4.6 Article

Modeling the Complex Exposure History of Smoking in Predicting Bladder Cancer A Pooled Analysis of 15 Case-Control Studies

Journal

EPIDEMIOLOGY
Volume 30, Issue 3, Pages 458-465

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/EDE.0000000000000964

Keywords

Bladder cancer; Cancer risk; Pooled analysis; Smoking history; statistical modeling

Funding

  1. World Cancer Research Fund
  2. NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES [ZIAES049033, ZIAES049032] Funding Source: NIH RePORTER

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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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