Core B- Biostat Core

摘要 概述：久坐时间和衰老研究（星星）计划生物统计学核心B将提供统一的 支持三个星星项目的信息学和统计需求。核心将最好地执行 数据收集和管理的实践，并采用严格的统计方法进行数据分析。的 具体目标是提供全面的信息学支持和数据管理， 沟通，进行数据分析，并开发适用于所有国家的新的统计方法。 星星项目。 信息学：生物统计学核心将协调和支持数据库的开发和维护， 星星项目。核心将进行广泛的数据验证、标准化监测和报告 跨星星项目，包括方案合规性、表格填写、应计报告、自动中期 数据质量检查、锁定和记录最终研究数据集。病人的隐私将是 保护.位于加州大学圣地亚哥分校超级计算机中心的星星信息系统符合HIPAA标准。 统计分析：生物统计学核心将提供严格的统一统计专业知识， 分析三个星星项目数据的最佳实践，包括意向治疗原则、纵向 数据分析和缺失数据方法。此外，生物统计学核心将开发和应用新的状态- 最先进的统计方法，与所有三个星星项目有关，包括模拟多个 纵向行为、生物标志物和健康结果。 新方法：利用客观生物标志物和24小时加速计测量，生物统计学 核心将整合跨星星项目的数据，并测试补充目标。我们将识别时间模式 健康行为（久坐行为，体力活动，睡眠）在绝经后妇女，并确定， 这些模式在参与干预试验后发生变化。同时，我们将开发算法来识别 “响应者”，即，在干预试验中生物标志物谱改善最大的参与者。我们 相信这些补充目的可以阐明健康行为积累是否/如何（例如，长期与 久坐行为或身体活动的中断）影响健康结果，并提供预测 确定可能的“反应者”的规则，这可以为未来试验的设计提供信息，并为 参与者需要最好地实现成功的行为改变和改善健康。 冲击总之，星星生物统计学核心将提供一个健全的，强大的和可重复的框架， 支持星星项目的总体目标：提高对 绝经后妇女不同样本中干预久坐行为的生物行为功效 妇女我们希望星星计划的发现最终将为以下公共卫生建议提供信息： 健康的生活

Abstract Overview: The Sedentary Time and Aging Research (STAR) Program Biostatistics Core B will provide unified support for informatics and statistical needs across the three STAR Projects. The core will implement best practices for data collection and management, and apply rigorous statistical methods for data analysis. The Specific Aims are to provide comprehensive informatics support and data management, enhance communication, and to conduct data analysis and develop novel statistical approaches applicable across STAR projects. Informatics: The Biostatistics Core will coordinate and support database development and maintenance for all STAR Projects. The core will undertake extensive data validation, standardized monitoring and reporting across STAR Projects, including protocol compliance, form completion, accrual reporting, automated interim data quality checks, locking and documenting of finalized study data sets. Patient confidentiality will be protected. The STAR informatics system, hosted at the UCSD Supercomputer center, is HIPAA compliant. Statistical Analysis: The Biostatistics Core will provide rigorous unified statistical expertise, implementing best practices to analyze data across the three STAR Projects including intent-to-treat principles, longitudinal data analysis, and missing data methods. In addition, the Biostatistics core will develop and apply novel state- of-the-art statistical methods, pertinent to all three STAR Projects, including methods for modeling multiple longitudinal behavioral, biomarker, and health outcomes. New Methodology: Leveraging objective biomarker and 24-hour accelerometer measures, the Biostatistics Core will integrate data across STAR Projects, and test supplemental aims. We will identify temporal patterns of health behaviors (sedentary behavior, physical activity, sleep) in postmenopausal women, and ascertain if these patterns change after participation in the intervention trials. Also, we will develop algorithms to identify “responders”, i.e., participants with the greatest improvement in biomarker profiles in the intervention trials. We believe these supplemental aims could elucidate if/how health behavior accumulation (e.g., long versus interrupted bouts of sedentary behavior or physical activity) impact health outcomes, and provide prediction rules to identify likely “responders,” which could inform design of future trials and tailor interventions to participant needs to best effect successful behavior change and improve health. Impact. In summary, the STAR Biostatistics Core will provide a sound, robust and reproducible framework for supporting the overall objective of the STAR Projects: to enhance scientific knowledge of and examine the biobehavioral efficacy of interventions to interrupt sedentary behavior in a diverse sample of postmenopausal women. We expect that STAR program findings will ultimately inform public health recommendations for healthy living.