BACKGROUND

The intrinsic limitations of studying rare cancers poses challenges to undertaking studies with adequate statistical power. Therefore, efforts are needed to exploit available, high-quality resources. The European Prospective Investigation into Cancer and Nutrition (EPIC) is a large-scale longitudinal cohort with great potential for rare cancer research.

MATERIALS AND METHODS

We have used the EPIC data, which includes lifestyle, diet, and health information, on ∼520  000 participants recruited across Europe. Rare cancers were identified according to the RARE CAncer REgistry network (RARECAREnet) classification, which includes incidence-based categorization and detailed morphological and site-specific information.

RESULTS

An interactive R Shiny web application was developed to explore EPIC data interactively, available at https://epic-rare-cancers-explorer.opendata.iarc.who.int. Among the EPIC participants, 11 450 incident cases of rare cancers were identified, with data currently available for 8851 of them, encompassing a wide range of cancer sites and morphologies. Sex ratios and incidence rates align with previously reported statistics. The R Shiny web application was designed for preliminary data analysis and hypothesis generation, aiding researchers in assessing the feasibility and potential of epidemiological studies. Taking head and neck cancers as a use case, we confirmed the strong association of these tumors with tobacco and alcohol consumption, proving the suitability of EPIC for identifying risk factors for rare cancers. However, it is important to note that, as with all observational studies, the associations reported in this article do not establish causality.

CONCLUSION

The development of the EPIC rare cancers database, accompanied by the development of an interactive web application, represents a significant step forward in rare cancer research embedded within a large-scale population-based cohort. It is therefore vital to promote awareness of this resource within the research community.