Retegui Goñi, Garazi

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https://academica-e.unavarra.es/handle/2454/50684

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Retegui Goñi

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Garazi

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Estadística, Informática y Matemáticas

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InaMat2. Instituto de Investigación en Materiales Avanzados y Matemáticas

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0009-0008-0005-2501

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751865

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812116

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Author: Ugarte Martínez, María Dolores × Subject: Bayesian inference ×

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    PublicationOpen Access
    Predicting cancer incidence in regions without population-based cancer registries using mortality
    (Oxford University Press, 2023) Retegui Goñi, Garazi; Etxeberria Andueza, Jaione; Riebler, Andrea; Ugarte Martínez, María Dolores; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute for Advanced Materials and Mathematics - INAMAT2; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA2018-11
    Cancer 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.