Pancreatic cancer risk in relation to lifetime smoking patterns, tobacco type, and dose-response relationships
Menée à l'aide de données européennes portant sur 2 009 patients atteints d'un cancer du pancréas et de 1 532 témoins, cette étude analyse l'association entre le tabagisme et le risque de développer la maladie, en fonction des caractéristiques du tabac et de différents facteurs liés aux habitudes de vie
BACKGROUND: Despite smoking being a well-established risk factor for pancreatic cancer (PC), there is a need to further characterize PC risk according to lifespan smoking patterns and other smoking features. Our aim was to deeply investigate them within a large European case-control study. METHODS: Tobacco smoking habits and other relevant information was obtained from 2,009 cases and 1,532 controls recruited in the PanGenEU study using standardized tools. Multivariate logistic regression analysis was performed to evaluate PC risk by smoking characteristics and interactions with other PC risk factors. Fractional polynomials and restricted cubic splines were used to test for non-linearity of the dose-response relationships and to analyse their shape. RESULTS: Relative to never-smokers, current smokers (OR=1.72, 95%CI: 1.39-2.12), those inhaling into the throat (OR=1.48, 95%CI: 1.11-1.99), chest (OR=1.33, 95%CI: 1.12-1.58), or using non-filtered cigarettes (OR=1.69, 95%CI: 1.10-2.61), were all at an increased PC risk. PC risk was highest in current black tobacco smokers (OR=2.09, 95%CI: 1.31-3.41), followed by blond tobacco smokers (OR=1.43, 95%CI: 1.01-2.04). Childhood exposure to tobacco smoke relative to parental smoking was also associated with increased PC risk (OR=1.24, 95%CI: 1.03-1.49). Dose-response relationships for smoking duration, intensity, cumulative dose, and smoking cessation were non-linear and showed different shapes by tobacco type. Effect modification by family history of PC and diabetes was likely. CONCLUSIONS: This study reveals differences in PC risk by tobacco type and other habit characteristics, as well as non-linear risk associations. IMPACT: This characterization of smoking-related PC risk profiles may help in defining PC high-risk populations.