Expanded lung cancer screening eligibility would save lives
Reducing the initial screening age and including those with lower smoking exposures would help avert lung cancer-related deaths, according to a new study by the Cancer Intervention and Surveillance Modeling Network, led by a University of Michigan researcher.
The modeling study, commissioned by the U.S. Preventive Services Task Force and published in JAMA this week, looks at the benefits and harms associated with various low-dose computed tomography screening strategies—identifying those that result in the most benefits for a given level of screening. It found that the new guidelines would help address current gender and race/ethnicity disparities.
The results helped inform the new USPSTF guidelines, published also in the same issue of JAMA.
The study suggests that screening individuals aged 50-80 who have a history of smoking a pack of cigarettes every day on average for at least 20 years would result in more benefits than previous criteria and less disparities in screening eligibility by gender and race/ethnicity.
Allowing for younger people who smoke or lighter smokers would bring lung cancer screening to a larger population group, said the study’s lead author, Rafael Meza, associate professor of epidemiology at the U-M School of Public Health and coordinating Principal Investigator of the Cancer Intervention and Surveillance Modeling Network Lung Working Group, which conducted the modeling study.
“Expanding screening eligibility will help further curb lung cancer deaths, which account for 1 in 4 cancer deaths in the U.S.—more than colon, breast and prostate cancer deaths combined,” said Meza, who is also co-leader of the Cancer Epidemiology and Prevention Program at U-M’s Rogel Cancer Center.
“According to our analyses, the new recommendations will reduce disparities in lung cancer eligibility by sex and race, which hopefully will result in reductions in lung cancer disparities in the U.S. Similar screening programs could also be adopted in other countries, where lung cancer is also a huge health concern.”
Globally, lung cancer is the leading cancer death among men and the third most common among women, according to the World Health Organization.
Under the revised screening criteria, the modeling estimated that 503 lung cancer deaths per 100,000 persons would be averted, compared to 381 per 100,000 persons under previous criteria, if all individuals eligible from the U.S. 1960 birth cohort would be screened.
Similarly, screening according to the new criteria would result in 6,918 life-years gained per 100,000 persons, compared to 4,882 per 100,000 persons under previous recommendations. Screening eligibility would increase to nearly 23%, compared to 14% of the population ever eligible under the previous criteria.
On the negative side, screening under the new criteria would result in more false-positive test results (2.2 per person screened vs.1.9 per person screened with the USPSTF strategy), overdiagnosed lung cancer cases (84 per 100,000 persons vs. 69 per 100,000 persons), and radiation-related lung cancer deaths (38.6 per 100,000 persons vs. 20.6 per 100,000 persons).
“We found expanded eligibility led to many more lung cancer deaths averted and life years gained versus a (much) smaller number of overdiagnosed lung cancer cases and radiation-related LC deaths,” Meza said.
Meza and colleagues did a comparative simulation modeling study with four institutions developing their own models before comparing the results and finding the most effective strategies. They used data of individuals from the 1950 and 1960 U.S. birth cohorts who were followed up from age 45 through 90.
The models considered factors such as number of pack years, number of cigarettes smoked per day at any given age, gender, age of smoking initiation, and years since quitting. Each model simulated more than 1,000 different screening strategies before identifying the most effective ones, Meza said, adding that all four models were also part of earlier analyses that supported 2013 USPSTF lung cancer recommendations.
The models included the Microsimulation Screening Analysis-Lung Model from Erasmus University Medical Center, the Massachusetts General Hospital-Harvard Medical School model, the Lung Cancer Outcomes Simulation model from Stanford University, and the University of Michigan model.
The study was funded by a grant from the Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services and the National Cancer Institute.