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JNCI Journal of the National Cancer Institute 2003 95(6):470-478; doi:10.1093/jnci/95.6.470
© 2003 by Oxford University Press
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Journal of the National Cancer Institute, Vol. 95, No. 6, 470-478, March 19, 2003
© 2003 Oxford University Press


ARTICLE

Variations in Lung Cancer Risk Among Smokers

Peter B. Bach, Michael W. Kattan, Mark D. Thornquist, Mark G. Kris, Ramsey C. Tate, Matt J. Barnett, Lillian J. Hsieh, Colin B. Begg

Affiliations of authors: P. B. Bach (The Health Outcomes Research Group, Department of Epidemiology and Biostatistics and Department of Medicine), M. W. Kattan (The Health Outcomes Research Group, Department of Epidemiology and Biostatistics and Department of Urology), Memorial Sloan-Kettering Cancer Center, New York, NY; M. D. Thornquist, M. J. Barnett, Fred Hutchinson Cancer Research Center, Seattle, WA; M. G. Kris, Department of Medicine, Memorial Sloan-Kettering Cancer Center; R. C. Tate, L. J. Hsieh, C. B. Begg, The Health Outcomes Research Group, Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center.

Correspondence to: Peter B. Bach, M.D., Memorial Sloan-Kettering Cancer Center, 307 E. 63rd St., New York, NY 10021 (e-mail: bachp{at}mskcc.org).

Background: Although there is no proven benefit associated with screening for lung cancer, screening programs are attracting many individuals who perceive themselves to be at high risk due to smoking. We sought to determine whether the risk of lung cancer varies predictably among smokers. Methods: We used data on 18 172 subjects enrolled in the Carotene and Retinol Efficacy Trial (CARET)—a large, randomized trial of lung cancer prevention—to derive a lung cancer risk prediction model. Model inputs included the subject’s age, sex, asbestos exposure history, and smoking history. We assessed the model’s calibration by comparing predicted and observed rates of lung cancer across risk deciles and validated it by assessing the extent to which a model estimated on data from five CARET study sites could predict events in the sixth study site. We then applied the model to evaluate the risk of lung cancer among smokers enrolled in a study of lung cancer screening with computed tomography (CT). Results: The model was internally valid and well calibrated. Ten-year lung cancer risk varied greatly among participants in the CT study, from 15% for a 68-year-old man who has smoked two packs per day for 50 years and continues to smoke, to 0.8% for a 51-year-old woman who smoked one pack per day for 28 years before quitting 9 years earlier. Even among the subset of CT study participants who would be eligible for a clinical trial of cancer prevention, risk varied greatly. Conclusions: The risk of lung cancer varies widely among smokers. Accurate risk prediction may help individuals who are contemplating voluntary screening to balance the potential benefits and risks. Risk prediction may also be useful for researchers designing clinical trials of lung cancer prevention.



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