Researchers identify the most accurate risk prediction models for selecting whom to screen
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Below please find summaries of new articles that will be published in the next issue of Annals of Internal Medicine. The summaries are not intended to substitute for the full articles as a source of information.

1. Researchers identify the most accurate risk prediction models for selecting whom to screen for lung cancer

Findings may be used to inform future lung cancer screening guidelines

Abstract: http://annals.org/aim/article/doi/10.7326/M17-2701

http://annals.org/aim/article/doi/10.7326/M17-2701

Editorial: http://annals.org/aim/article/doi/10.7326/M18-0986

http://annals.org/aim/article/doi/10.7326/M18-0986

URLs go live when the embargo lifts

Four risk prediction models have been shown to be most accurate for selecting the highest risk ever-smokers for lung cancer screening. Researchers suggest that this data can be used to inform future lung cancer screening guidelines. The findings are published in Annals of Internal Medicine.

There is growing recognition that, rather than selecting smokers for screening by using simple dichotomized risk factors, individualized risk calculations that account for certain demographic, clinical, and smoking characteristics could substantially enhance the effectiveness and efficiency of CT screening programs. As such, recent lung cancer screening guidelines from the National Comprehensive Cancer Network permit using individualized risk models to refer ever-smokers for screening. However, different models select different screening populations and it is not known how well they perform.

Researchers from the National Cancer Institute (NCI) and the

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Article originally posted at
www.eurekalert.org

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