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

Rare cancers affect millions of people worldwide each year. However, estimating incidence or mortality rates associated with rare cancers presents important difficulties and poses new statistical methodological challenges. In this paper, we expand the collection of multivariate spatio-temporal model...

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Bibliographic Details
Published in:Environmental and ecological statistics 2024-07, Vol.31 (4), p.977-1007
Main Authors: Retegui, Garazi, Etxeberria, Jaione, Ugarte, María Dolores
Format: Article
Language:English
Subjects:
Bayesian analysis
Biomedical and Life Sciences
Cancer
Chemistry and Earth Sciences
Computer Science
Ecology
Health Sciences
Leukemia
Life Sciences
Math. Appl. in Environmental Science
Mathematical models
Medicine
Mortality
Multivariate analysis
Pancreas
Pancreatic cancer
Physics
Probability theory
Spatiotemporal data
Statistical methods
Statistical models
Statistics for Engineering
Statistics for Life Sciences
Theoretical Ecology/Statistics
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Summary:Rare cancers affect millions of people worldwide each year. However, estimating incidence or mortality rates associated with rare cancers presents important difficulties 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 effects 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 flexible shared spatio-temporal term outperform conventional multivariate spatio-temporal models that include specific spatio-temporal effects 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).
ISSN:1352-8505
1573-3009
DOI:10.1007/s10651-024-00630-w