Tricia L Larose1,2, Florence Guida1, Anouar Fanidi1,3, Arnulf Langhammer4, Kristian Kveem2,4, Victoria L Stevens5, Eric J Jacobs5, Stephanie A Smith-Warner6,7, Edward Giovannucci6,7,8, Demetrius Albanes9, Stephanie J Weinstein9, Neal D Freedman9, Ross Prentice10, Mary Pettinger10, Cynthia A Thomson11, Qiuyin Cai12, Jie Wu12, William J Blot12,13, Alan A Arslan14, Anne Zeleniuch-Jacquotte15, Loic Le Marchand16, Lynne R Wilkens16, Christopher A Haiman16, Xuehong Zhang8, Meir J Stampfer6,7,8, Allison M Hodge17, Graham G Giles17,18, Gianluca Severi17,19,20, Mikael Johansson21, Kjell Grankvist21, Renwei Wang22, Jian-Min Yuan22,23, Yu-Tang Gao24, Woon-Puay Koh25, Xiao-Ou Shu26, Wei Zheng26, Yong-Bing Xiang27, Honglan Li28, Qing Lan28, Kala Visvanathan29, Judith Hoffman Bolton29, Per Magne Ueland30,31, Øivind Midttun32, Neil Caporaso9, Mark Purdue9, Howard D Sesso6,33,34, Julie E Buring6,34, I-Min Lee6,34, J Michael Gaziano33,34,35, Jonas Manjer36, Hans Brunnström37, Paul Brennan1, Mattias Johansson1. 1. Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France. 2. K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway. 3. MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK. 4. HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway. 5. Epidemiology Research Program, American Cancer Society, Atlanta, GA, USA. 6. Department of Epidemiology. 7. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 8. Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. 9. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA. 10. Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 11. Health Promotion Sciences, University of Arizona, Tucson, AZ, USA. 12. Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA. 13. International Epidemiology Institute, Rockville, MD, USA. 14. Departments of Obstetrics and Gynecology, Population Health, and Environmental Medicine. 15. Department of Population Health, New York University School of Medicine, New York, NY, USA. 16. Epidemiology Program, Cancer Research Center of Hawaii, University of Hawaii, Honolulu, HI, USA. 17. Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, VIC, Australia. 18. Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, VIC, Australia. 19. Italian Institute for Genomic Medicine (IIGM), Torino, Piedmont, Italy. 20. Centre de Recherche en Epidemiologie et Saé des Populations (CESP) UMR1018 Inserm, Facultés de Médicine Université Paris-Saclay, Villejuif, France. 21. Department of Radiation Sciences, Umeå University, Umeå, Västerbotten, Sweden. 22. UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA. 23. Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA. 24. Department of Epidemiology, Shanghai Jiaotong University, Shanghai, China. 25. Health Services and Systems Research, Duke-NUS Medical School, Singapore. 26. Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA. 27. State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Shanghai Jiaotong University School of Medicine, Shanghai, China. 28. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. 29. George W. Comstock Center for Public Health Research and Prevention Health Monitoring Unit, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. 30. Department of Clinical Sciences, Laboratory of Clinical Biochemistry, University of Bergen, Bergen, Norway. 31. Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway. 32. Bevital AS, Bergen, Norway. 33. Division of Aging, Brigham and Women's Hospital, Boston, MA, USA. 34. Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA. 35. Boston VA Medical Center, Boston, MA, USA. 36. Department of Surgery, Skåne University Hospital Malmö Lund University, Malmö, Sweden. 37. Department of Clinical Sciences Lund, Laboratory Medicine Region Skåne, Lund University, Lund, Sweden.
Abstract
Background: Self-reported smoking is the principal measure used to assess lung cancer risk in epidemiological studies. We evaluated if circulating cotinine-a nicotine metabolite and biomarker of recent tobacco exposure-provides additional information on lung cancer risk. Methods: The study was conducted in the Lung Cancer Cohort Consortium (LC3) involving 20 prospective cohort studies. Pre-diagnostic serum cotinine concentrations were measured in one laboratory on 5364 lung cancer cases and 5364 individually matched controls. We used conditional logistic regression to evaluate the association between circulating cotinine and lung cancer, and assessed if cotinine provided additional risk-discriminative information compared with self-reported smoking (smoking status, smoking intensity, smoking duration), using receiver-operating characteristic (ROC) curve analysis. Results: We observed a strong positive association between cotinine and lung cancer risk for current smokers [odds ratio (OR ) per 500 nmol/L increase in cotinine (OR500): 1.39, 95% confidence interval (CI): 1.32-1.47]. Cotinine concentrations consistent with active smoking (≥115 nmol/L) were common in former smokers (cases: 14.6%; controls: 9.2%) and rare in never smokers (cases: 2.7%; controls: 0.8%). Former and never smokers with cotinine concentrations indicative of active smoking (≥115 nmol/L) also showed increased lung cancer risk. For current smokers, the risk-discriminative performance of cotinine combined with self-reported smoking (AUCintegrated: 0.69, 95% CI: 0.68-0.71) yielded a small improvement over self-reported smoking alone (AUCsmoke: 0.66, 95% CI: 0.64-0.68) (P = 1.5x10-9). Conclusions: Circulating cotinine concentrations are consistently associated with lung cancer risk for current smokers and provide additional risk-discriminative information compared with self-report smoking alone.
Background: Self-reported smoking is the principal measure used to assess lung cancer risk in epidemiological studies. We evaluated if circulating cotinine-a nicotine metabolite and biomarker of recent tobacco exposure-provides additional information on lung cancer risk. Methods: The study was conducted in the Lung Cancer Cohort Consortium (LC3) involving 20 prospective cohort studies. Pre-diagnostic serum cotinine concentrations were measured in one laboratory on 5364 lung cancer cases and 5364 individually matched controls. We used conditional logistic regression to evaluate the association between circulating cotinine and lung cancer, and assessed if cotinine provided additional risk-discriminative information compared with self-reported smoking (smoking status, smoking intensity, smoking duration), using receiver-operating characteristic (ROC) curve analysis. Results: We observed a strong positive association between cotinine and lung cancer risk for current smokers [odds ratio (OR ) per 500 nmol/L increase in cotinine (OR500): 1.39, 95% confidence interval (CI): 1.32-1.47]. Cotinine concentrations consistent with active smoking (≥115 nmol/L) were common in former smokers (cases: 14.6%; controls: 9.2%) and rare in never smokers (cases: 2.7%; controls: 0.8%). Former and never smokers with cotinine concentrations indicative of active smoking (≥115 nmol/L) also showed increased lung cancer risk. For current smokers, the risk-discriminative performance of cotinine combined with self-reported smoking (AUCintegrated: 0.69, 95% CI: 0.68-0.71) yielded a small improvement over self-reported smoking alone (AUCsmoke: 0.66, 95% CI: 0.64-0.68) (P = 1.5x10-9). Conclusions: Circulating cotinine concentrations are consistently associated with lung cancer risk for current smokers and provide additional risk-discriminative information compared with self-report smoking alone.
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