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Risk Anal. 2012 Jul;32 Suppl 1:S117-24. doi: 10.1111/j.1539-6924.2011.01652.x.

Chapter 9: The MGH-HMS lung cancer policy model: tobacco control versus screening.

Author information

1
Institute for Technology Assessment, Massachusetts General Hospital, 101 Merrimac Street, Boston, MA 02114, USA. pamela@mgh-ita.org

Abstract

The natural history model underlying the MGH Lung Cancer Policy Model (LCPM) does not include the two-stage clonal expansion model employed in other CISNET lung models. We used the LCPM to predict numbers of U.S. lung cancer deaths for ages 30-84 between 1975 and 2000 under four scenarios as part of the comparative modeling analysis described in this issue. The LCPM is a comprehensive microsimulation model of lung cancer development, progression, detection, treatment, and survival. Individual-level patient histories are aggregated to estimate cohort or population-level outcomes. Lung cancer states are defined according to underlying disease variables, test results, and clinical events. By simulating detailed clinical procedures, the LCPM can predict benefits and harms attributable to a variety of patient management practices, including annual screening programs. Under the scenario of observed smoking patterns, predicted numbers of deaths from the calibrated LCPM were within 2% of observed over all years (1975-2000). The LCPM estimated that historical tobacco control policies achieved 28.6% (25.2% in men, 30.5% in women) of the potential reduction in U.S. lung cancer deaths had smoking had been eliminated entirely. The hypothetical adoption in 1975 of annual helical CT screening of all persons aged 55-74 with at least 30 pack-years of cigarette exposure to historical tobacco control would have yielded a proportion realized of 39.0% (42.0% in men, 33.3% in women). The adoption of annual screening would have prevented less than half as many lung cancer deaths as the elimination of cigarette smoking.

PMID:
22882882
PMCID:
PMC3478757
DOI:
10.1111/j.1539-6924.2011.01652.x
[Indexed for MEDLINE]
Free PMC Article

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