Biostatistics and Data Coordinating Core (BDCC)

核心C（生物统计学和数据管理）的目标是在以下方面提供专家生物统计学指导： 设计，进行和分析研究项目，包括P01，并提供可靠和准确的 涉及临床数据的项目的数据管理系统。核心C的目的是提供生物统计学 在研究的每个阶段为P01项目提供支持：在研究开始之前，核心工作人员将咨询 与调查人员一起帮助他们选择有效的设计和样本量， 解决研究目标。对于临床研究，他们将与研究人员合作，帮助建立有效的患者 招聘策略和设计案例报告表格，以明确的方式收集所有必要的信息， 路上了随着研究的进行，核心工作人员将协助审查项目数据库并监测 和收集的数据的质量，并将酌情建议对设计或分析计划进行修改。 研究完成后，核心将进行正确和有效的数据分析， 图表，协助研究人员准备演示文稿和手稿，并就 后续研究的设计。核心C的工作将与物理核心的工作接口， 临床项目期间的数据管理活动，以及作为实验室研究的动物核心， 计划和执行。核心C的工作人员有丰富的经验，支持癌症研究， 在基础科学，转化研究和临床试验方面有很强的背景， 他们是统计方法的研究者。凭借他们多年的PDT团队经验， 他们期待着进一步的合作机会，既适用现有的方法，也适应或 根据需要开发新方法。

The goals of Core C (Biostatistics and Data Management) are to provide expert biostatistical guidance in the design, conduct and analysis of research projects comprising the P01, and to provide a reliable and accurate data management system for projects involving clinical data. The aims of Core C are to provide biostatistical support to P01 projects at every stage of the research: Prior to the initiation of studies, Core staff will consult with investigators to help them select efficient designs and sample sizes that will give adequate power to address study objectives. For clinical studies, they will work with investigators to help set up effective patient recruitment strategies and design case report forms that collect all required information in an unambiguous way. As studies proceed, Core staff will assist in reviewing project databases and monitoring the quantity and quality of data collected, and will suggest modifications to the design or analysis plan as appropriate. When studies are finished, the Core will conduct correct and efficient data analyses, prepare any necessary graphs and tables, assist investigators with the preparation of presentations and manuscripts, and consult on the design of subsequent research. The work of Core C will interface with that of the Physics core providing data management activities during clinical projects, and with the Animal core as laboratory studies are planned and executed. The Core C staff members have extensive experience supporting cancer research, with strong backgrounds in basic science, translational research and clinical trials in addition to being themselves researchers in statistical methods. With their many years of experience with the PDT group, they look forward to further collaborative opportunities for both applying existing methods and adapting or developing new methods as needed.