Biostatistics Core

Biostastics Core的工作人员将负责为本项目的研究提供生物统计支持。生物统计核心由Timothy D博士监督。密歇根大学公共卫生学院生物统计学系的约翰逊说。该核心为该计划项目的临床前和临床实验的设计，分析和解释提供帮助。核心人员将与项目调查人员互动，以确保使用适当的设计和分析方法。设计问题涉及剂量选择、随机化、测量时间、动物或患者数量。对于数据分析，核心将确保使用有效的方法。将使用标准图形、组比较和相关分析方法对实验数据进行初步研究。混合模型方法将用于在涉及重复测量的实验中有效使用数据。核心人员在动物和临床数据的设计和分析方面经验丰富。这将确保从MR测量（项目1-3）、肿瘤组织学（项目1-2）、与治疗相关的细胞杀伤和生长变化（项目1-2）以及患者结局（项目3）中获得的所有数据都将得到有效收集和适当分析。Pub.健康状况：总的来说，这项研究工作将为启动联合分子靶向治疗恶性脑肿瘤的临床试验提供理论依据。此外，将确定和验证用于早期评估治疗反应的成像生物标志物，这将导致患者治疗的个体化。

The staff of the Biostastics Core will be responsible for providing biostatistical support to the research of this program. The Biostatistical Core is under the supervision of Dr. Timothy D. Johnson of the Biostatistics Department in the University of Michigan School of Public Health. The core provides assistance in the design, analysis and interpretation of preclinical and clinical experiments of the program project. Core personnel will interact with project investigators to ensure that appropriate designs and methods of analysis are used. Design issues involve selection of dose, randomization, timing of measurements, number of animals or patients. For analysis of data, the core will ensure that efficient methods are used. Standard graphical, group comparison and correlation methods of analysis will be used for initial investigation of the experimental data. Mixed model methods will be used for efficient use of the data in experiments involving repeated measures. Core personnel are experienced in the design and analysis of both animal and clinical data. This will ensure that all data obtained from MR measurements (Projects 1-3), tumor histology (Projects 1-2), cell kill and growth changes associated with therapy (Projects 1-2) and patient outcome (Project 3) will be collected efficiently and analyzed appropriately. Pub. Health: Overall, this research effort willprovide therationale for initiation of clinical trials with combinations of molecularly targeted therapies for the treatment of malignant brain tumors. In addition, imaging biomarkers for early assessment of treatment response will be identified and validated which will lead to individualization of patient treatmet.