Chronic Renal Disease-Individual Patient Meta Analysis

描述(申请人提供)：慢性肾脏疾病是一个世界性的公共卫生问题，发病率和患病率不断上升，结果很差，成本很高。这项研究应用的总体目标是使用个体患者数据荟萃分析来提供必要的证据，以改善慢性肾脏疾病患者的临床护理。目前的资助期集中于从血管紧张素转换酶抑制剂的随机临床试验中收集数据，以减缓非糖尿病肾脏疾病的进展。这项研究的开展产生了影响很大的原创文章，将研究结果纳入综述和临床实践指南，并创建了一个基础设施，以促进对与慢性肾脏疾病相关的其他主题的合作研究。在下一个赠款期间，将对慢性肾脏疾病患者诊断和管理的另一个核心问题--根据血清测量估计肾功能(肾小球滤过率，GFR)--应用个人患者数据荟萃分析。具体目标是1)建立广泛研究中的研究人员协作，在这些研究中，使用异硫氰酸酯的肾清除来测量GFR，并将单个患者的数据汇集到一个单一的数据库中。我们已经进行了合作，从研究研究中收集了6,000名患者的数据(&gt；31,000 GFR测量)，从临床人群中收集了14,000名患者的数据(&gt；23,000 GFR测量)。2)建立和验证了用血清肌酐预测GFR的方程。使用最先进的统计和实验室方法以及不同的患者群体，我们将能够严格评估这些方程在广泛的临床情况下的有效性。3)评估半胱氨酸氨基转移酶作为一种滤过标志物，并建立和验证利用血清半胱氨酸氨基转移酶预测肾小球滤过率的方程。4)使用新的公式估计美国人口中GFR水平下降的流行率。5)确定个人肾小球滤过率估计的精确度，并在估计人群中肾小球滤过率水平时纳入这些精确估计。首席研究员和合作研究员拥有肾病学、临床化学、生物统计学和流行病学方面的专业知识，并在解释GFR测量、实验室方法和完成该项目所需的统计技术方面拥有丰富的经验。这一结果将对慢性肾脏疾病患者的护理产生重大影响。

DESCRIPTION (provided by applicant): Chronic kidney disease is a worldwide public health problem, with increasing incidence and prevalence, poor outcomes and high cost. The overall aim of this research application is to use individual patient data meta-analysis to provide the evidence necessary to improve clinical care for patients with chronic kidney disease. The current grant period focused on pooling data from randomized clinical trials of angiotensin-converting-enzyme inhibitors to slow the progression of non-diabetic kidney disease. The conduct of this research has resulted in high impact original articles, incorporation of the findings into reviews and clinical practice guidelines, and creation of an infrastructure for stimulating collaborative research on other topics related to chronic kidney disease. In the next grant period will apply individual patient data meta-analysis to another problem central to the diagnosis and management of patients with chronic kidney disease - estimation of kidney function (glomerular filtration rate, GFR) from serum measurements. The specific aims are 1) Establish a collaboration of investigators from a wide range of studies in which GFR was measured using renal clearance of iothalamate and pool individual patient data into a single database. We have already secured collaborations to pool data on >6,000 patients (>31,000 GFR measurements) from research studies and > 14,000 patients (>23,000 GFR measurements) from clinical populations. 2) Develop and validate prediction equations using serum creatinine for estimating GFR. Using state of the art statistical and laboratory methods and diverse patient populations, we will be able to rigorously evaluate the validity of these equations in a wide range of clinical situations. 3) Assess cystatin as a filtration marker, and develop and validate prediction equations using serum cystatin for estimating GFR. 4) Use the new equations to estimate the prevalence of decreased GFR levels in the US population. 5) Characterize precision of GFR estimates in individuals and incorporate these precision estimates when estimating prevalence of GFR levels in populations. The principal investigator and co-investigators have expertise in nephrology, clinical chemistry, biostatistics, and epidemiology and have extensive experience with interpretation of GFR measurements, laboratory methods, and statistical techniques necessary to complete the project. The results will have a major impact on the care of patients with chronic kidney disease.