Biostatistics & Research Informatics

生物统计学

• 批准号: 9113312
• 负责人: PHILIP WILLIAM LAVORI
• 金额: $ 28.26万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9113312
• 关键词: Basic Science; Big Data; Biological Markers; Biometry; Biostatistics Shared Resource; Clinical Data; Clinical Research; Clinical Trials; Clinical Trials Design; Clinical effectiveness; Collaborations; Computer software; Consultations; Data; Data Aggregation; Data Analyses; Data Sources; Databases; Development; Dose; Electronic Health Record; Engineering; Ensure; Faculty; Funding; Future; Goals; Healthcare Systems; Human Resources; Informatics; Information Resources; Institutes; Leadership; Learning; Malignant Neoplasms; Medicine; Methods; Monitor; Nature; Patients; Phase; Publications; Randomized; Registries; Research; Research Design; Research Institute; Research Personnel; Research Support; Research Technics; Resource Sharing; Review Committee; Sample Size; Scientist; Services; Site; Software Tools; Statistical Methods; Strategic Planning; Subgroup; Techniques; Translational Research; anticancer research; base; data management; design; effectiveness research; genetic association; improved; informatics shared resource; innovation; meetings; member; novel; point of care; programs; translational study

The objective of the Biostatistics and Research Informatics Shared Resource (BRISR) is to provide collaborative and consultative services to Stanford Cancer Institute investigators and thereby add value in all phases of cancer research. Capabilities include high-quality biostatistics consultation on the use of standard methods, as well as innovation in statistical methods specifically developed to enhance the basic and translational research efforts of a discovery-oriented SCI. The BRISR operates under the direction of Drs. Phil Lavori, Tze Lai and Ying Lu. As a dedicated shared resource, BRISR benefits SCI investigators in need of statistical and analytic collaboration and consultation in their studies. Since 2009 the shared resource has served more than 130 SCI members representing all eight research programs. Significant methodological contributions by faculty and staff in this funding period include the introduction of new methods in high dimensional data analysis and genetic association studies, software tools for distributed computation (to avoid the need to aggregate data), as well as innovative designs for clinical trials, including Point-of-Care randomization methods, seamless Phase I/II designs, novel Phase I Bayesian designs, designs for biomarker-guided therapies, adaptive choice of subgroup, seamless Phase II/III designs and sequential randomization. The Shared Resource has the additional responsibility for expanding and managing the Stanford Cancer Institute Research Database (SCIRDB). This database allows SCI researchers to collect, integrate, and analyze de-identified patient data from the electronic health record (EPIC) and from a wide range of other data sources and provides consultative services to ensure its optimal use. Shared Resource staff also advise on strategic issues with statistical and informatics content, such as criteria for scientific review and development of databases and registries, as well as the re-engineering of clinical and research informatics across Stanford Medicine and its affiliated networks.

生物统计学和研究信息学共享资源（BRISR）的目的是为斯坦福癌症研究所的研究人员提供协作和咨询服务，从而在癌症研究的所有阶段增加价值。功能包括有关使用标准方法的高质量生物统计学咨询，以及专门开发的统计方法的创新，以增强面向发现的SCI的基本和转化研究工作。 Brisr在Drs的指导下运作。 Phil Lavori，Tze Lai和Ying Lu。作为专门的共享资源，BRISR受益于SCI调查人员，需要在其研究中需要统计和分析协作和咨询。自2009年以来，共享资源已为代表所有八项研究计划的130多名SCI成员提供服务。 Significant methodological contributions by faculty and staff in this funding period include the introduction of new methods in high dimensional data analysis and genetic association studies, software tools for distributed computation (to avoid the need to aggregate data), as well as innovative designs for clinical trials, including Point-of-Care randomization methods, seamless Phase I/II designs, novel Phase I Bayesian designs, designs for biomarker-guided therapies, adaptive choice of亚组，无缝II/III期设计和顺序随机化。 共享资源对扩大和管理斯坦福癌症研究所研究数据库（SCIRDB）的额外责任。该数据库允许SCI研究人员从电子健康记录（EPIC）和广泛的其他数据源中收集，整合和分析具有去识别的患者数据，并提供咨询服务以确保其最佳使用。 共享资源人员还为有关统计和信息学内容的战略问题提供了建议，例如数据库和注册表的科学审查和开发标准，以及在斯坦福医学及其附属网络中重新研究临床和研究信息学。