Comparative Modeling of Effective Policies for Colorectal Cancer Control

结直肠癌控制有效政策的比较模型

• 批准号: 10668399
• 负责人: KAREN M KUNTZ
• 金额: $ 112.67万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-08 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10668399
• 关键词: Address; Age; American Cancer Society; Area; Calibration; Cancer Control; Cancer Etiology; Cessation of life; Clinical; Collaborations; Colonoscopy; Colorectal Cancer; Country; Data; Diagnosis; Effectiveness; Goals; Health Policy; High Performance Computing; Incidence; Income; Intervention; Knowledge; Literature; Methods; Modality; Modeling; Natural History; New Hampshire; Outcome; Pathway interactions; Pattern; Persons; Policies; Population; Population Research; Positioning Attribute; Regimen; Registries; Research; Resources; Role; Seminal; United States; Update; Work; carcinogenesis; colorectal cancer risk; comparative; computer aided detection; deep learning; experience; improved; insight; learning strategy; models and simulation; novel; personalized medicine; personalized screening; population based; prevent; screening; screening program

ABSTRACT Colorectal cancer (CRC) is the second leading cause of cancer death in the United States. The long-term goal of our proposed project is to reduce the population burden of CRC by providing the information needed to address key policy questions across the CRC control continuum in an accessible and transparent manner. To accomplish this goal we will use our population-based microsimulation models to: 1) Evaluate the impact of screening as practiced in the US; 2) Inform the debate about the increase in CRC incidence before age 50; 3) Consider the effectiveness of precision of screening and surveillance; 4) Address other emerging issues and opportunities in CRC control; and 5) Use novel methods to improve model accessibility and transparency. Our team will fill critical gaps in knowledge, enabling decision makers to act. New evidence that we will incorporate in our models to better inform CRC control opportunities will be 1) updated information on screening patterns in the US (in collaboration with the Population-based Research Optimizing Screening through Personalized Regimen, or PROS PR), 2) data on the increased risk of CRC in persons under age 50 (in collaboration with Rebecca Siegal of the American Cancer Society, who did the seminal work in this area), and 3) state-of-the art colonoscopy screening data to incorporate alternative carcinogenesis pathways in the natural history models (in collaboration with the New Hampshire Colonoscopy Registry). We will synthesize and incorporate the growing body of evidence in the literature to assess the clinical utility of personalized screening and treatment, as well as the potential role for novel computer-aided detection and diagnosis modalities. We will expand our models to project clinical and resource-based outcomes for middle-income countries that are considering the implementation of a screening program. Lastly, there is a critical need to make our models assessible and transparent. To this end we will use high performance computing approaches to develop and apply deep-learning methods for model calibration and model emulation, which will aid in model sharing. The three participating modeling groups are well positioned to carry out this work, bringing a wealth of experience, expertise, and insight to issues related to microsimulation modeling of CRC, and have a proven track record of collaboration and disseminating our work to health policy decision makers.

摘要 结直肠癌（CRC）是美国癌症死亡的第二大原因。我们拟议项目的长期目标是通过以易于访问和透明的方式提供解决整个CRC控制连续体中关键政策问题所需的信息，减轻CRC的人口负担。为了实现这一目标，我们将使用我们的基于人群的微观模拟模型：1）评估在美国实施的筛查的影响; 2）告知关于50岁之前CRC发病率增加的辩论; 3）考虑筛查和监测的精确性的有效性; 4）解决CRC控制中的其他新问题和机会; 5）采用新的方法提高模型的可访问性和透明度。我们的团队将填补知识的关键空白，使决策者能够采取行动。我们将纳入模型以更好地告知CRC控制机会的新证据将是1）美国筛查模式的最新信息（与基于人群的研究通过个性化方案优化筛查，或PROS PR合作），2）关于50岁以下人群CRC风险增加的数据（与美国癌症协会的丽贝卡·西格尔合作，她在这一领域做了开创性的工作），以及3）最先进的结肠镜筛查数据，以将替代致癌途径纳入自然史模型中（与新罕布什尔州结肠镜登记处合作）。我们将综合并纳入文献中越来越多的证据，以评估个性化筛查和治疗的临床效用，以及新型计算机辅助检测和诊断模式的潜在作用。我们将扩大我们的模型，为正在考虑实施筛查计划的中等收入国家预测临床和基于资源的结果。最后，迫切需要使我们的模型可评估且透明。为此，我们将使用高性能计算方法来开发和应用深度学习方法进行模型校准和模型仿真，这将有助于模型共享。三个参与的建模小组都有能力开展这项工作，为CRC的微观模拟建模相关问题带来了丰富的经验，专业知识和见解，并在合作和向卫生政策决策者传播我们的工作方面有着良好的记录。

项目成果

Cost-effectiveness analysis of colorectal cancer screening in Shanghai, China: A modelling study.

• DOI: 10.1016/j.pmedr.2022.101891
• 发表时间: 2022-10
• 期刊: PREVENTIVE MEDICINE REPORTS
• 影响因子: 2.8
• 作者: Wang, Jie;de Jonge, Lucie;Cenin, Dayna R.;Li, Pei;Tao, Sha;Yang, Chen;Yan, Bei;Lansdorp-Vogelaar, Iris
• 通讯作者: Lansdorp-Vogelaar, Iris

Use of 2-Stage Modeling to Identify How Colorectal Cancer Risk Changes With Period and Cohort.

使用两阶段模型来确定结直肠癌风险如何随时期和队列变化。

• DOI: 10.1093/aje/kwac177
• 发表时间: 2023
• 期刊: American journal of epidemiology
• 影响因子: 5
• 作者: DeYoreo,Maria;Rutter,CarolynM;Lee,SaritaD
• 通讯作者: Lee,SaritaD

Methods for Communicating the Impact of Parameter Uncertainty in a Multiple-Strategies Cost-Effectiveness Comparison.

• DOI: 10.1177/0272989x221100112
• 发表时间: 2022-10
• 期刊: MEDICAL DECISION MAKING
• 影响因子: 3.6
• 作者: Wolff, Henri B.;Qendri, Venetia;Kunst, Natalia;Alarid-Escudero, Fernando;Coupe, Veerle M. H.
• 通讯作者: Coupe, Veerle M. H.

An Evolutionary Algorithm to Personalize Stool-Based Colorectal Cancer Screening.

• DOI: 10.3389/fphys.2021.718276
• 发表时间: 2021
• 期刊: Frontiers in physiology
• 影响因子: 4
• 作者: van Duuren LA;Ozik J;Spliet R;Collier NT;Lansdorp-Vogelaar I;Meester RGS
• 通讯作者: Meester RGS

Emulator-based Bayesian calibration of the CISNET colorectal cancer models.

基于模拟器的 CISNET 结直肠癌模型贝叶斯校准。

• DOI: 10.1101/2023.02.27.23286525
• 发表时间: 2024
• 期刊: medRxiv : the preprint server for health sciences
• 作者: Pineda-Antunez,Carlos;Seguin,Claudia;vanDuuren,LuukA;Knudsen,AmyB;Davidi,Barak;deLima,PedroNascimento;Rutter,Carolyn;Kuntz,KarenM;Lansdorp-Vogelaar,Iris;Collier,Nicholson;Ozik,Jonathan;Alarid-Escudero,Fernando
• 通讯作者: Alarid-Escudero,Fernando