Tehran University of Medical Sciences Iranian Journal of Public Health 2251-6085 46 10 2017 10 08 1413 1421 Meysam OLFATIFAR Student Research Committee, Hamadan University of Medical Sciences, Hamadan, Iran AND Dept. of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran Manoochehr KARAMI Dept. of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran AND Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran Seyed Mehdi HOSSEINI Dept. of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran Masoud PARVIN Student Research Committee, Hamadan University of Medical Sciences, Hamadan, Iran Abbas MOGHIMBEIGI Dept. of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran Ahmad KOUSHA Center for Noncommunicable Diseases Control and Prevention, Deputy of Health, Ministry of Health and Medical Education, Tehran, Iran Ali MOTLAGH Cancer Office, Non-Communicable Diseases, Deputy of Health, Ministry of Health and Medical Education, Tehran, Iran AND Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran Mansoureh ABDOLAHI Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran Elham PARTOVIPOUR Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran 2017 10 07 2017 10 07 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.     https://ijph.tums.ac.ir/index.php/ijph/article/view/11254 https://ijph.tums.ac.ir/index.php/ijph/article/download/11254/5765