Risk stratification strategies and abbreviated MRI-based surveillance for early detection of HCC in high-risk AI/AN patients

用于早期检测高危 AI/AN 患者 HCC 的风险分层策略和基于 MRI 的简化监测

基本信息

批准号：
10286760
负责人：
George Ioannou
金额：
$ 26.26万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
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/10286760
关键词：
Alaska Native American Indians Biological Categories Cessation of life Cirrhosis Colorectal Cancer Development Early Diagnosis Epidemiology Face Feasibility Studies Foundations Functional disorder Genotype HBV Genotype Hepatitis B Hepatitis B Virus Incidence Magnetic Resonance Imaging Malignant Neoplasms Malignant neoplasm of liver Malignant neoplasm of lung Malignant neoplasm of prostate Maps Modeling Mutation Native-Born Patients Persons Pilot Projects Primary carcinoma of the liver cells Protocols documentation Randomized Controlled Trials Reporting Research Risk Risk Factors Role Testing Time Ultrasonography Veterans Health Administration Woman base cancer health disparity clinically significant cost effective disparity elimination high risk imaging modality improved individual patient innovation machine learning algorithm malignant breast neoplasm men mortality novel patient stratification prospective risk stratification screening surveillance strategy translational approach

项目摘要

ABSTRACT: PROJECT 2. Risk Stratification and abbreviated MRI-based surveillance This translational project will first investigate further the clinical significance of an HCC pathogenetic mechanism that we described, which is particularly important in AI/AN patients, i.e. HBV genotype-specific mutations. We will then use AI/AN-specific HCC risk factors described by our group (including HBV genotype and genotype- specific mutations) to develop AI/AN-specific “HCC Risk Calculators” for HCC risk stratification and risk-based surveillance. Finally, we will use HCC Risk Calculators to identify high-risk patients for more intensive surveillance strategies using abbreviated MRI, which will be tested in a pilot and feasibility RCT. The project will accomplish the following specific aims: SA1. Investigate the role of genotype-specific HBV mutations in the development of HCC in Alaska Native patients: Determine the development of HBV genotype-specific mutations in AN patients with different HBV genotypes prior to the occurrence of HCC compared to appropriate controls without HCC, and the excess HCC risk associated with these mutations. SA2. Develop and validate “HCC Risk Calculators” in AI/AN patients with HBV or cirrhosis using biological and demographic predictors specific to AI/AN patients for the purpose of risk stratification, identification of high-risk patients and personalized HCC surveillance strategies. SA3. Perform a pilot and feasibility randomized controlled trial of abbreviated MRI (aMRI) versus ultrasonography (US) for HCC screening in 200 AI/AN patients who have high HCC risk. SIGNIFICANCE. This project will set the foundation for “precision HCC screening” based on estimating HCC risk in individual patients using HCC Risk Calculators, risk stratifying patients according to their HCC risk, and developing specific HCC surveillance strategies for different categories of HCC risk. This will be developed and pursued further in a subsequent P50 application

摘要：项目2。风险分层和缩写基于MRI的监视这个翻译项目将首先进一步研究HCC致病机制的临床意义我们描述的是，这在AI/A/A的患者中尤为重要，即HBV基因型特异性突变。我们然后，将使用我们组描述的AI/AN AN AN特异性HCC风险因素（包括HBV基因型和基因型 - 特定突变）为HCC风险分层和基于风险的hcc风险分层开发AI/AN特异性“ HCC风险计算器” 监视。最后，我们将使用HCC风险计算器来识别高风险患者的更密集使用缩写的MRI进行监视策略，该策略将在试点和可行性RCT中进行测试。该项目将完成以下特定目标： SA1。研究基因型特异性HBV突变在阿拉斯加天然HCC发展中的作用患者：确定不同HBV患者中HBV基因型特异性突变的发展与没有HCC的适当对照相比，HCC发生之前的基因型和过量的HCC 这些突变相关的风险。 SA2。使用生物学和人口统计学预测因素是针对风险分层的目的，特定于AI/A的患者，高风险的识别患者和个性化HCC监视策略。 SA3。执行缩写MRI（AMRI）的飞行员和可行性随机对照试验超声检查（US）用于200个AI/A A/A A的HCC风险较高的患者进行HCC筛查。意义。该项目将根据估计HCC为“精确HCC筛查”奠定基础使用HCC风险计算器的个别患者的风险，根据患者的HCC风险对患者进行分层的风险，以及为不同类别的HCC风险开发特定的HCC监视策略。这将被开发在随后的P50申请中进一步追求