA为17年，GH为20年）将确保足够的权力。丰富的EHR数据 包括诊断，程序，实验室和生命体征措施将使我们能够控制许多 潜在的混杂因素，例如血红蛋白A1C水平，医学和精神病合并症以及 使用伴随药物。主要分析将使用VA数据，并将使用 GH数据；在两个独特的大型医疗系统中的独立复制将提高我们的有效性 发现。我们将解决以下具体目标：1。比较痴呆症患者启动二甲双胍的风险 对于T2DM而言，与那些发起的磺酰脲。 2。比较引发二甲双胍VS的人的痴呆症风险。 那些延迟初始药理治疗的人，3。确定二甲双胍 - 痴呆症关联是否通过 年龄组（50-65 vs.> 65岁）和性别。探索性分析将研究二甲双胍剂量 持续时间和痴呆症风险。通过使用相同的措施和方法来复制结果 不同的患者人群，我们将产生有关二甲双胍潜力的迄今 降低痴呆症的风险。结果将为提供者与患者讨论有关二甲双胍使用的讨论，并可以指导 随后，有效的RCT的设计，该RCT的目标是最有可能受益于二甲双胍的人。