CANCER INTERVENTION AND SURVEILLANCE MODELING NETWORK

说明(申请人提供)建议的研究旨在开发一个全面监测肺癌人口趋势的模型。该模型将估计癌症控制干预措施对以下方面的影响：观察到的发病率和/或死亡率的趋势；建议的干预措施对人口产生预期影响的程度；新干预措施对未来国家肺癌趋势的潜在影响；以及有针对性的癌症控制干预措施对人口结果的影响。 建议的模型将基于早些时候为其他癌症模拟开发的微模拟筛查分析(MISCAN)模拟模型，并将进行调整，以包括暴露于风险因素(吸烟和饮食)与肺癌风险之间的关联以及暴露与效果之间的时间的显式模型。这一风险因素模型将先于筛查评估的综合模型，该模型包括肺癌的自然病史以及接触筛查及其对健康的影响。该肺癌筛查评估模型将类似于以前成功用于乳腺癌、宫颈癌、结直肠癌和前列腺癌筛查评估的MISCAN模型。与其他MISCAN模型一样，MISCAN-肺癌模型将模拟完全动态的人口，这使得它特别适合于监测人口趋势。 该模型将以文献中的证据为依据，并将在有关风险因素和筛查方面的几项经验性纵向研究中进行验证。 拟议的项目还将开发一个评估肺癌存活率趋势的模式，最好地考虑到报告做法的变化，以便评估治疗变化的影响。 这一项目提供了一个独特的机会，可以整合与监测人口趋势有关的肺癌所有方面的知识。

DESCRIPTION (provided by applicant) The proposed study is intended to develop a model for the comprehensive surveillance of population trends in lung cancer. This model will deliver estimates of the impact of cancer control interventions on: observed trends in incidence and/or mortality; the extent to which recommended interventions are having their expected population impact; the potential impact of new interventions on future national lung cancer trends; and the impact of targeted cancer control interventions on population outcome. The proposed model will be based on the Micro-simulation SCreening ANalysis (MISCAN) simulation model developed earlier for other cancer simulations and will be adapted to include an explicit model for the association between exposure to risk factors (smoking and diet) and risk for lung cancer as well as the time between exposure and effect. This risk-factor model will precede the comprehensive model for screening evaluation that includes the natural history of lung cancer, as well as exposure to screening and its health effects. This lung cancer screening evaluation model will be similar to MISCAN models that were previously successfully used for the evaluation of screening for breast, cervical, colorectal, and prostate cancer. As with other MISCAN models, the MISCAN-lung cancer model will simulate a full dynamic population, which makes it particularly suitable for surveillance of population trends. The model will be informed by the evidence from the literature, and it will be validated on several empirical longitudinal studies both on aspects concerning risk factors as well as screening. The proposed project will also develop a model for the evaluation of trends in survival from lung cancer that will optimally account for changes in reporting practice, in order to evaluate the impact of changes in therapy. This project provides a unique opportunity to integrate knowledge on all aspects of lung cancer that are relevant for the surveillance of population trends.