Cancer Biostatistics (CB)

癌症生物统计学共享资源 摘要 癌症生物统计(CB)共享资源提供最先进的生物统计和研究设计 为亨斯迈癌症研究所的实验室、翻译、临床和人口科学研究人员提供支持 (人机界面)。它是犹他大学(U Of University)研究设计和生物统计中心(SDBC)的一个部门， 加州大学健康科学中心及其国立卫生临床和临床研究所的生物统计学核心 翻译科学奖支持的临床和翻译科学中心(CCTS)。 CB共享资源由Kenneth Boucher博士领导，他是一位有成就的生物统计学家和 自1996年起成为癌症中心成员，包括五名具有癌症研究专业知识的人员。 鲍彻博士与美国疾病控制与预防中心主任汤姆·格林博士密切合作，后者是 在NIH和行业赞助的多中心担任首席统计师超过25年的经验 临床试验和其他大规模多学科研究努力。 CB共享资源安排统计团队为研究过程的所有阶段提供支持 使癌症中心成员受益，为HCI研究人员提供综合的统计学和流行病学 研究设计、健康测量和数据分析方面的专业知识。这种专业知识包括临床试验和 观察性研究设计、纵向数据分析、线性和非线性混合效应模型、存活率 分析，多元方法，荟萃分析，贝叶斯模型，计算统计，诊断测试， 比较有效性研究，现代因果推理，调查设计和问卷开发， 项目反应理论和计算机适应性测验，以及统计遗传学和基因组学。除了……之外 CB共享资源提供统计分析，为研究的制定提供指导 目标，制定信息丰富和有效的研究设计，实施随机程序， 设计和实施调查、选择适当的工具和开发新的 衡量健康结果的工具，制定适当的收集程序和 安全地存储数据，在数据分析之前协作制定预先指定的分析计划，以及 在出版物和口头陈述中对数据进行解释和介绍。 CB共享资源位于HCI大楼，提供对资源的直接现场访问 用户在整个研究过程的所有阶段。CB共享资源的重要性在于 其广泛的用户范围和对众多出版物的贡献(其中许多是高调的)证明了这一点 日记。2013年，癌症中心研究人员通过同行评审资助使用CB共享资源 超过66%，而协调委员会的预算申请只占拟议预算总额的6%(46 388美元)。

CANCER BIOSTATISTICS SHARED RESOURCE ABSTRACT The Cancer Biostatistics (CB) Shared Resource provides state-of-the-art biostatistics and research design support to laboratory, translational, clinical, and population sciences investigators at Huntsman Cancer Institute (HCI). It is a section of the University of Utah (U of U) Study Design and Biostatistics Center (SDBC), the biostatistics core of the U of U Health Sciences Center and its National Institutes of Health Clinical and Translational Science Award-supported Center for Clinical and Translational Science (CCTS). The CB Shared Resource is led by Kenneth Boucher, PhD, an accomplished biostatistician and a Cancer Center member since 1996, and includes five personnel with specialized cancer research expertise. Dr. Boucher works in close coordination with Tom Greene, PhD, SDBC Director, a senior biostatistician with more than 25 years of experience serving as the lead statistician for NIH- and industry-sponsored multi-center clinical trials and other large-scale multidisciplinary research efforts. The CB Shared Resource arranges statistical teams to support all stages of the research process to benefit Cancer Center members, providing HCI researchers with integrated statistical and epidemiologic expertise in study design, health measurement, and data analysis. This expertise includes clinical trial and observational study design, longitudinal data analysis, linear and nonlinear mixed effects models, survival analysis, multivariate methods, meta-analysis, Bayesian models, computational statistics, diagnostic testing, comparative effectiveness research, modern causal inference, survey design and questionnaire development, item response theory and computer adaptive testing, and statistical genetics and genomics. In addition to providing statistical analyses, the CB Shared Resource provides guidance in formulation of research objectives, development of informative and efficient study designs, implementation of randomized procedures, design and implementation of surveys, selection of appropriate instruments and development of new instruments for measurement of health outcomes, development of appropriate procedures for collection and secure storage of data, collaborative formulation of pre-specified analysis plans prior to data analysis, and interpretation and presentation of data in publications and oral presentations. The CB Shared Resource is located in the HCI building, providing direct on-site access to resource users throughout all stages of the research process. The importance of the CB Shared Resource is demonstrated by its wide array of users and its contributions to numerous publications, many in high-profile journals. In 2013, use of the CB Shared Resource by Cancer Center investigators with peer-reviewed funding exceeded 66%, while the CCSG budget request is only 6% ($46,388) of the total proposed budget.