Optimizing long-term post-polypectomy surveillance for colorectal cancer prevention using a prediction rule developed from a large, community-based cohort

使用基于大型社区队列的预测规则优化长期息肉切除术后监测以预防结直肠癌

• 批准号: 9624487
• 负责人: Jeffrey Kuang Zou Lee
• 金额: $ 10.95万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-14 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9624487
• 关键词: Optimizing; long; term; post; polypectomy

PROJECT SUMMARY AND ABSTRACT The purpose of this K07 proposal is to provide Jeffrey Lee, MD, MAS with the protected time and resources to pursue the additional training needed to reach his long-term goal of becoming an independent clinical investigator, focused on colorectal cancer (CRC) prevention. Screening has been shown to reduce the incidence and mortality for CRC. However, screening has resulted in a growing cohort of patients with adenomatous polyps (adenomas) and little is known about effectively managing their post-polypectomy surveillance. With limited data available in the literature to determine the appropriate timing and frequency of follow-up colonoscopy for patients after adenoma removal, recommendations for post-polypectomy surveillance from our national guidelines have been imprecise at best. For example, the currently recommended range of 5-10 years for a surveillance colonoscopy for patients with a single adenoma covers a two-fold difference in exam frequency, with resultant two-fold impact on patient risk, cost, and colonoscopy capacity. To help optimize the timing of colonoscopic surveillance and guide appropriate utilization of this invasive and costly resource, stratification of CRC risk after colonoscopic polypectomy from a large community-based cohort with long-term follow-up is needed. Building on his prior work in CRC screening, Dr. Lee seeks to fill this knowledge gap by optimizing surveillance practices in post-polypectomy patients according to patient-, polyp-, and colonoscopy exam-related factors. Specifically, he will determine the long- term CRC risk in patients after colonoscopic polypectomy in a very large “real world” community-based population (Aim 1). He will also identify patient-, polyp-, and exam-related risk factors associated with incident CRC in these patients (Aim 2). Finally, he will develop a CRC risk prediction model that will identify post- polypectomy patients at high and low risk for developing subsequent CRC (Aim 3). To achieve these goals, Dr. Lee and his mentors have designed a career development plan for research and educational training to obtain: 1) knowledge and expertise in advanced epidemiologic methods for design and analysis of cohort studies; 2) knowledge in medical informatics methods; and 3) predictive modeling skills. To achieve the proposed research aims, Dr. Lee will leverage the rich electronic health records of Kaiser Permanente Northern California, a large community-based healthcare system, in which data on patient, physician, colonoscopy, pathology, and CRC status have been collected since 1994. In addition, Dr. Lee will use an established natural language processing tool to efficiently collect data and evaluate potential confounding variables from more than 600,000 colonoscopy reports in order to address one of the main practical challenges that have limited the feasibility of large-scale population-based studies. Thus, completion of these aims has the potential to improve prevention and early detection of CRC, impact current surveillance guidelines for post-polypectomy patients, and reduce overuse and underuse of surveillance colonoscopy. Importantly, this proposal is realistic and feasible within the award period and will allow Dr. Lee to continue to build research skills, generate preliminary data, create additional collaborative relationships, and compete for R01 funding. In summary, this K07 award will support and accelerate the career development activities of Dr. Lee and allow him to successfully launch into the next phase of his career as an independent investigator.

项目摘要和摘要 该K07提案的目的是向MAS的Jeffrey Lee，MAS提供受保护的时间和资源 寻求达到成为独立临床的长期目标所需的额外培训 研究人员，专注于结直肠癌（CRC）预防。筛选已显示可减少 CRC的发病率和死亡率。但是，筛查导致越来越多的患者 腺瘤息肉（腺瘤）和关于有效管理其植物后切除术的知之甚少 监视。文献中可用的数据有限，以确定适当的时间和频率 去除腺瘤后患者的随访结肠镜检查，植物后切除术的建议 我们国家准则的监视充其量是暗示的。例如，当前 针对单个腺瘤患者进行监视结肠镜检查的建议范围为5 - 10年 考试频率差异两倍，导致对患者风险，成本和结肠镜检查的两倍影响 容量。为了帮助优化结肠镜检查的时机，并指导对此的适当利用 侵入性且昂贵的资源，结肠镜检查后CRC风险分层的大型资源 需要长期随访的基于社区的队列。在他先前在CRC筛查中的工作，博士 Lee试图通过优化型后切除术患者的监视实践来填补这一知识差距 根据患者，息肉和结肠镜检查相关的因素。具体来说，他将确定长期 结肠镜息肉切除术后患者的术语CRC风险在非常大的“现实世界”社区中 人口（目标1）。他还将确定与事件相关的患者，息肉和检查相关的危险因素 这些患者的CRC（AIM 2）。最后，他将开发一个CRC风险预测模型，该模型将确定 息肉切除术患者患有高和低风险的患者出现随后的CRC（AIM 3）。为了实现这些目标，博士 Lee和他的导师为研究和教育培训设计了一项职业发展计划： 1）用于研究和分析研究的高级流行病学方法的知识和专业知识； 2） 医学信息方法的知识； 3）预测建模技巧。为了实现拟议的 研究目的，李博士将利用北北部的富裕电子健康记录 加利福尼亚州是一种大型社区医疗保健系统，其中患者，物理，结肠镜检查的数据 自1994年以来，已经收集了病理和CRC状态。此外，李博士将使用既定的自然 语言处理工具有效地收集数据并评估潜在的混杂变量 超过600,000个结肠镜检查报告，以解决限制的主要实际挑战之一 大型基于人群的研究的可行性。这是这些目标的完成有可能 改善预防和早期检测CRC，影响当前的监视后型后切除术指南 患者，减少过度使用和不足监测结肠镜检查。重要的是，该提议是现实的 并且在奖励期内可行，并将允许Lee博士继续建立研究技能，并产生 初步数据，创建其他协作关系，并争夺R01资金。总而言之，这 K07奖将支持和加速Lee博士的职业发展活动，并允许他 成功地进入了他职业生涯的下一阶段，担任独立调查员。