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Spatial gender-age-period-cohort analysis of pancreatic cancer mortality in Spain (1990-2013).

Jaione EtxeberriaTomás GoicoaGonzalo López-AbenteAndrea RieblerMaría Dolores Ugarte
Published in: PloS one (2017)
Recently, the interest in studying pancreatic cancer mortality has increased due to its high lethality. In this work a detailed analysis of pancreatic cancer mortality in Spanish provinces was performed using recent data. A set of multivariate spatial gender-age-period-cohort models was considered to look for potential candidates to analyze pancreatic cancer mortality rates. The selected model combines features of APC (age-period-cohort) models with disease mapping approaches. To ensure model identifiability sum-to-zero constraints were applied. A fully Bayesian approach based on integrated nested Laplace approximations (INLA) was considered for model fitting and inference. Sensitivity analyses were also conducted. In general, estimated average rates by age, cohort, and period are higher in males than in females. The higher differences according to age between males and females correspond to the age groups [65, 70), [70, 75), and [75, 80). Regarding the cohort, the greatest difference between men and women is observed for those born between the forties and the sixties. From there on, the younger the birth cohort is, the smaller the difference becomes. Some cohort differences are also identified by regions and age-groups. The spatial pattern indicates a North-South gradient of pancreatic cancer mortality in Spain, the provinces in the North being the ones with the highest effects on mortality during the studied period. Finally, the space-time evolution shows that the space pattern has changed little over time.
Keyphrases
  • cardiovascular events
  • risk factors
  • mental health
  • type diabetes
  • coronary artery disease
  • high resolution
  • machine learning
  • risk assessment
  • tertiary care
  • single cell
  • deep learning
  • low birth weight