Biostatistics Core

生物统计学核心

• 批准号: 10286762
• 负责人: Ziding Feng
• 金额: $ 11.01万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-06 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10286762
• 关键词: Address; Alaska Native; American Indians; Back; Bayesian Method; Biological Markers; Biometry; Biostatistics Core; Blinded; Cessation of life; Colorectal Cancer; Communication; Communities; Custom; Data Analyses; Data Element; Data Management Resources; Data Scientist; Data Set; Data Sources; Development; Early Diagnosis; Ensure; Epidemiology; Evaluation; Face; Functional disorder; Funding; Future; Goals; Guidelines; Health Sciences; Hepatitis B Virus; Home; Incidence; Individual; International; Leadership; Machine Learning; Malignant Neoplasms; Malignant neoplasm of liver; Malignant neoplasm of lung; Malignant neoplasm of prostate; Maps; Methods; Modeling; Mutation; Native-Born; Pathology; Patients; Persons; Phase; Play; Population; Primary carcinoma of the liver cells; Public Health; Publications; Reporting; Reproducibility; Research; Research Design; Research Personnel; Resources; Role; Screening for Hepatocellular Cancer; Screening for cancer; Services; Statistical Data Interpretation; Systematic Bias; Time; Validation; Visualization software; Woman; Work; biobank; biomarker development; biomarker discovery; cancer health disparity; clinical application; clinically relevant; cohort; computerized data processing; data harmonization; data management; data visualization; design; disparity elimination; early detection biomarkers; experience; improved; innovation; interest; malignant breast neoplasm; men; mortality; novel; prospective; risk prediction model; sample collection; translational approach

ABSTRACT: BIOSTATISTICS CORE The Biostatistics Core (BC) will support the study design, data processing, and analysis needs for individual projects as well as enhance interactions among all the projects in the P20. Experience has shown that involvement of biostatisticians and data scientists from the concept phase yields studies that are better designed, more likely to answer the scientific questions of interest, and, ultimately, more compelling in their conclusions. The goal of the Biostatistics Core is to support the investigators through all phases of their studies from design to publication via the following Specific Aims. Specific Aim 1: Study Design The BC will employ the 5-phase early detection biomarker development guideline as well as the PRoBE study design standards in order to help the P20 team establish a road map and research strategies for improving liver cancer early detection in AI/AN patients. The use of the 5-phase guideline will allow P20 investigators to strategize and make long-term plans, helping move biomarkers from discovery phases 1-2 to validation phases 3-5, fulfilling the translational continuum. Adhering to PRoBE standards will guide the study design driven by intended clinical application, reducing systematic bias, and ensuring a high likelihood of reproducible and clinically relevant study conclusions. Specific Aim 2: Analysis and Interpretation The BC will play a leadership role in statistical analysis and interpretation for the proposed Li-CAD P20 projects. The BC will identify and implement quantitative methods to address the scientific questions of interest and provide valid statistical inferences about the evidence addressing the various study hypotheses. For example, Parametric Empirical Bayesian (PEG) and Multivariate Fully Bayesian (mFB) approaches will be used to model longitudinal biomarkers, which will be used to build risk prediction models for the early detection of HCC in AI/AN population. Additionally, data visualization will be conducted to investigate HBV mutations, and state-of-the-art machine learning approaches will be utilized to develop and validate HCC risk prediction models in AI/AN persons. The BC will also work with study investigators to clearly communicate methods and results in study publications and insure that reported conclusions are justified. Specific Aim 3: Promote Interactions with DRP and Other Cores The BC will interact with the DRP as well as the Biospecimen and Pathology Core to ensure efforts within the Li-CAD P20 are on track, including all proposed P20 projects as well as DRP projects. The BC leader will communicate directly with the P20 Executive Committee to ensure any decision that has statistical implications has appropriate and timely inputs from the Core.

摘要：生物统计学核心 生物统计学核心（BC）将支持个人的研究设计，数据处理和分析需求 项目以及P20中所有项目之间的互动。经验表明 概念阶段的生物统计学家和数据科学家的参与产生了更好的研究 设计，更有可能回答感兴趣的科学问题，并最终更引人注目 结论。生物统计学核心的目的是通过其所有研究阶段来支持研究人员 从设计到出版物通过以下特定目标。 特定目标1：研究设计 卑诗省将采用5阶段的早期检测生物标志物开发指南以及探测研究 设计标准是为了帮助P20团队建立路线图和研究策略以改善 肝癌在AI/A/A的患者中早期检测。使用5阶段指南将允许P20调查人员能够 制定并制定长期计划，帮助将生物标志物从发现阶段1-2转移到验证阶段 3-5，实现翻译连续性。遵守探测标准将指导研究设计。 预期的临床应用，减少系统偏见，并确保可再现的可能性很高 临床相关的研究结论。 特定目的2：分析和解释 卑诗省将在拟议的LI-CAD P20项目的统计分析和解释中发挥领导作用。 卑诗省将识别并实施定量方法，以解决感兴趣的科学问题和 提供有关解决各种研究假设的证据的有效统计推断。例如， 参数经验贝叶斯（PEG）和多元完全贝叶斯（MFB）方法将用于建模 纵向生物标志物，将用于建立AI/AN中HCC早期检测的风险预测模型 人口。此外，将进行数据可视化以研究HBV突变和最先进的 机器学习方法将用于开发和验证AI/AN中的HCC风险预测模型 人。卑诗省还将与研究研究人员合作，清楚地传达方法和研究结果 出版物和确保报告结论是合理的。 特定目标3：促进与DRP和其他核心的互动 卑诗省将与DRP以及生物测量和病理学核心互动，以确保努力 LI-CAD P20正在步入正轨，包括所有拟议的P20项目以及DRP项目。卑诗省的领导人将 直接与P20执行委员会沟通，以确保任何具有统计意义的决定 从核心具有适当及时的输入。