Empirical Likelihood Bayes Analysis of Quantile Regression Model

分位数回归模型的经验似然贝叶斯分析

• 批准号: 7739837
• 负责人: Mi-Ok Kim
• 金额: $ 8.31万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7739837
• 关键词: Accounting; Acute Lymphocytic Leukemia; Address; Adult; Affect; Age; Autologous Bone Marrow Transplantation; Bayesian Method; Body mass index; Cancer Patient; Cancer Survivor; Cancer and Leukemia Group B; Cephalic; Childhood Acute Lymphocytic Leukemia; Childhood Cancer Survivor Study; Cohort Studies; Computational algorithm; Computer software; Data; Data Analyses; Diagnosis; Disease; Disease-Free Survival; Dose; Environmental Risk Factor; Future; Gender; Generic Drugs; Genetic; Hand; Health; High Dose Chemotherapy; High-Risk Cancer; Intervention; Knowledge; Lead; Malignant Childhood Neoplasm; Methodology; Methods; Modeling; Morbidity - disease rate; Obesity; Overweight; Patients; Predisposition; Radiation therapy; Randomized Clinical Trials; Regression Analysis; Relative (related person); Research; Research Design; Risk; Risk Factors; Role; Siblings; Survivors; Testing; Time; Treatment Protocols; Woman; base; cancer epidemiology; cancer therapy; chemotherapy; childhood cancer survivor; design; epidemiology study; falls; hazard; high risk; improved; innovation; malignant breast neoplasm; mortality; obesity risk; outcome forecast; patient population; prospective; public health relevance; software development; tool; treatment effect; trial comparing

DESCRIPTION (provided by applicant): The purpose of this study is reanalyzing the Childhood Cancer Survivors Study (CCSS) and the Cancer and Leukemia Group B (CALGB) study 9082 data using an innovative Bayesian method for quantile regression (QR) and censored QR model. The CCSS and the CALGB study 9082 are concerned with two important questions of cancer epidemiology, respectively, identifying and assessing risk factors for modifiable disease and weighing more aggressive cancer treatment against less aggressive one. The primary analyses of the studies were constrained by the study design or the choice of statistical analysis method and fell short of adequately answering their respective research questions. Reanalyzing these studies is well warranted by appropriately addressing such constraints. We will use an innovative Bayesian (censored) QR method. It replaces the likelihood with empirical likelihood within the Bayesian analytic framework and conducts (censored) QR analysis. It will be a method, the first and only regarding the censored QR and one among a few regarding the uncensored QR, that accommodate all the features that are essential to adequately reanalyze the CCSS and the CALGB study 9082 data. It will also provide an alternative analytic tool for many other cancer epidemiology studies where standard regression or survival data analysis methods fail or are deemed insufficient. This study will improve our understanding of, respectively, obesity related future health risks in the childhood acute lymphoblastic leukemia (ALL) survivors and the role of cranial radiotherapy, and of the relative benefit of the high dose chemotherapy (with autologous bone marrow transplantation) in women with high risk breast cancer. This knowledge will consequently lead to better designed treatment protocols and intervention strategies that will increase survival and minimize harmful health effects in pediatric cancer and high risk breast cancer patient populations. PUBLIC HEALTH RELEVANCE: The purpose of this study is reanalyzing the Childhood Cancer Survivors Study (CCSS) and the Cancer and Leukemia Group B (CALGB) study 9082 by using an innovative Bayesian method for quantile regression and censored quantile regression model. The proposed analyses will improve our understanding of, respectively, obesity related future health risks in the childhood acute lymphoblastic leukemia (ALL) survivors and the role of cranial radiotherapy, and of the relative benefit of high dose chemotherapy with autologous bone marrow transplantation in women with high risk breast cancer.

描述（由申请人提供）： 这项研究的目的是重新分析儿童癌症幸存者研究（CCSS）和癌症和白血病B组（CALGB）研究9082数据，使用创新的贝叶斯分位数回归方法（QR）和审查QR模型。 CCSS和CALGB研究9082分别涉及两个重要的癌症流行病学问题，这些问题识别和评估可修改疾病的危险因素，并为更侵略性的癌症治疗与较少侵略性的疾病进行权衡。研究的主要分析受研究设计或统计分析方法的选择限制，并且没有充分回答其各自的研究问题。通过适当解决此类限制，可以很好地保证对这些研究进行重新分析。我们将使用创新的贝叶斯（审查）QR方法。它用贝叶斯分析框架内的经验可能性替代了可能性（审查）QR分析。这将是一种方法，第一个也是关于未经审查的QR的QR的第一个也是唯一的方法，它适用于充分重新分析CCSS和CALGB研究9082数据所必需的所有功能。它还将为许多其他癌症流行病学研究提供一种替代分析工具，其中标准回归或生存数据分析方法失败或认为不足。这项研究将分别提高我们对肥胖症与肥胖相关的未来健康风险的理解，在儿童急性淋巴细胞白血病（ALL）幸存者和颅性放疗的作用以及高剂量化学疗法（自体骨髓移植）对高风险乳腺癌的女性中的相对益处。因此，这些知识将导致更好地设计的治疗方案和干预策略，从而增加生存率并最大程度地减少儿科癌症和高风险乳腺癌患者人群的有害健康影响。 公共卫生相关性： 这项研究的目的是通过使用创新的贝叶斯方法来重新分析儿童癌症幸存者研究（CCSS）和癌症和白血病B组（CALGB）研究9082。提出的分析将分别提高我们对儿童急性淋巴细胞白血病（ALL）幸存者和颅骨放疗的作用以及高剂量化学疗法对高剂量骨髓移植的高剂量化学疗法对高剂量乳腺癌妇女对高风险乳腺癌的高剂量化学疗法的益处。