title: Trends of breast cancer incidence in Iran during 2004-2008: a Bayesian space-time model.
abstract: BACKGROUND
  Breast cancer is the most frequently diagnosed cancer in women and estimating its relative risks and trends of incidence at the area-level is helpful for health policy makers. However, traditional methods of estimation which do not take spatial heterogeneity into account suffer from drawbacks and their results may be misleading, as the estimated maps of incidence vary dramatically in neighboring areas. Spatial methods have been proposed to overcome drawbacks of traditional methods by including spatial sources of variation in the model to produce smoother maps.
  
  
  METHODS
  In this study we analyzed the breast cancer data in Iran during 2004-2008. We used a method proposed to cover spatial and temporal effects simultaneously and their interactions to study trends of breast cancer incidence in Iran.
  
  
  RESULTS
  The results agree with previous studies but provide new information about two main issues regarding the trend of breast cancer in provinces of Iran. First, this model discovered provinces with high relative risks of breast cancer during the 5 years of the study. Second, new information was provided with respect to overall trend trends o. East-Azerbaijan, Golestan, North-Khorasan, and Khorasan-Razavi had the highest increases in rates of breast cancer incidence whilst Tehran, Isfahan, and Yazd had the highest incidence rates during 2004-2008.
  
  
  CONCLUSIONS
  Using spatial methods can provide more accurate and detailed information about the incidence or prevalence of a disease. These models can specify provinces with different health priorities in terms of needs for therapy and drugs or demands for efficient education, screening, and preventive policy into action.
authors.affiliation: Department of Biostatistics and Epidemiology, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran E-mail : behzad.mahaki@gmail.com.
authors.forename: Tohid
authors.initials: T
authors.lastname: Jafari-Koshki
authors.forename: Volker Johann
authors.initials: VJ
authors.lastname: Schmid
authors.forename: Behzad
authors.initials: B
authors.lastname: Mahaki
mesh_terms: D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000453:epidemiology*; D005260:Female; D005843:Geography; D006801:Humans; D007492:Iran / Q000453:epidemiology; D008962:Models, Theoretical; D015995:Prevalence; D012042:Registries