Comparative Modeling of Lung Cancer Prevention and Control Policies

肺癌预防和控制政策的比较模型

• 批准号: 8967752
• 负责人: THEODORE R HOLFORD
• 金额: $ 175.18万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-16 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8967752
• 关键词: Accounting; Adopted; Advisory Committees; Age; Biological Markers; Cancer Burden; Cancer Control; Cancer Etiology; Cancer Intervention and Surveillance Modeling Network; Cancer Model; Cause of Death; Cessation of life; Colon Carcinoma; Cost Effectiveness Analysis; Country; Decision Aid; Dose; Education; Effectiveness; Eligibility Determination; Ethnic Origin; Future; Gender; Geographic Locations; Goals; Heterogeneity; Incidence; Income; Individual; Insurance Coverage; Investigation; Joints; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Malignant neoplasm of prostate; Measures; Mexico; Modeling; Multiple Birth Offspring; Other Genetics; Outcome; Policies; Population; Prevalence; Protocols documentation; Race; Recommendation; Research Personnel; Risk; Screening for cancer; Services; Smoker; Smoking; Smoking Behavior; Smoking History; Subgroup; Surveys; Thailand; Tobacco; Translating; United States; Variant; Work; X-Ray Computed Tomography; base; cancer health disparity; cancer risk; cohort; comparative; cost effectiveness; health disparity; high risk; lung cancer prevention; lung cancer screening; malignant breast neoplasm; models and simulation; mortality; network models; population health; prevent; public health relevance; public policy on tobacco; response; screening; smoking prevalence; tobacco control; tobacco screening; trend; working group

 DESCRIPTION (provided by applicant): Lung cancer is the top cancer killer and smoking remains the leading preventable cause of death in the US. Furthermore, major disparities in smoking and lung cancer exist by education, income, and race/ethnicity. While tobacco control policies are the most effective strategies to prevent lung cancers, lung cancer computed tomography (CT) screening has also been shown to reduce lung cancer risk among heavy current and former smokers. The Cancer Intervention and Surveillance Modeling Network (CISNET) lung group develops and applies population models for lung cancer, quantifying the impact of tobacco control and CT screening on lung cancer and all-cause mortality. To date, this work has focused on the country as a whole and has yet to account for tobacco and lung cancer disparities by subgroup and region. This proposed work will extend existing CISNET lung models to investigate the synergistic impacts of tobacco control policies and lung cancer screening in the US and in middle-income nations, focusing on disparities in both smoking behavior and lung cancer risk. The smoking and lung cancer models will incorporate other factors that reflect different smoking risks such as race/ethnicity, education, income, and geographic location. This will allow for analyses of the effects of tobacco control policies on US smoking prevalence in relevant high-risk groups, and estimation of the impact of policies on health disparities in smoking and lung cancer outcomes. Models will also be adapted for two middle-income nations, Mexico and Thailand, to evaluate the impact of tobacco control policies on smoking and lung cancer rates in middle-income countries with different demographic and smoking behavior profiles than the US. Although lung cancer screening is now supported by the USPSTF and other major national organizations, there is still considerable debate over the potential benefits and harms of screening at the population level. This project will extend CISNET lung cancer screening models to assess the consequences of heterogeneity in lung cancer screening implementation, insurance coverage, and compliance with recommended protocols on population health. Models will also be used to investigate the implications of using alternative individual risk prediction measures as eligibility criteria for screening, and to perfom cost-effectiveness analyses of current and alternative screening recommendations, with the goal of identifying optimal strategies at the population level.

 描述（由申请人提供）：肺癌是头号癌症杀手，吸烟仍然是美国主要的可预防死亡原因。此外，教育、收入和种族/民族在吸烟和肺癌方面存在重大差异。虽然烟草控制政策是预防肺癌最有效的策略，但肺癌计算机断层扫描 (CT) 筛查也被证明可以降低重度吸烟者和前吸烟者患肺癌的风险。癌症干预和监测模型网络 (CISNET) 肺部小组开发并应用肺癌群体模型，量化烟草控制和 CT 筛查对肺癌和全因死亡率的影响。迄今为止，这项工作的重点是整个国家，尚未考虑按亚组和地区划分的烟草和肺癌差异。这项拟议的工作将扩展现有的 CISNET 肺部模型，以研究美国和中等收入国家烟草控制政策和肺癌筛查的协同影响，重点关注吸烟行为和肺癌风险的差异。吸烟和肺癌模型将纳入反映不同吸烟风险的其他因素，例如种族/民族、教育、收入和地理位置。这将有助于分析烟草控制政策对美国相关高危人群吸烟率的影响，并估计政策对吸烟和肺癌结果健康差异的影响。模型还将针对墨西哥和泰国这两个中等收入国家进行调整，以评估人口和吸烟行为特征与美国不同的中等收入国家的烟草控制政策对吸烟和肺癌发病率的影响。尽管肺癌筛查现在得到了 USPSTF 和其他主要国家组织的支持，但对于人群层面筛查的潜在益处和危害仍然存在相当大的争论。该项目将扩展 CISNET 肺癌筛查模型，以评估肺癌筛查实施、保险覆盖范围以及遵守人口健康推荐协议方面的异质性后果。模型还将用于研究使用替代个人风险预测措施作为筛查资格标准的影响，并对当前和替代筛查建议进行成本效益分析，目的是确定人群水平的最佳策略。