Optimizing colorectal cancer prevention: a multi-disciplinary, population-based investigation of serrated polyps using risk prediction and modeling

优化结直肠癌预防：利用风险预测和建模对锯齿状息肉进行多学科、基于人群的调查

• 批准号: 10207552
• 负责人: Christopher I. Amos
• 金额: $ 60.89万
• 依托单位: DARTMOUTH-HITCHCOCK CLINIC
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10207552
• 关键词: Accounting; Address; Adenomatous Polyps; Advisory Committees; Age; Benign; Biological; Biometry; Calibration; Cancer Etiology; Cancer Intervention; Cause of Death; Cessation of life; Characteristics; Clinical; Clinical Management; Clinical effectiveness; Colon; Colonoscopy; Colorectal; Colorectal Cancer; Data; Databases; Detection; Development; Digestive System Disorders; Effectiveness; Endoscopy; Family; Future; Goals; Growth; Guidelines; Incidence; International; Interruption; Investigation; Knowledge; Lesion; Link; Literature; Location; Malignant Neoplasms; Modeling; Natural History; New Hampshire; Outcome; Painless; Pathology; Pathway interactions; Patient risk; Patients; Polyps; Precancerous Polyp; Preventive service; Procedures; Public Health; Recommendation; Recording of previous events; Registries; Research; Risk; Risk Estimate; Risk Factors; Scientific Advances and Accomplishments; Screening for cancer; Site; Surveillance Modeling; Update; adenoma; base; college; colorectal cancer prevention; colorectal cancer screening; cost effective; cost effectiveness; data registry; effectiveness evaluation; evidence base; follow-up; improved; indexing; medical schools; member; models and simulation; mortality; multidisciplinary; neoplasm registry; network models; patient stratification; personalized care; population based; premalignant; prevent; risk prediction; risk prediction model; risk stratification; screening guidelines; sex; simulation; surveillance network; surveillance strategy; time interval; tool

Project Summary/Abstract Colorectal cancer (CRC), the second most common cause of cancer deaths in the US, can be prevented through colonoscopy, during which potentially pre-cancerous polyps are removed from the colon. Serrated polyps may precede up to 30% of CRC, but unlike adenomatous polyps (their more common counterparts), there is limited data about their outcomes and natural history. Current clinical guidelines highlight that there is a critical lack of evidence available on future risks in patients with serrated polyps. To address this knowledge gap, this project proposes to combine the comprehensive data on colonoscopy patients, procedures, and pathology of the New Hampshire Colonoscopy Registry (NHCR), which has been collecting data from endoscopy sites across NH since 2004, with the statistical and risk prediction modeling expertise of the Geisel School of Medicine at Dartmouth College and the internationally recognized micro-simulation modelers of the Cancer Intervention and Surveillance Network (CISNET). The development and application of microsimulation models to characterize how digestive diseases progress is a key need for improving public health. In Aim 1.1, NHCR data, including key information on polyp subtype, size and location in the colon as well as the interval between index and subsequent colonoscopy, will be used to develop a risk-prediction model that can generate accurate personalized estimates of future risk in patients with serrated polyps. In Aim 1.2, NHCR data on patient risk factors and characteristics will be added to this model, to further refine the personalized estimates of future risk. In Aim 2.1, these risk estimates and additional NHCR data from patients with serrated lesions will be used by members of the CISNET Colorectal Group to inform and expand existing colorectal cancer micro-simulation models (SimCRC and MISCAN), and, in Aim 2.2, adding data from the literature, to validate these models. Aim 3.1 will use these expanded micro-simulation models to assess the clinical and cost effectiveness of recommended follow-up intervals for colonoscopy surveillance in patients with serrated polyps, stratified by specific polyp characteristics. Aim 3.2 will use the models to assess the effectiveness of recommended follow-up intervals for surveillance in patients with serrated polyps stratified by both polyp and patient characteristics. By linking the data of the NHCR with the biostatistical tools of risk-prediction and micro-simulation modelling, this study will significantly advance the scientific evidence-base and transform the landscape of serrated polyp management, helping colonoscopy achieve its tremendous potential for reducing CRC incidence and mortality.

项目摘要/摘要 结直肠癌(CRC)是美国第二常见的癌症死亡原因，可以预防 通过结肠镜检查，在此期间，潜在的癌前息肉被从结肠中移除。锯齿状 息肉可能先于30%的结直肠癌，但与腺瘤性息肉(更常见的息肉)不同， 关于他们的结果和自然历史的数据有限。目前的临床指南强调，有 严重缺乏关于锯齿状息肉患者未来风险的证据。要解决这个问题 知识鸿沟，这个项目建议结合结肠镜检查患者的全面数据， 新汉普郡结肠镜检查登记处(NHCR)的程序和病理，该登记处一直在收集 来自全国各地内窥镜检查站点的数据，具有以下统计和风险预测建模专业知识 达特茅斯学院盖泽尔医学院与国际公认的微观模拟 癌症干预和监测网络(CISNET)的模型师。计算机网络技术的发展与应用 用微模拟模型来描述消化系统疾病的进展情况是改善公众健康的关键 健康。 在Aim 1.1中，NHCR数据，包括关于息肉亚型、大小和在结肠中的位置以及 指数和随后的结肠镜检查之间的间隔将被用来开发风险预测模型，该模型 可以对锯齿状息肉患者的未来风险进行准确的个性化评估。在Aim 1.2中， 关于患者风险因素和特征的NHCR数据将被添加到该模型中，以进一步完善 对未来风险的个性化估计。在Aim 2.1中，这些风险估计和来自患者的额外NHCR数据 有锯齿状病变的情况将由CISNET结直肠组成员使用，以通知和扩大 现有的结直肠癌微观模拟模型(SimCRC和MISCAN)，并在Aim 2.2中增加了数据 从文献中，来验证这些模型。AIM 3.1将使用这些扩展的微观模拟模型来 评估结肠镜检查推荐随访间隔的临床和成本效益 对锯齿状息肉患者的监测，按特定息肉特征分层。AIM 3.2将使用 评估建议的随访间隔在监测慢性病患者中的有效性的模型 锯齿状息肉，根据息肉和患者特征分层。 通过将NHCR的数据与风险预测和微观模拟建模的生物统计工具联系起来， 这一研究将大大推进锯齿状息肉的科学证据基础，改变锯齿状息肉的面貌 帮助结肠镜检查发挥其降低结直肠癌发病率和死亡率的巨大潜力。