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.

核心2摘要 该方案项目包括四个单独的项目，将： 针对预计对初始治疗应答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作为早期标志物 （项目2）;描述无应答者的生物学特征，为治疗选择提供信息（项目 3）;并开发一系列药物和决策工具，用于与非肿瘤生物学相匹配的治疗重新分配。 肿瘤（Project 4）。生物信息学和统计学核心将作为一个集中资源， 这些项目的分析目标是一致的，我们不仅与每个项目组密切合作， 提供针对具体项目的分析支持，同时也构建跨多种模式的预测模型 （成像，分子概况及其组合），并促进跨项目的相互作用， 共同目标是建立稳健的决策算法，使治疗适应于个体女性 对他们最初的新辅助靶向和/或化疗反应差。这项工作将利用 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 验证算法，该算法将使过渡到I-SPY 2+，其中患者预测为不足 通过优化的、基于亚型特异性MRI的预测器“虚拟RCB”的应答者可以在治疗期间被识别。 初始治疗过程（完成紫杉醇+/-实验药物和2个周期AC治疗后），以及 根据其肿瘤生物学提供替代治疗策略，以减轻复发， 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 支持单个项目，促进跨项目分析和项目内成果共享 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和分析方法 项目需要实现其特定目标。 具体目标2：开发SMART（序贯、多重分配、随机试验）方法， 在I-SPY 2+计划项目框架内治疗预测的无应答者。 具体目标3：将项目内和项目间的生物标志物数据合成为可操作的临床信息。