Data Analysis

数据分析和建模小组提供放射性药物生物分布动力学的数学分析，作为研究和服务组成部分。特别是，我们将在未来五年内将残留物分析扩展到每个项目，并使用PET成像将新的异质性分析应用于肿瘤的表征。在治疗计划阶段，需要测试基于图像的信息的临床实用性，即PET衍生的测量有助于预测患者结果的附加信息。我们的每个假设都描述了一项观察性研究，包括成像数据、相关生物标记物的分析以及患者反应/存活的测量。我们的目标是确定可以在预测准确性方面实现临床上重要改进的成像程序，而不是现有的临床和诊断方法所达到的水平。由于改进的预测将具有明确的治疗意义，并且我们的结果将为这些假设在未来的合作临床试验中进行测试铺平道路，生物统计学的顾问在聚焦方案和指导预期合作前瞻性试验的数据分析方面发挥着关键作用。 为了提高生物统计学参与方案设计和假设检验的水平，这个新的数据分析核心将包括与F O‘Sullivan以及M Muzi和D Mankoff的当地领导的分包合同，以及L·凯斯勒的新努力，这对我们研究计划的质量和整体生产率至关重要。它将建立在我们的研究基础上，通过在一系列肿瘤组织学中的几个较小的患者试验来概括更成熟的显像剂的作用。我们的目标是制定一种策略，以说服癌症社区，特别是FDA，机械验证的显像剂可以与新的治疗试验并行使用。也就是说，显像剂的资格不应该是肿瘤特有的；它应该针对肿瘤表型的特定特征进行验证。我们的目标是提出一个令人信服的理由，即新的成像方法应该尽早投入治疗试验。最近为FDA工作的卫生政策专家L·凯斯勒最近加入了我们的教职员工，这对实现这一目标非常重要。

The data analysis and modeling group provides mathematical analysis of the kinetics of biodistribution of radiopharmaceutical as both a research and a service component. In particular, we will extend residue analysis to each of the projects over the next five years and apply novel heterogeneity analysis to the characterization of tumors using PET imaging. The clinical utility of image-based information needs to be tested in terms of what additional information the PET-derived measurements contribute to the prediction of patient outcome at the treatment planning stage. Each of our hypotheses describes an observational study with imaging data, assays of relevant biomarkers, and measures of patient response/survival. Our goal is to identify imaging procedures where a clinically important improvement in predictive accuracy, beyond that attained with existing clinical and diagnostic methods, can be achieved. Because the improved prediction will have clear therapeutic implications and our results will pave the way for these hypotheses to be tested in future cooperative clinical trials, the consultants in biostatistics play a critical role in focusing protocols and directing data analysis in anticipation of cooperative prospective trials. In order to increase the level of biostatistical involvement in protocol design and hypothesis testing, this new data analysis core will include a sub-contract with F O'Sullivan and the local leadership of M Muzi and D Mankoff plus new effort by L Kessler that are essential to the quality and overall productivity of our research program. It will build on our research to generalize the role of the more well established imaging agents through several smaller patient trials in a range of tumor histologies. Our goal is to develop a strategy to convince the cancer community in general and FDA in particular that mechanistically validated imaging agents can be used in parallel with new treatment trials. That is, qualification of an imaging agent should not be tumor-specific; it should be validated for a specific characteristic of the tumor phenotype.. Our goal is to make a convincing case that new imaging methods should be engaged in treatment trials sooner rather than later. The recent addition of L Kessler, a health policy expert who recently worked for FDA, to our faculty is important for this objective.