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Cancer Control Research

Abstract

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.