Retegui Goñi, GaraziEtxeberria Andueza, JaioneRiebler, AndreaUgarte Martínez, María Dolores2023-09-112023-09-112023Retegui, G., Etxeberria, J., Riebler, A., Ugarte, M. D. (2023) Predicting cancer incidence in regions without population-based cancer registries using mortality. Journal of the Royal Statistical Society: Series A (Statistics in Society), 1-16. https://doi.org/10.1093/jrsssa/qnad077.0964-199810.1093/jrsssa/qnad077https://academica-e.unavarra.es/handle/2454/46260Cancer incidence numbers are routinely recorded by national or regional population-based cancer registries (PBCRs). However, in most southern European countries, the local PBCRs cover only a fraction of the country. Therefore, national cancer incidence can be only obtained through estimation methods. In this paper, we predict incidence rates in areas without cancer registry using multivariate spatial models modelling jointly cancer incidence and mortality. To evaluate the proposal, we use cancer incidence and mortality data from all the German states. We also conduct a simulation study by mimicking the real case of Spain considering different scenarios depending on the similarity of spatial patterns between incidence and mortality, the levels of lethality, and varying the amount of incidence data available. The new proposal provides good interval estimates in regions without PBCRs and reduces the relative error in estimating national incidence compared to one of the most widely used methodologies.application/pdfeng© The Royal Statistical Society 2023. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Bayesian inferenceCancer incidenceDisease mappingMultivariate spatial modelsPredictionsinfo:eu-repo/semantics/article2023-09-11Acceso abierto / Sarbide irekiainfo:eu-repo/semantics/openAccess