title: Chapter 13: CISNET lung models: comparison of model assumptions and model structures.
abstract: Sophisticated modeling techniques can be powerful tools to help us understand the effects of cancer control interventions on population trends in cancer incidence and mortality. Readers of journal articles are, however, rarely supplied with modeling details. Six modeling groups collaborated as part of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET) to investigate the contribution of U.S. tobacco-control efforts toward reducing lung cancer deaths over the period 1975-2000. The six models included in this monograph were developed independently and use distinct, complementary approaches toward modeling the natural history of lung cancer. The models used the same data for inputs, and agreed on the design of the analysis and the outcome measures. This article highlights aspects of the models that are most relevant to similarities of or differences between the results. Structured comparisons can increase the transparency of these complex models.
authors.affiliation: Institute of Technology Assessment, 101 Merrimac St., Boston, MA 02114-4724, USA. pamela@mgh-ita.org
authors.forename: Pamela M
authors.initials: PM
authors.lastname: McMahon
authors.forename: William D
authors.initials: WD
authors.lastname: Hazelton
authors.forename: Marek
authors.initials: M
authors.lastname: Kimmel
authors.forename: Lauren D
authors.initials: LD
authors.lastname: Clarke
mesh_terms: D000465:Algorithms; D002138:Calibration; D015331:Cohort Studies; D006801:Humans; D015994:Incidence; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000453:epidemiology* / Q000209:etiology; D015233:Models, Statistical; D008962:Models, Theoretical; D054547:National Cancer Institute (U.S.); D011336:Probability; D011634:Public Health; D012907:Smoking / Q000009:adverse effects* / Q000453:epidemiology; D016540:Smoking Cessation; D014481:United States