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.

项目总结/摘要 结直肠癌（CRC）是美国第二大常见的癌症死亡原因，可以预防 通过结肠镜检查，在此期间，潜在的癌前息肉从结肠中取出。锯齿状 息肉可能先于高达30%的CRC，但与腺瘤性息肉（它们更常见的对应物）不同， 关于其结果和自然史的数据有限。目前的临床指南强调， 严重缺乏关于锯齿状息肉患者未来风险的证据。为了解决这个 知识差距，该项目建议将联合收割机结合结肠镜检查患者的全面数据， 新罕布什尔州结肠镜登记处（NHCR）的程序和病理学，该登记处一直在收集 自2004年以来，来自NH各内镜检查站的数据， 达特茅斯学院的盖泽尔医学院和国际公认的微观模拟 癌症干预和监测网络（CISNET）。的发展和应用 描述消化系统疾病进展的微观模拟模型是改善公众健康的关键。 健康 在目标1.1中，NHCR数据，包括息肉亚型、大小和结肠位置的关键信息，以及 指数和随后的结肠镜检查之间的间隔，将用于开发风险预测模型， 可以对锯齿状息肉患者的未来风险进行准确的个性化估计。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评估。在目标2.1中，这些风险估计和来自患者的额外NHCR数据 CISNET结直肠组的成员将使用锯齿状病变来告知和扩展 现有的结直肠癌微观模拟模型（SimCRC和MISCAN），并在目标2.2中添加数据 来验证这些模型。Aim 3.1将使用这些扩展的微观模拟模型， 评估结肠镜检查推荐随访间隔的临床和成本效益 监测锯齿状息肉患者，按特定息肉特征分层。目标3.2将使用 用于评估推荐的随访间隔对以下患者进行监测的有效性的模型 根据息肉和患者特征分层的锯齿状息肉。 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， 这项研究将大大推进科学证据基础，并改变锯齿状息肉的景观 管理，帮助结肠镜检查实现其巨大的潜力，降低CRC的发病率和死亡率。