Multivariate Bayesian models with flexible shared interactions for analyzing spatio-temporal patterns of rare cancers

Retegui Goñi, Garazi; Etxeberria Andueza, Jaione; Ugarte Martínez, María Dolores

Publication:
Multivariate Bayesian models with flexible shared interactions for analyzing spatio-temporal patterns of rare cancers

dc.contributor.author	Retegui Goñi, Garazi
dc.contributor.author	Etxeberria Andueza, Jaione
dc.contributor.author	Ugarte Martínez, María Dolores
dc.contributor.department	Estadística, Informática y Matemáticas	es_ES
dc.contributor.department	Estatistika, Informatika eta Matematika	eu
dc.contributor.department	Institute for Advanced Materials and Mathematics - INAMAT2	en
dc.contributor.funder	Universidad Pública de Navarra - Nafarroako Unibertsitate Publikoa	es
dc.date.accessioned	2024-08-12T09:18:32Z
dc.date.available	2024-08-12T09:18:32Z
dc.date.issued	2024
dc.date.updated	2024-08-12T09:14:41Z
dc.description.abstract	Rare cancers afect millions of people worldwide each year. However, estimating incidence or mortality rates associated with rare cancers presents important difculties and poses new statistical methodological challenges. In this paper, we expand the collection of multivariate spatio-temporal models by introducing adaptable shared spatio-temporal components to enable a comprehensive analysis of both incidence and cancer mortality in rare cancer cases. These models allow the modulation of spatio-temporal efects between incidence and mortality, allowing for changes in their relationship over time. The new models have been implemented in INLA using r-generic constructions. We conduct a simulation study to evaluate the performance of the new spatio-temporal models. Our results show that multivariate spatio-temporal models incorporating a fexible shared spatio-temporal term outperform conventional multivariate spatio-temporal models that include specifc spatio-temporal efects for each health outcome. We use these models to analyze incidence and mortality data for pancreatic cancer and leukaemia among males across 142 administrative health care districts of Great Britain over a span of nine biennial periods (2002-2019)	en
dc.description.sponsorship	The work was supported by Project PID2020-113125RB-I00/MCIN/AEI/10.13039/501100011033, Project UNEDPAM/PI/PR24/05A and Ayudas Predoctorales Santander UPNA 2021-2022. Open Access funding provided by Universidad Pública de Navarra
dc.format.mimetype	application/pdf
dc.format.mimetype	application/zip
dc.identifier.citation	Retegui, G., Etxeberria, J., Ugarte, M. D. (2024) Multivariate Bayesian models with flexible shared interactions for analyzing spatio-temporal patterns of rare cancers. Environmental and Ecological Statistics, 1-31. https://doi.org/10.1007/s10651-024-00630-w.
dc.identifier.doi	10.1007/s10651-024-00630-w
dc.identifier.issn	1352-8505
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/50682
dc.language.iso	eng
dc.publisher	Springer
dc.relation.ispartof	Environmental and Ecological Statistics (2024)
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113125RB-I00/ES/	en
dc.relation.publisherversion	https://doi.org/10.1007/s10651-024-00630-w
dc.rights	© 2024 The author(s). This article is licensed under a Creative Commons Attribution 4.0 International License
dc.rights.accessRights	info:eu-repo/semantics/openAccess
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	Leukaemia	en
dc.subject	Multivariate disease mapping	en
dc.subject	Pancreatic cancer	en
dc.subject	Spatiotemporal	en
dc.subject	shared component models	en
dc.title	Multivariate Bayesian models with flexible shared interactions for analyzing spatio-temporal patterns of rare cancers	en
dc.type	info:eu-repo/semantics/article
dc.type.version	info:eu-repo/semantics/publishedVersion
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