Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
Mapping the invisible: a Bayesian spatio-temporal analysis of male breast cancer mortality inequalities across Spanish provinces, 1999-2023.
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Cayuela Lucía, Pereyra-Rodríguez José-Juan, Rodríguez-Hernández Juan Carlos, Machancoses Francisco H, Cayuela Aurelio
Аннотация
BACKGROUND: Male breast cancer (MBC) is a rare malignancy with marked geographic variation. This study presents the first nationwide spatio-temporal analysis of MBC mortality across Spain's 52 administrative units from 1999-2023.
METHODS: We conducted an ecological spatio-temporal study analyzing 1,931 MBC deaths in Spain. Using indirect age standardization and 80 Bayesian hierarchical models, the best model incorporated Leroux spatial effects, first-order random walk temporal effects, and type II interaction. Model performance was evaluated using the Watanabe-Akaike information criterion and posterior predictive checks to estimate province-specific relative risks (RR) and posterior probabilities (PP) of excess risk.
RESULTS: The selected model demonstrated high predictive accuracy, with a root mean squared error of 4.65. Temporal effects accounted for most of the variability (51.5%). National mortality declined from an elevated risk in 1999 (RR 1.16; PP 0.96) to a reduced risk in 2023 (RR 0.89; PP 0.08). Spatial heterogeneity persisted, with excess risk concentrated in north-western Spain, particularly in A Coruña (period RR 1.23, 95% credible interval 1.02-1.48; PP 0.99). In contrast, Barcelona showed lower risk (RR 0.86, 95% credible interval 0.75-0.98; PP 0.01). Several provinces exhibited transient increases in risk around 2012-2013.
CONCLUSION: The decline in Spanish MBC mortality marks a significant public health success. However, the persistent geographic inequality, particularly the excess risk in A Coruña, identifies a clear priority for future research. These findings offer a robust foundation for integrating clinical and genomic data to determine the drivers of these patterns and develop targeted interventions.
METHODS: We conducted an ecological spatio-temporal study analyzing 1,931 MBC deaths in Spain. Using indirect age standardization and 80 Bayesian hierarchical models, the best model incorporated Leroux spatial effects, first-order random walk temporal effects, and type II interaction. Model performance was evaluated using the Watanabe-Akaike information criterion and posterior predictive checks to estimate province-specific relative risks (RR) and posterior probabilities (PP) of excess risk.
RESULTS: The selected model demonstrated high predictive accuracy, with a root mean squared error of 4.65. Temporal effects accounted for most of the variability (51.5%). National mortality declined from an elevated risk in 1999 (RR 1.16; PP 0.96) to a reduced risk in 2023 (RR 0.89; PP 0.08). Spatial heterogeneity persisted, with excess risk concentrated in north-western Spain, particularly in A Coruña (period RR 1.23, 95% credible interval 1.02-1.48; PP 0.99). In contrast, Barcelona showed lower risk (RR 0.86, 95% credible interval 0.75-0.98; PP 0.01). Several provinces exhibited transient increases in risk around 2012-2013.
CONCLUSION: The decline in Spanish MBC mortality marks a significant public health success. However, the persistent geographic inequality, particularly the excess risk in A Coruña, identifies a clear priority for future research. These findings offer a robust foundation for integrating clinical and genomic data to determine the drivers of these patterns and develop targeted interventions.