Lessons learned from the INHANCE consortium: An overview of recent results on head and neck cancer

Objective: To summarize the latest evidence on head and neck cancer epidemiology from the International Head and Neck Cancer Epidemiology (INHANCE) consortium. Subjects and Methods: INHANCE was established in 2004 to elucidate the etiology of head and neck cancer through pooled analyses of individual-level data on a large scale. We summarize results from recent INHANCE-based publications updating our 2015 overview. Results: Seventeen papers were published between 2015 and May 2020. These studies further define the nature of risks associated with tobacco and alcohol, and occupational exposures on head and neck cancer. The beneficial effects on incidence of head and neck cancer were identified for good oral health, endogenous and exogenous hormonal factors, and selected aspects of diet related to fruit and vegetables. INHANCE has begun to develop risk prediction models and to pool follow-up data on their studies, finding that ~30% of cases had cancer recurrence and 9% second primary cancers, with overall- and disease-specific 5-year-survival of 51% and 57%, respectively. Conclusions: The number and importance of INHANCE scientific findings provides further evidence of the advantages of large-scale internationally collaborative projects and will support the development of prevention strategies

Bivariate spline models to assess the joint effect of intensity and duration of alcohol drinking and cancer of the oral cavity: a focus on a novel approach

When modeling the relationship between a response and some continuous covariates, assuming linearity may be too restrictive in many contexts. Naive solutions to overcome this limitation, such as categorisation of the predictor, have well-known drawbacks. A viable alternative is represented by spline functions. In epidemiological studies, the number and position of knots usually have an important meaning. Therefore, special attention should be posed to techniques that allow to choose the number and position of knots. The aim of the present work is to: 1. introduce a two-step Bayesian procedure within the semiparametric generalised linear model framework to be applied in epidemiological studies where the effect of a continuous exposure on risk is under investigation; 2. show how this framework is applied in a bivariate context where the aim is to modeling the joint effect of intensity and duration of alcohol drinking in cancer of the oral cavity