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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

https://doi.org/10.1093/aje/kwm089

20040683

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

AJEPAS

20070815

Journal Article

lubinj@mail.nih.gov

Grant

2007

Grant-Number-T42-OH-008491

4

0002-9262

American Journal of Epidemiology

CA; IA; MD; NC; NJ; MO

University of Iowa