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Bayesian analysis of gastric cancer mortality in Iranian population

Mohamad Amin Pourhoseingholi, Soghrat Faghihzadeh, Ebrahim Hajizadeh, Alireza Abadi




Aim: The aim of this study is to estimate gastric cancer (GC) mortality rate for Iranian population, using Bayesian approach in order to revise the existing classification which is thought to be a misclassification.

Background: Gastric cancer (GC) is an important cause of mortality among many other types of cancer. Data on cancer mortality can be used to guide policy makers in order to setup cancer prevention programs. According to Iranian death registry, about 20% death statistics are still recorded in misclassified categories.

Patients and methods: National Death Statistics Reported by the Ministry of Health and Medical Education (MOH&ME) from 1995 to 2004 is included in this analysis. The Bayesian approach to correct and account for misclassification effects in Poisson count regression with a beta prior is employed to estimate the mortality rate of GC in age and sex group.

Results: According to the Bayesian analysis there were between 30 to 40 percent underreported mortality records in death due to GC and the mortality rate is increased through recent years.

Conclusion: Our findings suggest a substantial undercount of GC mortality in Iranian population. So healthcare policy makers who determine research and treatment priorities on death rates as an indicator of public health priorities should notice this underreported data.


Gastric Cancer; Mortality; Bayesian Analysis

DOI: https://doi.org/10.22037/ghfbb.v3i1.64