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Racial and ethnic differences in diabetes treatment and outcomes in US hemodialys

Racial and ethnic differences in diabetes treatment and outcomes in US hemodialys
美国血液透析中糖尿病治疗和结果的种族和民族差异
批准号:
8783373
负责人:
JINNIE J. RHEE
金额:
$5.15万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-08-13 至 2016-08-12

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中文摘要
翻译
描述(由申请方提供):在患有糖尿病(DM)的血液透析(HD)患者中,发生糖尿病相关并发症和死亡率的风险较高。然而,关于HD合并DM患者的糖尿病控制、治疗和糖尿病相关并发症之间相关性的数据非常有限。此外,这些关系中的种族和民族差异也没有记录。目的:本观察性研究的目的是评估HD合并DM患者的血糖控制、口服降糖药物(OAD)治疗与心血管和非心血管结局之间的关系。我们还将探讨这些协会中的种族和民族差异。方法:我们将使用美国肾脏数据系统的数据和DaVita,Inc.的电子病历,在一家大型国家级医疗机构对接受HD治疗的糖尿病患者进行回顾性队列研究, 透析服务,以检查HbA1c与各种临床结局之间的相关性(具体目标1和2)。这些患者的一个子集将用于接受TZD或磺脲类药物单药治疗的患者的比较有效性研究(特定目标3)。对于前两个目标,我们将使用考克斯比例风险模型评估HbA1c与至主要关注结局时间之间的相关性,并通过以下方法检验人种和种族的效应修饰: 包括交互作用项和执行Wald测试。我们将进一步探讨不同种族和民族群体之间的对比,找到显着的相互作用条款。为特定 目的3,我们将比较TZD的流行和偶发使用者与磺脲类药物的使用者,所有分析均限于接受这两种药物之一单药治疗的患者。我们将通过使用线性回归模型和稳健的三明治估计量进行重复测量分析,检查OAD单药治疗(TZD vs.磺脲类药物)与HbA1c之间的相关性。我们还将使用考克斯比例风险模型分析OAD单药治疗(TZD vs.磺脲类)与至心血管事件和死亡时间之间的相关性。除其他敏感性分析外,我们将进一步进行实际治疗和意向治疗分析,并采用先进的统计方法,包括倾向评分技术。将使用上述前两个目的的方法研究这些关联中的种族和民族差异。意义:本研究将利用一个异常庞大且详细的HD患者数据集。由于糖尿病管理和治疗(包括血糖控制和OAD治疗)与HD伴DM患者的糖尿病并发症之间相关性的数据有限,因此有必要在该高危人群中进行额外研究。此外,我们的研究将有能力在这些协会的种族和民族的差异,因为我们利用了巨大的数据库,将可用于分析。
英文摘要
DESCRIPTION (provided by applicant): In hemodialysis (HD) patients with diabetes mellitus (DM), the risk of developing diabetes- related complications and mortality is high. However, data on the associations among diabetes control, treatment, and diabetes-related complications in HD patients with DM are extremely limited. In addition, racial and ethnic differences in these relationships have not been documented. Objectives: The objective of this observational study is to assess the relationship among glycemic control, oral antidiabetic drug (OAD) therapy, and both cardiovascular and non-cardiovascular outcomes in HD patients with DM. We will also explore racial and ethnic differences in these associations. Methods: We will use data from the U.S. Renal Data System and electronic medical records of DaVita, Inc., to conduct a retrospective cohort study of patients on HD with diabetes mellitus at a large national provider of dialysis services to examine the associations among HbA1c and various clinical outcomes (Specific Aims 1 and 2). A subset of these patients will be used for a comparative effectiveness study of patients receiving TZD or sulfonylurea monotherapy (Specific Aim 3). For the first two aims, we will use Cox proportional hazards models to assess the associations between HbA1c and time to primary outcomes of interest, and test for effect modification by race and ethnicity by including interaction terms and performing a Wald test. We will further explore contrasts between different racial and ethnic groups upon finding significant interaction terms. For Specific Aim 3, we will compare prevalent and incident users of TZDs to users of sulfonylureas by limiting all analyses to patients receiving monotherapy with one of these two drug classes. We will examine the association between OAD monotherapy (TZD vs. sulfonylurea) and HbA1c by performing a repeated-measures analysis using linear regression models with a robust sandwich estimator. We will also analyze the association between OAD monotherapy (TZD vs. sulfonylurea) and time to cardiovascular events and death using Cox proportional hazards models. We will further conduct as-treated and intention-to-treat analyses in addition to other sensitivity analyses, and employ advanced statistical methods including propensity score techniques. Racial and ethnic differences in these associations will be investigated using the method described above for the first two aims. Significance: This research study will take advantage of an unusually large and detailed dataset of patients initiating HD. Due to the limited data on the associations among diabetes management and treatment, including glycemic control and OAD therapy, and diabetes complications in HD patients with DM, additional studies are warranted in this high-risk population. Moreover, our study will have the ability to investigat racial and ethnic differences in these associations as we capitalize on the enormous size of the database that will be available for analysis.
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