Core 02 - Statistics and Bioinformatics

核心 02 - 统计和生物信息学

• 批准号: 10013144
• 负责人: DONALD A BERRY
• 金额: $ 20.39万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-08 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10013144
• 关键词: Address; Algorithms; Archives; Berry; Bioinformatics; Biological Markers; Biology; Biometry; Breast Cancer Patient; Clinical Trials Design; Code; Data; Data Set; Data Storage and Retrieval; Documentation; Ensure; Goals; Image; Individual; Information Systems; Internet; Magnetic Resonance Imaging; Methods; Modality; Molecular Profiling; Neoadjuvant Therapy; New Agents; Outcome; Paclitaxel; Patients; Pharmaceutical Preparations; Recurrence; Reproducibility of Results; Research Personnel; Resource Allocation; Resources; Retreatment; Selection for Treatments; Sequential Multiple Assignment Randomized Trial; Sequential Treatment; Services; Statistical Models; System; Systems Integration; TimeLine; Tumor Biology; Woman; Work; alternative treatment; base; chemotherapy; clinically actionable; data sharing; design; evidence base; genomic data; high standard; high throughput analysis; imaging modality; improved; innovation; malignant breast neoplasm; member; model design; non-invasive imaging; predictive modeling; programs; repository; response; statistics; symposium; tool; treatment strategy; trial design; tumor; virtual

SUMMARY CORE 2 This Program Project comprises four individual projects, which will: implement evidence-based sequential multiple treatment assignment strategies for patients predicted to have insufficient response to their initial neoadjuvant targeted and/or chemotherapy (Project 1); qualify non-invasive imaging methods as early markers of non-response (Project 2); characterize the biology of non-responders to inform treatment selection (Project 3); and develop a portfolio of agents and decision tools for treatment re-assignment matched to biology of non- responding tumors (Project 4). The Bioinformatics and Statistics Core will act as a centralized resource where the analytical goals of these projects converge - where we work closely with each of the project groups not only to provide project-specific analytical support, but also to build predictive models across multiple modalities (imaging, molecular profiles and their combination) and facilitate cross-project interactions towards the common goal of building robust decision algorithms to enable adaptation of treatment for individual women with poor response to their initial neoadjuvant targeted and/or chemotherapy. This undertaking will utilize substantial the archived and newly generated datasets from the I-SPY 1 and I-SPY 2 trials to develop and validate algorithms that will enable the transition to I-SPY 2+, where patients predicted as insufficient responders by an optimized, subtype-specific MRI-based predictor “Virtual RCB” can be identified during the course of their initial therapy (after completion of their taxol +/- experimental agent and 2 cycles of AC) and offered alternative treatment strategies based on their tumor biology in order to mitigate recurrence and improve long term outcomes. The primary goal of the Biostatistics and Bioinformatics Core is to provide biostatistics and bioinformatics support to individual projects and facilitate cross-project analyses and results sharing within the Program Project Framework. The specific aims are listed as follows: Specific Aim 1: To provide innovative bioinformatics and statistical modeling and analytical approaches needed by the projects to achieve their Specific Aims. Specific Aim 2: To develop SMART (sequential, multiple assignment, randomized trial) methods for adaptive treatment of predicted non-responders within the I-SPY 2+ Program Project framework. Specific Aim 3: To synthesize biomarker data within and across projects into actionable clinical information.

摘要核心2 该方案项目包括四个单独的项目，它们将：实施循证顺序 预测对初始治疗反应不足的患者的多种治疗分配策略 新辅助靶向和/或化疗(项目1)；将非侵入性成像方法鉴定为早期标记 无应答(项目2)；描述无应答者的生物学特征，以指导治疗选择(项目 3)；并开发用于治疗重新分配的代理和决策工具组合，以与非 反应性肿瘤(项目4)。生物信息学和统计核心将作为一个集中的资源， 这些项目的分析目标是一致的--我们与每个项目组密切合作，不仅 提供特定于项目的分析支持，同时构建跨多个医疗设备的预测模型 (成像、分子轮廓及其组合)，并促进跨项目相互作用 共同目标是建立稳健的决策算法，以适应个别妇女的治疗 对最初的新辅助药物靶向和/或化疗反应差。这项承诺将利用 充实I-SPY 1和I-SPY 2试验的存档和新生成的数据集，以开发和 验证将实现向I-SPY 2+过渡的算法，而患者预测为不足 通过优化的、特定于亚型的基于MRI的预测器“虚拟RCB”，可以在 他们的初始治疗疗程(在完成紫杉醇+/-实验制剂和2个周期的AC之后)和 根据肿瘤生物学提供替代治疗策略，以减少复发和 改善长期结果。 生物统计和生物信息学核心的主要目标是提供生物统计和生物信息学 支持个别项目，并促进计划内的跨项目分析和成果共享 项目框架。具体目标如下： 具体目标1：提供创新的生物信息学和统计建模及分析方法 项目实现其特定目标所需的资源。 具体目标2：开发SMART(序贯、多次分配、随机试验)方法 在I-SPY 2+计划项目框架内对预测无应答者的治疗。 具体目标3：将项目内和项目间的生物标记物数据合成为可操作的临床信息。