Exploring the uncertainties of early detection results: model-based interpretation of mayo lung project

• Main Authors: Berman Barbara, McCarthy William J, Tian Haijun, Shi Lu, Wu Shinyi, Boer Rob
• Format: Article
• Language: English
• Published: BMC 2011-03-01
• Series: BMC Cancer
• Online Access: http://www.biomedcentral.com/1471-2407/11/92

<p>Abstract</p> <p>Background</p> <p>The Mayo Lung Project (MLP), a randomized controlled clinical trial of lung cancer screening conducted between 1971 and 1986 among male smokers aged 45 or above, demonstrated an increase in lung cancer survival since the time of diagnosis, but no reduction in lung cancer mortality. Whether this result necessarily indicates a lack of mortality benefit for screening remains controversial. A number of hypotheses have been proposed to explain the observed outcome, including over-diagnosis, screening sensitivity, and population heterogeneity (initial difference in lung cancer risks between the two trial arms). This study is intended to provide model-based testing for some of these important arguments.</p> <p>Method</p> <p>Using a micro-simulation model, the MISCAN-lung model, we explore the possible influence of screening sensitivity, systematic error, over-diagnosis and population heterogeneity.</p> <p>Results</p> <p>Calibrating screening sensitivity, systematic error, or over-diagnosis does not noticeably improve the fit of the model, whereas calibrating population heterogeneity helps the model predict lung cancer incidence better.</p> <p>Conclusions</p> <p>Our conclusion is that the hypothesized imperfection in screening sensitivity, systematic error, and over-diagnosis do not in themselves explain the observed trial results. Model fit improvement achieved by accounting for population heterogeneity suggests a higher risk of cancer incidence in the intervention group as compared with the control group.</p>