Core F Biostatistics

生物统计核心-核心F：项目摘要/摘要 BIOCARD研究是一项纵向的观察性研究，对349名认知正常和 注册时主要为中年(平均年龄为57.1岁)。这些受试者现在已经被跟踪了长达27年。 该项目的总体目标是进一步推进临床前阿尔茨海默病的研究 通过：(1)澄清AD生物标志物(包括基于脑脊液、血液、MRI、 和PET成像)和认知；待研究的生物标记物包括几个有前途的新生物标记物 从血液、脑脊液和脑成像中提取。(2)通过与多家公司协作，最大限度地利用我们的数据 拥有可比较数据的研究小组，以及(3)提供公开可访问的数据、脑扫描和 生物标本，供该领域的研究人员使用。为了实现这些目标，我们建立了7个核心， 本申请，还包括2个项目。生物统计核心(F核心)负责监督 与BIOCARD研究相关的研究设计和统计分析。具体目标包括：(1) 为与研究有关的所有分析提供统计支持和专家统计咨询；(2) 采用和开发统计方法和分析工具来研究与临床前相关的生物标志物 阿尔茨海默病阶段，(3)设计和确定适当和稳健的分析方法进行分析 集成来自核心和项目的数据，(4)提供电力计算、样本大小估计 以及其他定量方法来检查新的生物标记物，这些标记物可能在即将到来的 资金周期，以及(5)将新开发的衡量标准，如综合分数，纳入数据文件 与外部调查人员分享。

BIOSTATISTICS CORE – CORE F: PROJECT SUMMARY/ABSTRACT The BIOCARD study is a longitudinal, observational study of 349 individuals who were cognitively normal and primarily middle aged (mean age=57.1) at enrollment. The subjects have now been followed for up to 27 years. The overall objectives of the project are to further advance the study of preclinical Alzheimer’s disease by: (1) clarifying the pattern and rate of change in AD biomarkers (including those based on CSF, blood, MRI, and PET imaging) and cognition; the biomarkers to be studied include several promising novel biomarkers derived from blood, CSF and brain imaging. (2) maximizing our data by working collaboratively with several research groups who have comparable data, and (3) providing a publicly accessible data, brain scans, and biological specimens, for researchers in the field. To accomplish these goals we established 7 Cores and, with this application, are also including 2 projects. The Biostatistics Core (Core F) is responsible for overseeing the study design and statistical analyses related to the BIOCARD study. The specific aims include: (1) to provide statistical support and expert statistical consultation for all analyses associated with the study, (2) to adopt and develop statistical methods and analytical tools to study biomarkers associated with the preclinical phase of Alzheimer’s disease, (3) to design and identify proper and robust analytical approaches to analyze integrated data from across the Cores and Projects, (4) to provide power calculations, sample size estimates and other quantitative approaches to examining new biomarkers that might be identified during the coming funding cycle, and (5) to incorporate newly developed measures, such as composite scores, into the datafiles shared with external investigators.