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.

痴呆症是一种常见的和非常可怕的与衰老有关的疾病。在美国 预计到2050年，痴呆症患病率将增加近两倍，达到1 300万人。2型糖尿病 2型糖尿病（T2 DM）是痴呆症的一个危险因素，也在迅速增加。新的数据表明一线治疗 对于T2 DM，二甲双胍可降低痴呆风险。在动物模型中，二甲双胍可改善记忆， 似乎可以预防痴呆症如果这一发现在人类中得到证实，它可以为临床决策提供信息。 包括在糖尿病病程中多早开始二甲双胍治疗， 患者过渡到胰岛素。然而，缺乏确切的数据。随机对照试验（RCT） 尚未进行二甲双胍是否预防人类痴呆症的研究。还为时过早 考虑到文献的当前状态以及所需的高成本和长随访时间，进行RCT。 现有观察性研究的不一致结果可能是由于对混杂因素的控制不足。 目前的提案使用了退伍军人健康中心丰富的电子健康数据资源。 管理（VA）和集团健康（GH），在美国西北部的综合医疗保健系统， 进行一项严格的回顾性队列研究，研究二甲双胍使用与事件之间的关系， 痴呆我们将使用电子健康记录（EHR）来识别约10万例VA患者的队列， 20，000名患有T2 DM且无痴呆且基线时未服用糖尿病药物的GH患者。 我们将使用一个新的用户设计和最先进的分析方法，包括倾向分数和逆 治疗加权概率，以控制潜在混杂因素，包括糖尿病严重程度。的 长观察期（VA为17年，GH为20年）将确保足够的把握度。丰富的EHR数据 包括诊断，程序，实验室和生命体征测量将使我们能够控制许多 潜在的混杂因素，如血红蛋白A1 c水平、医学和精神病合并症，以及 使用合并用药。主要分析将使用VA数据，结果将使用 GH数据;在两个独特的大型医疗保健系统中独立复制将提高我们的有效性。 调查结果。我们将致力于以下具体目标：1。比较开始服用二甲双胍的人患痴呆症的风险 与开始使用磺酰脲类药物的患者相比。2.比较开始使用二甲双胍与 那些延迟初始药物治疗的患者，3.确定二甲双胍与痴呆的关联是否因 年龄组（50-65岁与>65岁）和性别。探索性分析将研究二甲双胍剂量 以及痴呆症的持续时间和风险。通过使用相同的措施和方法， 不同的患者人群，我们将产生迄今为止关于二甲双胍 降低患痴呆症的风险。结果将告知提供者-患者关于二甲双胍使用的讨论， 设计一个后续的、有效的随机对照试验，以最有可能从二甲双胍中获益的人群为目标。