Adjustment For Misclassification Error In Iranís Cancer Mortality Registration, Using Bayesian Method

Pourhoseingholi MOHAMAD AMIN, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Iran

1 Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2 Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Purpose: According to the Iranian death registry, about 15% to 20% of death statistics are recorded in misclassified categories such as septicemia, cancer without mention of details, and other ill-defined conditions. It calls misclassification error (disagreement between the observed and the true value), that makes the registered data inaccurate and often leads to major problems in epidemiological analysis with biased estimates of burden, and underestimating the health risks. The aim of this study is to use Bayesian method to estimate the rate of gastric cancer deaths that have registered as cancer (without label) in Iran registry system.
Methods: National death Statistic from 2006 to 2010 for gastric cancer [ICD-10; C16] which reported annually by the Ministry of Health and Medical Education included in this study. To correct the rate of gastric cancer mortality, a Bayesian approach was used with Poisson count regression and beta prior for male and female categories. Reported percent for misclassified cause of death were used as parameters of beta distribution.
Results: According to the Bayesian re-estimate, about 5 to 6 percent of deaths due to gastric cancer have registered as cancer without mentioning details. It makes an undercount of gastric cancer mortality in Iranian population.
Conclusions: Cancer registry data are important to monitor the effects of screening programs, earlier diagnosis and other prognostic factors. Although it seems that the misclassification rate in registry has been reduced, it is still exists as a major problem. Therefore, policy makers who determine research and treatment priorities on death rates should consider this underreported data in order to setup appropriate cancer prevention programs. To achieve this goal the accuracy of registration system should be increased specially in registering causes of deaths.