U-M Study: Increasing Lung Cancer Screening Eligibility Saves Lives Despite Risk

A researcher at the University of Michigan in Ann Arbor is leading a project that found reducing the initial screening age and including those with lower smoking exposures would help avert lung cancer-related deaths.
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lung screen stock photo
A U-M researcher found that reducing the initial screening age would help avert lung cancer-related deaths. // Stock photo

A researcher at the University of Michigan in Ann Arbor is leading a project that found reducing the initial screening age and including those with lower smoking exposures would help avert lung cancer-related deaths.

The study was completed by the Cancer Intervention and Surveillance Modeling Network, which is led by the U-M researcher, and was commissioned by the U.S. Preventive Services Task Force, an independent volunteer panel of national experts in disease prevention and evidence-based medicine.

It looks at benefits and harms associated with low-dose computer 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 gender and race/ethnicity disparities.

The results helped inform the new U.S. Preventive Services Task Force guidelines, and both the study and new guidelines were published in JAMA, a peer-reviewed medical journal published by the American Medical Association.

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 those who are considered light smokers would bring lung cancer screening to a larger population group, says 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 curve lung cancer deaths, which account for one in four cancer deaths in the U.S. – more than colon, breast, and prostate cancer deaths combined,” says 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 criteria, the modeling estimated that 503 lung cancer deaths per 100,000 people would be averted, compared to 381 per 100,000 people under previous criteria, if all individuals eligible form 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 people, compared to 4,882 per 100,000 people under previous recommendations. Screening eligibility would increase to nearly 23 percent compared to 14 percent of the population eligible under the previous criteria.

However, screening under the new criteria would result in more false-positive test results, overdiagnosed lung cancer cases (84 per 100,000 people versus 69 per 100,000 people), and radiation-related lung cancer deaths (38.6 per 100,000 people versus 20.6 per 100,000 people). However, Meza says the increase in these numbers is worth the risk.

“We found expanded eligibility led to many more lung cancer deaths averted and life years gained versus a smaller number of overdiagnosed lung cancer cases and radiation-related LC deaths,” Meza said.

The team 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 from age 45-90.

The models considered factors such as number of pack years; number of cigarettes smoked per day at any given age and 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 says. The four models were also part of earlier analyses that supported 2013 U.S. Preventive Services Task Force 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 U-M 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.

The study is available here, and the U.S. Preventive Services Task Force’s statement is available here.

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