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）：复杂的建模技术可以成为决策者寻求了解癌症控制干预措施对癌症发病率和死亡率人口趋势的影响的强大工具。然而，此类模型在卫生政策中的价值已被证实，但由于对复杂模型缺乏透明度以及不同群体公布的结果存在差异的合理担忧而受到限制。 NCI 的癌症干预和监测建模网络 (CISNET) 旨在促进调查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源作为输入并就统一的结果衡量标准达成一致，结果的可变性反映了癌症控制干预措施效果的不确定性，而不是分析设计的差异。此外，通过共同努力，建模小组可以连贯地解释变化的原因。 该提案通过使用比较模型方法来估计烟草控制和筛查对减少肺癌死亡的贡献，从而进一步实现了 CISNET 的目标。未来 5 年，主要试验将报告螺旋 CT 筛查肺癌的功效结果。该提案中描述的五个 CISNET 模型代表了现有的基础设施，可用于将这些新数据与来自观察和队列研究以及肿瘤登记的现有数据进行合成。如果单独或组合采用这些政策干预措施，这组模型有望将试验结果转化为人口水平的影响，并预测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项或多项具体干预措施的方式传播我们的结果，以最大程度地减少肺癌死亡。