Training Program in Biostatistics for Cancer Research

描述（由申请人提供）：本申请是为了继续生物统计学的培训计划，特别关注癌症研究。该培训计划每年支持6名学生。生物统计学的实践正在发生变化，特别是在癌症领域 research.在过去的二十年里，对细胞生长和发育的分子、生物化学和遗传成分的发现改变了我们对正常细胞癌变和转移的理解。鉴于许多癌症的许多可用治疗方法，每种方法对一部分患者有效，这些信息有可能被用于个性化治疗，因此每个患者都可以接受最有可能使他们受益的治疗，因为他们的癌症分子特征。早期发现和预防工作也在许多癌症中取得进展，并显示出降低癌症死亡率和发病率的持续希望。用于在分子和遗传上测量肿瘤的新方法的发展已经导致了巨大的、复杂的数据集，其相关的生物信息难以提取，并且这些方法中的许多方法的复杂性和超灵敏度在设计获得可再现的测量和可复制的结果的研究方面提出了相当大的挑战。设计能够纳入这些信息并在患者治疗中考虑这些信息的临床试验是具有挑战性的，并且需要仔细处理许多定量问题。多学科研究团队是现代抗癌方法的核心，鉴于许多现代生物医学研究挑战的基本定量性质，生物统计学家和其他定量科学家发现自己是这些团队中越来越重要的一部分。这样的团队合作需要统计学家熟悉分子生物学家、病理学家，当然，如果合作研究者小组要成功的话，还有临床肿瘤学家。因此，有效的生物医学合作需要在统计学，概率，计算方法以及癌症生物学和医学伦理学方面进行广泛的培训。莱斯大学统计系和德克萨斯大学定量科学系的各个系。D.安德森癌症中心与他们在临床和基础科学方面的合作者联手开发了一个独特的培训计划，结合他们各自的优势，培训癌症研究中的生物统计学家。该生物统计学培训计划的目标是 培养新一代的生物统计学家，他们将与现代癌症研究中的生物医学研究人员并肩工作。我们的计划旨在为学员提供：-严格的统计和概率培训; - 在基础和临床癌症研究方面的实践经验; -在癌症生物学方面和医学研究伦理方面的培训。 该计划的学生遵循博士预期的标准课程。在赖斯统计系的学生，在生物统计学，生物学和伦理学的额外课程，以及在这两个机构的特别研讨会和讲习班。凭借贝叶斯方法，决策理论，癌症临床试验，癌症筛查，生存分析，统计遗传学，基因组学，生物信息学和统计计算方面的专业知识，学员将获得现代癌症研究所需的生物统计学的广泛背景。暑期实习和实验室轮换为学生的培训提供了实践经验。

DESCRIPTION (provided by applicant): This application is for continuation of a training program in biostatistics with a specific focus on cancer research. This training program supports six students each year. The practice of biostatistics is changing, especially in the area of cancer research. Discoveries over the past two decades into the molecular, biochemical, and genetic components of cell growth and development have changed our understanding of what makes a normal cell become cancerous, and then later metastasize. Given numerous available treatments for many cancers, each with efficacy for a subset of patients, this information has the potential to be leveraged to personalize therapy so each patient can be given the treatment that is most likely to benefit them given their cancer's molecular signature. Early detection and prevention efforts have also made inroads in numerous cancers, and demonstrate continuing promise to reduce mortality and morbidity due to cancer. The development of new methods for surveying a tumor molecularly and genetically have led to enormous, complex data sets whose relevant biological information is difficult to extract, and the intricacy and exceeding sensi- tivty of many of these methods raise considerable challenges in terms of designing studies that obtain reproducible measurements and replicable results. Designing clinical trials that can incorporate such information and take it into account in patient treatment is challenging, and requires many quantitative issues be carefully handled. Multidisciplinary research teams are at the heart of modern approaches to fighting cancer, and biostatisticians and other quantitative scientists find themselves as an increasingly crucial part of such teams, given the fundamental quantitative nature of many of the modern biomedical research challenges. Such teamwork requires that the statistician be conversant with molecular biologists, pathologists, and, of course, clinical oncologists if the group of co-investigators is to succeed. Effective biostatisticl collaboration thus requires broad training in statistics, probability, computational methods, as well as cancer biology and medical ethics. The Department of Statistics, Rice University, and the departments in the Division of Quantitative Sciences at the University of Texas M. D. Anderson Cancer Center have joined forces with their collaborators in the clinical and basic sciences to developed a unique training program that combines their respective strengths to train biostatisticians in cancer research. The goal of this Training Program in Biostatistics is to prepare a new generation of biostatisticians who will work side-by-side with biomedical investigators in modern cancer research. Our program aims to provide trainees with: - Rigorous training in statistics and probability; - Practical experience in basic and clinical cancer research; - Training in biological aspects of cancer and medical research ethics. Students in this program follow a standard course of study expected of Ph.D. students in the Department of Statistics at Rice, with additional coursework in biostatistics, biology, and ethics, as well as special seminars and workshops at both institutions. With faculty expertise in Bayesian methods, decision theory, cancer clinical trials, cancer screening, survival analysis, statistical genetics, genomics, bioinformatics, and statistical computing, trainees will receive a broad background in biostatistics necessary for modem cancer research. Summer internships and laboratory rotations provide practical experience in the student's training.