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Paper Chase

Population impact of lung cancer screening in the United States: Projections from a microsimulation model.

PLoS Med.. 02 07, 2018;15(2):e1002506.
Criss SD, Sheehan DF, Palazzo L, Kong CY.

Harvard Medical School, Boston, Massachusetts, United States of America.

Abstract:

BACKGROUND

Previous simulation studies estimating the impacts of lung cancer screening have ignored the changes in smoking prevalence over time in the United States. Our primary rationale was to perform, to our knowledge, the first simulation study that estimates the health outcomes of lung cancer screening with explicit modeling of smoking trends for the whole US population.

METHODS/FINDINGS

Utilizing a well-validated microsimulation model, we estimated the benefits and harms of an annual low-dose computed tomography screening scenario with a realistic screening adherence rate versus a no-screening scenario for the US population from 2016-2030. The Centers for Medicare and Medicaid Services (CMS) eligibility criteria were applied: age 55-77 years at time of screening, history of at least 30 pack-years of smoking, and current smoker or former smoker with fewer than 15 years since quitting. In the screened population, cumulative mortality reduction was projected to reach 16.98% (95% CI 16.90%-17.07%). Cumulative mortality reduction was estimated to be 3.52% (95% CI 3.50%-3.53%) for the overall study population, with annual mortality reduction peaking at 4.38% (95% CI 4.36%-4.41%) in 2021 and falling to 3.53% (95% CI 3.50%-3.56%) by 2030. Lung cancer screening would save a projected 148,484 life-years (95% CI 147,429-149,540) across the total population through 2030. There were estimated to be 9,054 (95% CI 9,011-9,098) overdiagnosed cases among the 252,429 (95% CI 251,208-253,649) screen-detected lung cancer diagnoses, yielding an overdiagnosis rate of 3.59%. The limitations of our study are that we do not explicitly model race or socioeconomic status and our model was calibrated to data from studies performed in academic centers, both of which may impact the generalizability of our results. We also exclusively model the effects of the CMS guidelines for lung cancer screening and not any other screening strategies.

CONCLUSIONS

The mortality reduction and life-years gained estimated by this study are lower than those of single birth cohort studies. Single cohort studies neglect the changing dynamics of smoking behavior across generations, whereas this study reflects the trend of decreasing smoking prevalence since the 1960s. Maximum benefit could be derived from lung cancer screening through 2021; in later years, mortality reduction due to screening will decline. If a comprehensive screening program is not implemented in the near future, the opportunity to achieve these benefits will have passed.

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