부산대학교 도서관

Background: Spatial scan statistic has been shown as a useful tool to investigate spatial patterns and detecting the spatial clusters of cancer. This study conducted to study spatial analysis of breast cancer and its late-stage cases, one of the most common women cancers in Iran and the world. Methods: We used space-time and purely spatial scan statistic implemented in SaTScan software to detect clusters of breast cancer and late-stage cases, at city level by applying Poisson and Bernoulli distribution. Data on 40017 of breast cancer cases that reported to the Ministry of Health and Medical Education (MOHME) during 2005 to 2010 were included. Results: Purely spatial and spatiotemporal high rates significant clusters of breast cancer and its late-stage cases with Poisson distribution were in the same geographical area including southwest, north, and northeast. Conclusion: Significant clusters areas have probably differences with other areas in terms of delay in diagnosis and access to appropriate health services because late-stage breast cancer cases had the greatest impact on formation of clusters. However, more studies are essential to be conducted in different areas of country to explain more precisely clusters detected areas and detecting reasonable justification for existence of significant clusters.