Biostatistics and Data Coordinating Core (BDCC)

生物统计和数据协调核心 (BDCC)

• 批准号: 7348015
• 负责人: Mary E. Putt
• 金额: $ 17.65万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-07 至 2013-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7348015
• 关键词: Address; Animal Model; Animals; Basic Science; Biometry; Biostatistics Core; Carcinomatosis; Case Report Form; Cell Line; Clinical; Clinical Data; Clinical Protocols; Clinical Research; Clinical Trials; Code; Collaborations; Computer software; Consult; Data; Data Analyses; Data Collection; Data Quality; Databases; Enrollment; Future; Generations; Goals; Graph; Heterogeneity; Human; Human Resources; Immunohistochemistry; In Vitro; Laboratories; Laboratory Study; Lead; Malignant Neoplasms; Malignant neoplasm of lung; Manuscripts; Maximum Tolerated Dose; Measures; Mediating; Methods; Microscopic; Modification; Monitor; Monoclonal Antibody C225; Non-Small-Cell Lung Carcinoma; Operative Surgical Procedures; Ovarian; Patient Recruitments; Patients; Pennsylvania; Peritoneal; Phase I Clinical Trials; Phase II Clinical Trials; Photochemotherapy; Physics; Physiological; Physiology; Pleural; Porfimer Sodium; Preparation; Procedures; Range; Reporting; Research; Research Design; Research Personnel; Research Project Grants; Research Proposals; Safety; Sample Size; Secondary to; Services; Specialist; Staging; Statistical Data Interpretation; Statistical Methods; Structure; System; Testing; Time; Toxic effect; Translational Research; Universities; Validation; Work; Writing; abstracting; anticancer research; clinical epidemiology; data management; design; experience; gastrointestinal; innovation; medical schools; member; multidisciplinary; preclinical study; professor; programs; quality assurance; tumor

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.

核心C（生物统计学和数据管理）的目标是在 由P01组成的研究项目的设计，进行和分析，并提供可靠，准确的 用于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 在研究的每个阶段对P01项目的支持：在启动研究之前，核心人员将咨询 与调查人员一起帮助他们选择有效的设计和样本量，这将赋予足够的权力 解决研究目标。对于临床研究，他们将与研究人员合作，以帮助建立有效的患者 招聘策略和设计案例报告表格，以明确的明确收集所有必需的信息 方式。随着研究的进行，核心人员将协助审查项目数据库并监视数量 和收集的数据的质量，并将建议对设计或分析计划进行适当的修改。 研究完成后，核心将进行正确有效的数据分析，准备任何必要的 图形和桌子，协助​​调查人员准备演示和手稿，并咨询 随后的研究的设计。核心C的工作将与物理核心提供的工作 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是 计划和执行。 C核C工作人员拥有支持癌症研究的丰富经验， 除了是基础科学，转化研究和临床试验的强大背景 他们自己的统计方法研究人员。凭借他们在PDT小组的多年经验， 他们期待着应用现有方法和适应或 根据需要开发新方法。