The national trend of the gastric cancer burden in Iran from 1990 to 2017.

INTRODUCTION: Gastric cancer (GC), the leading cause of cancer mortality, is the third most common cancer in Iran. To our knowledge, there have been few accurate estimates on the burden of GC in Iran. Therefore, as part of the Global Burden of Diseases Study 2017 (GBD 2017), we aimed to study and illustrate the burden of GC and to compare rates by sex and age groups at the national level in Iran from 1990 to 2017. METHODS: We extracted data related to the 1990-2017 period from the GBD study. To report the burden of GC, we used disability adjusted life years (DALYs), mortality, incidence, and prevalence rates in different sex and age groups in Iran during the 1990-2017 period. Decomposition analysis was also performed to evaluate the roots change in incident cases. RESULTS: At a national level, the age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized DALYs rate (ASDR) in 2017 were 22.9 (95% uncertainty interval [UI]: 22.1-23.9), 14.6 (14.1-15.2), 14.9 (14.4-15.4), and 296.8 (286.3-308.7) per 100,000 population, respectively. Over the 1990-2017 period, the average annual percent changes in all of the studied age-standardized rates were negative. Moreover, the male to female sex ratios of all estimates were greater than one. The incidence rate, prevalence rate, and mortality rate slowly began to increase at the age of 50 and reached its highest level among people aged 80 years and over. CONCLUSION: The GC age-standardized rates revealed a downward trend from 1990 to 2017. The current study provides comprehensive knowledge about the GC burden in Iran. Therefore, it can help the appropriate allocation of resources for GC to expand preventive programs by reducing exposure to risk factors and Helicobacter pylori infection and by recommending increased consumption of fruits and vegetables. Also, expanding GC screening programs with laboratory tests or endoscopy can be an important step towards the reduction of the GC burden.