Impact of lung cancer screening results on smoking cessation.


BACKGROUND Lung cancer screening programs may provide opportunities to reduce smoking rates among participants. This study evaluates the impact of lung cancer screening results on smoking cessation. METHODS Data from Lung Screening Study participants in the National Lung Screening Trial (NLST; 2002-2009) were used to prepare multivariable longitudinal regression models predicting annual smoking cessation in those who were current smokers at study entry (n = 15489, excluding those developing lung cancer in follow-up). The associations of lung cancer screening results on smoking cessation over the trial period were analyzed. All hypothesis testing used two sided P values. RESULTS In adjusted analyses, smoking cessation was strongly associated with the amount of abnormality observed in the previous year's screening (P < .0001). Compared with those with a normal screen, individuals were less likely to be smokers if their previous year's screen had a major abnormality that was not suspicious for lung cancer (odds ratio [OR] = 0.811; 95% confidence interval [CI] = 0.722 to 0.912; P < .001), was suspicious for lung cancer but stable from previous screens (OR = 0.785; 95% CI = 0.706 to 0.872; P < .001), or was suspicious for lung cancer and was new or changed from the previous screen (OR = 0.663; 95% CI = 0.607 to 0.724; P < .001). Differences in smoking prevalence were present up to 5 years after the last screen. CONCLUSIONS Smoking cessation is statistically significantly associated with screen-detected abnormality. Integration of effective smoking cessation programs within screening programs should lead to further reduction in smoking-related morbidity and mortality.

DOI: 10.1093/jnci/dju084
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@article{Tammemgi2014ImpactOL, title={Impact of lung cancer screening results on smoking cessation.}, author={Martin C. Tammem{\"a}gi and Christine D. Berg and Thomas L. Riley and Christopher R Cunningham and Kathryn L. Taylor}, journal={Journal of the National Cancer Institute}, year={2014}, volume={106 6}, pages={dju084} }