Personalizing Post-Polypectomy Surveillance for Colorectal Cancer Prevention

个性化息肉切除术后监测以预防结直肠癌

基本信息

批准号：
10734405
负责人：
Jeffrey Kuang Zou Lee
金额：
$ 69.08万
依托单位：
KAISER FOUNDATION RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-19 至 2028-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10734405
关键词：
Address Adoption Advanced Development Age Attitude Benefits and Risks Cancer Detection Cancer Etiology Caring Categories Cessation of life Characteristics Clinical Clinical Data Collaborations Colon Colonoscopy Colorectal Cancer Communities Cost Analysis Coupled Data Diagnosis Early identification Eligibility Determination Evaluation Excision Family Future Genetic Genetic Databases Genetic Risk Genetic Services Genomics Genotype Goals Guidelines Health Services Research Incidence Individual International Knowledge Link Lung Managed Care Methods Neoplasms Outcome Pathologic Patients Performance Play Policies Polypectomy Polyps Precancerous Polyp Productivity Prostate Randomized, Controlled Trials Recommendation Recording of previous events Research Resources Risk Risk Estimate Risk Factors Risk Reduction Role Scheme Screening for Ovarian Cancer Screening for cancer Sensitivity and Specificity Techniques Technology Testing United States United States Preventative Services Task Force Unnecessary Procedures Validation Work clinical risk cohort colorectal cancer prevention colorectal cancer risk colorectal cancer screening comorbidity cost cost effective cost-effectiveness evaluation ethnic diversity experience follow-up genetic risk factor genome-wide high risk high risk population implementation barriers implementation facilitators improved indexing interest life time cost models and simulation mortality novel patient oriented personalized approach polygenic risk score population based pragmatic trial predictive modeling predictive tools racial diversity risk prediction risk prediction model risk stratification risk variant screening screening guidelines service providers sex surveillance strategy time interval

项目摘要

PROJECT SUMMARY AND ABSTRACT Screening is an established method for decreasing colorectal cancer (CRC) incidence and mortality. However, despite guidance supporting CRC screening initiation (i.e., 45 years), relatively little is known about what to do after a precancerous polyp is detected and removed. This is particularly concerning given that over 40% of individuals who undergo CRC screening are found to have a precancerous polyp and then instructed to undergo frequent colonoscopies (termed surveillance) every 3-10 years for CRC risk reduction. Current guidelines utilize a risk-stratification scheme that categorizes patients as high or low risk based only on polyp characteristics from their initial colonoscopy. However, polyp-based risk stratification methods are imprecise, with a sensitivity and specificity of 59-81% and 43-58%, respectively, for predicting subsequent advanced neoplasia after polyp removal. Thus, our current guideline-based risk stratification methods both miss high-risk individuals who may benefit from early surveillance and subject many low-risk individuals to unnecessary colonoscopies and its associated harms. Recent studies from our group and others have identified several clinical and genetic (i.e., polygenic risk score) risk factors associated with CRC; these may further optimize risk stratification following CRC screening and polyp removal, but remain understudied. For this R01 proposal, we will first develop and validate a practical, clinically useful risk prediction tool that incorporates both detailed polyp characteristics and other important predictors known to play an important role in CRC risk, such as clinical and genetic (i.e., polygenic risk score) risk factors (Aims 1 and 2). Second, we will identify optimal strategies for CRC surveillance given individual risk estimates defined in Aims 1-2 and evaluate the cost- effectiveness of different risk-stratified surveillance strategies compared to current guideline recommended polyp-based surveillance strategies (Aim 3). This Aim will leverage our ongoing collaboration with an established, internationally recognized micro-simulation model (MISCAN-Colon) that informs U.S. Preventative Task Force recommendations. Lastly, we will gain patient, clinician, and service provider’s perspectives on these novel comprehensive risk prediction methods, to optimize potential adoption, and assess potential implementation barriers and facilitators (Aim 4). This aim will incorporate group experiences with mixed methods techniques to identify attitudes and barriers of implementation. The overall aims will leverage comprehensive data from an extremely large contemporary community-based cohort and an independent cohort for validation. These cohorts’ detailed data include genome-wide genotype arrays coupled with prior screening, pathologic and clinical data, and surveillance outcomes. This study can substantially transform how we manage care for over 7 million patients diagnosed annually with precancerous polyps, personalize post- polypectomy surveillance using a new, novel, comprehensive, patient-centered risk prediction model, and optimize post-polypectomy surveillance to reduce CRC incidence and mortality.

项目概要和摘要筛查是降低结直肠癌 (CRC) 发病率和死亡率的既定方法。尽管支持 CRC 筛查启动指南（即 45 岁），但对于该做什么知之甚少鉴于超过 40% 的癌前息肉被检测并切除后，这一点尤其令人担忧。接受结直肠癌筛查的个体被发现患有癌前息肉，然后被指示每 3-10 年进行一次频繁的结肠镜检查（称为监测）以降低 CRC 风险。指南采用风险分层方案，仅根据息肉将患者分为高风险或低风险然而，基于息肉的风险分层方法并不精确，预测后续进展的敏感性和特异性分别为 59-81% 和 43-58% 因此，我们目前基于指南的风险分层方法都错过了高风险。可能从早期监测中受益的个人，并使许多低风险个人受到不必要的我们小组和其他人的最近研究发现了一些结肠镜检查及其相关危害。与 CRC 相关的临床和遗传（即多基因风险评分）风险因素可能会进一步优化风险； CRC 筛查和息肉切除后的分层，但对于此 R01 提案，我们仍在研究中。将首先开发并验证一种实用的、临床上有用的风险预测工具，该工具结合了详细的息肉特征和其他已知在结直肠癌风险中发挥重要作用的重要预测因素，例如临床和遗传（即多基因风险评分）风险因素（目标 1 和 2）其次，我们将确定最佳风险因素。考虑到目标 1-2 中的个体风险定义估计，制定 CRC 监测策略并评估成本与当前推荐指南相比，不同风险分层监测策略的有效性基于息肉的监测策略（目标 3）。该目标将利用我们与以下机构的持续合作。已建立的国际公认的微观模拟模型（MISCAN-Colon）为美国预防部门提供信息最后，我们将了解患者、临床医生和服务提供者的观点。这些新颖的综合风险预测方法，以优化潜在的采用并评估潜力实施和促进者（目标 4）。该目标障碍将包含混合的团体经验。确定态度和实施障碍的方法技术。来自极其庞大的当代社区群体的综合数据和独立的这些队列的详细数据包括全基因组基因型阵列以及先前的数据。这项研究可以极大地改变筛查、病理和临床数据以及监测结果。我们为超过 700 万诊断为癌前息肉的患者提供护理，个性化术后治疗使用新的、新颖的、全面的、以患者为中心的风险预测模型进行息肉切除术监测，以及优化息肉切除术后监测以降低结直肠癌的发病率和死亡率。