Comparative Modeling of Lung Cancer Control Policies

肺癌控制政策的比较模型

• 批准号: 8548101
• 负责人: Chung Yin Kong
• 金额: $ 129.11万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8548101
• 关键词: Adopted; Adult; American; Area; Biological Markers; Cancer Control; Cancer Etiology; Cancer Intervention; Cancer Intervention and Surveillance Modeling Network; Cessation of life; Cohort Studies; Collaborations; Complex; Data; Data Sources; Focus Groups; Goals; Health Policy; Image; Incidence; Intervention; Joints; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Modeling; Natural History; Observational Study; Outcome Measure; Policies; Population; Publishing; Randomized Controlled Trials; Reporting; Research Infrastructure; Smoke; Smoking; Spiral Computed Tomography; Subgroup; Techniques; Tobacco; Translating; Uncertainty; United States; Variant; Work; arm; base; comparative; design; flexibility; lung cancer screening; mortality; network models; programs; public policy on tobacco; screening; tobacco control; tobacco screening; tool; trend; tumor registry

DESCRIPTION (provided by applicant): Sophisticated modeling techniques can be powerful tools for decision makers seeking to understand the effects of cancer control interventions on population trends in cancer incidence and mortality. Yet the proven value of such models in health policy is limited by legitimate concerns over lack of transparency of complex models and variability in published results from different groups. NCI's Cancer Intervention and Surveillance Modeling Network (CISNET) was created to promote collaboration between independent modeling groups investigating similar questions. By using the same sources of data for inputs and agreeing on uniform outcome measures, the variability in results reflects uncertainty in the effects of cancer control interventions rather than differences in design of the analysis. Further, by working together, the modeling groups can coherently explain the causes of variation. This proposal furthers the goals of CISNET by using comparative modeling approach to estimate the contributions of tobacco control and screening to reducing deaths from lung cancer. Over the next 5 years, major trials will report results on the efficacy of helical CT screening for lung cancer. The five CISNET models described in this proposal represent an existing infrastructure with which to synthesize these new data with existing data from observational and cohort studies and tumor registries. This group of models is poised to translate trial results into population-level effects and to project trends in lung cancer incidence and mortality if these policy interventions were adopted alone or in combination. We propose to disseminate our results in ways that will allow decision makers to prioritize one or more specific interventions to achieve the greatest reduction in lung cancer deaths.

描述（由申请人提供）：复杂的建模技术可能是试图了解癌症控制干预措施对癌症发病率和死亡率人群趋势的影响的决策者的强大工具。然而，这种模型在卫生政策中的可靠价值受到对复杂模型缺乏透明度的正当关注以及不同群体已发表的结果的可变性的限制。 NCI的癌症干预和监视建模网络（CISNET）的创建是为了促进研究类似问题的独立建模小组之间的合作。通过使用相同的数据来源进行输入并同意统一的结果指标，结果的可变性反映了癌症控制干预措施的影响的不确定性，而不是分析设计的差异。此外，通过共同努力，建模组可以一致解释变异的原因。 该提议通过使用比较建模方法来估算烟草控制和筛查对减少肺癌死亡的贡献的贡献，从而进一步促进了CISNET的目标。在接下来的5年中，重大试验将报告有关螺旋CT筛查对肺癌的功效的结果。本提案中描述的五个CISNET模型代表了现有的基础架构，该基础架构与观察和队列研究和肿瘤注册处的现有数据合成这些新数据。如果采用这些政策干预措施，则该组有望将试验结果转化为人群级别的影响和肺癌发病率和死亡率的趋势。我们建议以允许决策者优先考虑一种或多种特定干预措施以实现肺癌死亡最大的干预措施的优先级优先级。