Frits H M van Osch1,2, Jelle Vlaanderen3, Sylvia H J Jochems1,2, Cristina Bosetti4, Jerry Polesel5, Stefano Porru6,7, Angela Carta7,8, Klaus Golka9, Xuejuan Jiang10,11, Mariana C Stern10, Wei-De Zhong12, Eliane Kellen13, Hermann Pohlabeln14, Li Tang15, James Marshall15, Gunnar Steineck16, Margaret R Karagas17, Kenneth C Johnson18, Zuo-Feng Zhang19, Jack A Taylor20, Carlo La Vecchia21, Richard T Bryan2, Frederik J van Schooten22, Anke Wesselius1, Maurice P Zeegers1,2,23. 1. From the Department of Complex Genetics, Nutrition and Translational Research in Metabolism (School NUTRIM), Maastricht University, Maastricht, The Netherlands. 2. Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom. 3. Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands. 4. Unit of Cancer Epidemiology, Department of Oncology, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri Via Giuseppe La Masa, Milan, Italy. 5. Unit of Cancer Epidemiology, CRO Aviano National Cancer Institute, Aviano (PN), Italy. 6. Department of Diagnostics and Public Health, Section of Occupational Health, University of Verona, Italy. 7. University Research Center "Integrated Models for Prevention and Protection in Environmental and Occupational Health" MISTRAL, University of Brescia, Italy. 8. Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Italy. 9. Leibniz Research Centre for Working Environment and Human Factors, Sektion Lebenswissenschaften Dortmund, Germany. 10. Department of Preventive Medicine, University of Southern California, Los Angeles, CA. 11. Department of Ophthalmology, University of Southern California, Los Angeles, CA. 12. Department of Urology, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, China. 13. Leuven University Centre for Cancer Prevention (LUCK), Leuven, Belgium. 14. Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany. 15. Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY. 16. Department of Oncology & Pathology, Division of Clinical Cancer Epidemiology, Karolinska Hospital, Stockholm, Sweden. 17. Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH. 18. Department of Epidemiology and Community Medicine, University of Ottawa, ON, Canada. 19. Departments of Epidemiology, UCLA Center for Environmental Genomics, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, CA. 20. Epidemiology Branch, and Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC. 21. Department of Clinical Medicine and Community Health - Università degli Studi di Milano, Milan, Italy. 22. Department of Pharmacology and Toxicology, NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands. 23. Department of Complex Genetics, Public Health and Primary Care (School CAPHRI), Maastricht University, Maastricht, The Netherlands.
Abstract
BACKGROUND: Few studies have modeled smoking histories by combining smoking intensity and duration to show what profile of smoking behavior is associated with highest risk of bladder cancer. This study aims to provide insight into the association between smoking exposure history and bladder cancer risk by modeling both smoking intensity and duration in a pooled analysis. METHODS: We used data from 15 case-control studies included in the bladder cancer epidemiology and nutritional determinants study, including a total of 6,874 cases and 17,727 controls. To jointly interpret the effects of intensity and duration of smoking, we modeled excess odds ratios per pack-year by intensity continuously to estimate the risk difference between smokers with long duration/low intensity and short duration/high intensity. RESULTS: The pattern observed from the pooled excess odds ratios model indicated that for a fixed number of pack-years, smoking for a longer duration at lower intensity was more deleterious for bladder cancer risk than smoking more cigarettes/day for a shorter duration. We observed similar patterns within individual study samples. CONCLUSIONS: This pooled analysis shows that long duration/low intensity smoking is associated with a greater increase in bladder cancer risk than short duration/high intensity smoking within equal pack-year categories, thus confirming studies in other smoking-related cancers and demonstrating that reducing exposure history to a single metric such as pack-years was too restrictive.
BACKGROUND: Few studies have modeled smoking histories by combining smoking intensity and duration to show what profile of smoking behavior is associated with highest risk of bladder cancer. This study aims to provide insight into the association between smoking exposure history and bladder cancer risk by modeling both smoking intensity and duration in a pooled analysis. METHODS: We used data from 15 case-control studies included in the bladder cancer epidemiology and nutritional determinants study, including a total of 6,874 cases and 17,727 controls. To jointly interpret the effects of intensity and duration of smoking, we modeled excess odds ratios per pack-year by intensity continuously to estimate the risk difference between smokers with long duration/low intensity and short duration/high intensity. RESULTS: The pattern observed from the pooled excess odds ratios model indicated that for a fixed number of pack-years, smoking for a longer duration at lower intensity was more deleterious for bladder cancer risk than smoking more cigarettes/day for a shorter duration. We observed similar patterns within individual study samples. CONCLUSIONS: This pooled analysis shows that long duration/low intensity smoking is associated with a greater increase in bladder cancer risk than short duration/high intensity smoking within equal pack-year categories, thus confirming studies in other smoking-related cancers and demonstrating that reducing exposure history to a single metric such as pack-years was too restrictive.
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