Comparative Modeling of Effective Policies for Colorectal Cancer Control

结直肠癌控制有效政策的比较模型

基本信息

批准号：
10471354
负责人：
KAREN M KUNTZ
金额：
$ 113.31万
依托单位：
SLOAN-KETTERING INST CAN RESEARCH
依托单位国家：
美国
项目类别：
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/10471354
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 base carcinogenesis colorectal cancer risk comparative computer aided detection deep learning experience improved insight learning strategy novel personalized medicine personalized screening population based prevent screening screening program

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 base carcinogenesis colorectal cancer risk comparative computer aided detection deep learning experience improved insight learning strategy novel personalized medicine personalized screening population based prevent screening screening program

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项目摘要

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 PROSPR), 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.

抽象的结直肠癌（CRC）是美国癌症死亡的第二大原因。长期目标我们提议的项目是通过提供所需的信息来减轻CRC的人口负担以可访问且透明的方式解决CRC控制连续性的关键政策问题。到实现这一目标，我们将使用基于人群的微仿真模型来：1）评估在美国进行的筛查； 2）告知关于50岁以前CRC发病率增加的辩论； 3）考虑筛查和监视精度的有效性； 4）解决其他新兴问题和 CRC控制的机会； 5）使用新颖的方法来提高模型可访问性和透明度。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。我们将合并的新证据在我们的模型中，以更好地告知CRC控制机会是1）有关筛选模式的最新信息美国（与基于人群的研究合作，通过个性化优化筛查疗法或PROSPR），2）关于50岁以下人士的CRC风险增加的数据（与美国癌症协会的丽贝卡·西格尔（Rebecca Siegal）在这一领域进行了开创性的工作），3）结肠镜检查筛查数据以在自然史模型中纳入替代的癌变途径（与新罕布什尔州结肠镜检查注册中心合作）。我们将合成并合并文献中越来越多的证据体系评估个性化筛查和治疗的临床实用性，以及新型计算机辅助检测和诊断方式的潜在作用。我们将扩大我们的为中等收入国家投影基于临床和资源的结果的模型筛选程序的实施。最后，迫切需要评估我们的模型，并且透明的。为此，我们将使用高性能计算方法来开发和应用深度模型校准和模型仿真的学习方法，这将有助于模型共享。三个参与的建模小组在进行这项工作，带来丰富的经验，专业知识，并深入了解与CRC的显微仿真建模有关的问题，并具有可靠的记录合作并将我们的工作传播给健康政策决策者。