Potential Impact of Including Time to First Cigarette in Risk Models for Selecting Ever-Smokers for Lung Cancer Screening.

INTRODUCTION: Selecting individuals on the basis of model-predicted risks has been reported to improve lung cancer screening efficiency. On the basis of case-control studies, time to first cigarette (TTFC), a nicotine dependency measurement, has been a strong independent predictor of lung cancer risk. Our objective was to verify the TTFC-lung cancer association in the prospective National Lung Screening Trial and evaluate whether adding TTFC can improve lung cancer risk-prediction models. METHODS: Using Cox models, we examined associations between TTFC (≤5, 6-14, 15-29, 30-59, and ≥60 minutes) and lung cancer incidence and death in 18,729 National Lung Screening Trial participants, adjusting for smoking and other lung cancer risk factors comprehensively. We estimated 5-year individual lung cancer incidence by using models without and with TTFC and dichotomized into screening or no-screening groups based on risk thresholds of 1% and 2%. Area under the receiver operating curve values were calculated for models without and with TTFC. RESULTS: Smokers with a TTFC of 60 minutes or more had a much lower standardized 5-year lung cancer incidence risk-1.54% (1.52%-1.56%) for TTFC 60 minutes or more versus 4.07% (4.04%-4.09%) for TTFC 5 minutes or less-and lung cancer death risk-0.59% (0.57%-0.61%) for TTFC 60 minutes or more versus 2.26% (2.23%-2.28%) for TTFC 5 minutes or less (p trend < 0.001). Adding TTFC to the lung cancer incidence model improved the area under the receiver operating curve by 0.0079 (95% confidence interval = 0.0019-0.0138 [p = 0.0085]). Among 8994 smokers without a lung cancer diagnosis, 180 (2.00%) and 155 (1.67%) more people would be assigned to the no-screening group by adding TTFC to the model (p values for percent changes <0.001) at the 1% and 2% risk thresholds, respectively. CONCLUSION: Including TTFC, which can be elicited by a single question at very low cost and noninvasively question, into risk models might better identify smokers with lower risk and could therefore be a safe, convenient tool to improve identification of those who benefit less from lung cancer screening.