Changing the way individuals are selected to be screened for lung cancer, by considering their probability of getting or dying from lung cancer calculated from risk-prediction models, could prevent 14 percent of lung cancer deaths per year.
The Cancer Intervention and Surveillance Modeling Network Lung Working Group (CISNET), which includes researchers from the University of Michigan School of Public Health, says this means nearly 2,000 deaths could be prevented annually in the United States by factoring more information from among the many risk-prediction models developed in recent years that consider a person’s risk factor profile.
Current lung cancer screening is based on age, on how much individuals have smoked (measured as pack-years), and how long they have stopped smoking. The team looked at various risk-prediction models that consider behavior, lifestyle and family history to estimate the probability of getting or dying from lung cancer.
“The results of this study are of major importance for the implementation of lung cancer screening worldwide,” said Dr. Rafael Meza, associate chair of epidemiology at the Michigan Public Health and coordinating principal investigator of the CISNET Lung group. “Risk-based screening strategies have the potential of saving more lives.
“However, by moving screening to older ages, they result in fewer years of life saved per lung cancer death prevented. This is important for countries to consider, as well as the challenges of implementing risk calculation in clinical settings, when deciding which strategy works best for them.”Friday Letter Submission, Publish on October 04