Biostatistics and Data Coordinating Core (BDCC)

核心C（生物统计学和数据管理）的目标是为组成P01的研究项目的设计、实施和分析提供专业的生物统计学指导，并为涉及临床数据的项目提供可靠和准确的数据管理系统。Core C的目标是在研究的每个阶段为P01项目提供生物统计学支持：在研究开始之前，Core工作人员将与研究人员协商，帮助他们选择有效的设计和样本量，以提供足够的力量来实现研究目标。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募策略，并设计病例报告表格，以明确的方式收集所有所需的信息。随着研究的进行，核心工作人员将协助审查项目数据库和监测所收集数据的数量和质量，并将酌情对设计或分析计划提出修改建议。研究完成后，核心将进行正确有效的数据分析，准备必要的图表和表格，协助研究者准备演示文稿和手稿，并就后续研究的设计提供咨询。核心C的工作将与物理核心对接，在临床项目中提供数据管理活动，并与动物核心对接，作为实验室研究的计划和执行。Core C的工作人员在支持癌症研究方面有着丰富的经验，他们在基础科学、转化研究和临床试验方面有着强大的背景，此外他们自己也是统计方法方面的研究人员。凭借他们在PDT团队的多年经验，他们期待着进一步的合作机会，既可以应用现有方法，也可以根据需要调整或开发新方法。

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.