The appropriate screening inclusion criteria of low-dose computed tomography screening for lung cancer in Chinese population remains unclear and the effect of combining screening with nurse-led smoking cessation intervention is poorly understood as well.

We compared the benefits and costs of lung cancer screening with and without nurse-led smoking cessation intervention in different inclusion criteria to help select optimal screening strategies.

Different screening strategies were set based on diverse starting ages, smoking pack-year and whether nurse-led smoking cessation intervention was applied. We use nationally representative data published by the China Health and Retirement Longitudinal Survey, based on a microsimulation model, to predict incremental cost-effectiveness ratio and net health benefits under different strategies.

The incremental cost-effectiveness ratios for all lung cancer screening strategies were less than three times GDP per capita, and screening combined with smoking cessation intervention had lower incremental cost-effectiveness ratios. The largest net health benefits and probability of cost-effectiveness were both obtained in the strategy which conducted screening and nurse-led smoking cessation intervention for people over 45 years with at least 20 pack-year smoking history. In strategies screening alone, it was obtained in screening for people over 50 years and with at 20 pack-year smoking history.

Nurse-led smoking cessation intervention is recommended provided in conjunction with lung cancer screening. The optimal strategy is conducted screening with cessation intervention for current smokers or smoking quitters in the past 15 years who are over 45 years with at least 20 pack-year smoking history. For strategies screening alone, the target population should be over 50 years old with at least 20 pack year smoking history, when willingness to pay less than three times GPD per capita.

Lung cancer screening

Smoking cessation intervention

Nursing

Microsimulation models

Cost effectiveness

© 2022 Published by Elsevier Ltd.