Incorporating smoking cessation programs into low-dose CT lung cancer screening is a cost-effective way to decrease mortality rates, according to a study presented at the International Association for the Study of Lung Cancer (IASLC) World Conference on Lung Cancer (WCLC) in Yokohama, Japan.
Multiple studies have previously demonstrated that CT screening can reduce deaths from lung cancer. Research has also shown that smoking cessation and related programs can contribute to drops in mortality rates.
Considering that the majority of smokers have been avoiding CT lung cancer screening, Dr. William Evans and colleagues at McMaster University in Canada set out to uncover a way to encourage participation.
They used a microsimulation model, OncoSim-LC, to compare 20-year projections of CT screening with and without an accompanying smoking cessation program. Combining CT screening with a cessation program would only cost $14,000 per quality-adjusted life year gained, they found. This represents a cost-effective way to lower the death rate of smokers from lung cancer, according to the researchers.
"To achieve the maximal benefits of a [low-dose CT] screening program, it is essential to incorporate a robust smoking cessation intervention," Evans said at the conference. "An organized lung screening program can be used to provide teachable moments for heavy smokers and, ultimately, save lives."


















![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&fit=crop&h=112&q=70&w=112)

