Scientific models project a continued decrease in lung cancer mortality.
Tobacco control efforts implemented in the mid-1960s should continue to reduce lung cancer rates and mortality until 2065, according to a study — published in Annals of Internal Medicine — that used comparative modeling to predict tobacco use.1
“Our analyses indicate that maintaining existing tobacco control efforts will result in considerable reductions in the lung cancer burden in the United States,” researchers wrote.
The researchers developed 4 independent models of the natural history of lung cancer to project mortality rates for men and women from 1964 — when the Surgeon General’s Report on smoking and health was published — until the year 2065. The models used US data on smoking from 1964 to 2015 and on lung cancer mortality from 1969 to 2010.
All of the models accurately predicted observed trends in lung cancer mortality that occurred from 1969 to 2010. Using status quo trend scenarios, the models projected continued decreases in lung cancer mortality rates from 2015 to 2065.
Specifically, age-adjusted lung cancer mortality was projected to decrease by almost 80% from 2015 to 2065. Additionally, despite population growth and an aging population, the annual number of lung cancer deaths was projected to decrease by 63% from 135,000 per year to 50,000 per year.
The researchers noted that despite these reductions in mortality, models projected about 4.4 million deaths due to lung cancer will still occur in the 50-year span from 2015 to 2065. The majority of these deaths will likely be in ever-smokers, showing a need for additional screening efforts.
“We note that, although lung cancer screening is now being slowly adopted, changes to it could not only reduce lung cancer deaths but could also increase smoking cessation rates if support for quitting is combined with screening at the point of care,” the researchers wrote.
1. Jeon J, Holford TR, Levy DT, et al. Smoking and lung cancer mortality in the United States from 2015 to 2065. A comparative modeling approach [published online October 9, 2018]. Ann Intern Med. doi: 10.7326/M18-1250