Cigarette smoking and cancer risk: modeling total exposure and intensity.
Lubin-JH; Alavanja-MCR; Caporaso-N; Brown-LM; Brownson-RC; Field-RW; Garcia-Closas-M; Hartge-P; Hauptmann-M; Hayes-RB; Kleinerman-R; Kogevinas-M; Krewski-D; Langholz-B; Létourneau-EG; Lynch-CF; Malats-N; Sandler-DP; Schaffrath-Rosario-A; Schoenberg-JB; Silverman-DT; Wang-Z; Wichmann-H-E; Wilcox-HB; Zielinski-JM
Am J Epidemiol 2007 Aug; 166(4):479-489
A recent analysis showed that the excess odds ratio (EOR) for lung cancer due to smoking can be modeled by a function which is linear in total pack-years and exponential in the logarithm of smoking intensity and its square. Below 15-20 cigarettes per day, the EOR/pack-year increased with intensity (direct exposure rate or enhanced potency effect), suggesting greater risk for a total exposure delivered at higher intensity (for a shorter duration) than for an equivalent exposure delivered at lower intensity. Above 20 cigarettes per day, the EOR/pack-year decreased with increasing intensity (inverse exposure rate or reduced potency effect), suggesting greater risk for a total exposure delivered at lower intensity (for a longer duration) than for an equivalent exposure delivered at higher intensity. The authors applied this model to data from 10 case-control studies of cancer, including cancers of the lung, bladder, oral cavity, pancreas, and esophagus. At lower intensities, there was enhanced potency for several cancer sites, but narrow ranges for pack-years increased uncertainty, precluding definitive conclusions. At higher intensities, there was a consistent reduced potency effect across studies. The intensity effects were statistically homogeneous, indicating that after accounting for risk from total pack-years, intensity patterns were comparable across the diverse cancer sites.
Humans; Men; Women; Smoking; Case-studies; Age-groups; Neoplasms; Epidemiology; Statistical-analysis; Risk-factors; Models; Lung-cancer; Lung; Lung-disease; Lung-disorders; Lung-function; Pulmonary-cancer; Pulmonary-function; Pulmonary-system; Pulmonary-system-disorders;
Author Keywords: case-control studies; epidemiologic methods; statistical models; neoplasms; risk; smoking
Dr. Jay H. Lubin, Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Blvd., Rockville, MD 20852
American Journal of Epidemiology
CA; IA; MD; NC; NJ; MO
University of Iowa