Spatio-temporal mapping of breast and prostate cancers in South Iran from 2014-2017

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In developing countries, cancer screening of all at risk is impractical because of healthcare resource limitations. Thus, determining high-risk areas might be an important first screening step. This study explores incidence patterns of potential high-risk clusters of breast and prostate cancers in southern Iran. Methods: This cross-sectional study was conducted in the province of Kerman, South Iran. Patient data were aggregated at the county and district levels calculating the incidence rate per 100,000 people both for cancers of the breast and the prostate. We used the natural-break classification with five classes to produce descriptive maps. A spatial clustering analysis (Anselin Local Moran’s I ) was used to identify potential clusters and outliers in the pattern of these cancers from 2014 to 2017. Results: There were 1,350 breast cancer patients (including, 42 male cases) and 478 prostate cancer patients in the province of Kerman, Iran during the study period. After 45 years of age, the number of men with diagnosed prostate cancer increased similarly to that of breast cancer for women after 25 years of age. The age-standardised incidence rate of breast cancer for women showed an increase from 29.93 to 32.27 cases per 100,000 people and that of prostate cancer from 13.93 to 15.47 cases per 100,000 during 2014-2017. Cluster analysis at the county level identified high-high clusters of breast cancer in the north-western part of the province for all years studied, but the analysis at the district level showed high-high clusters for only two of the years. With regard to prostate cancer, cluster analysis at the county and district levels identified high-high clusters in this area of the province for two of the study years. Conclusions: North-western Kerman had a significantly higher incidence rate of both breast and prostate cancer than the average, which should help in designing tailored screening and surveillance systems. Furthermore, this study generates new hypotheses regarding the potential relationship between increased incidence of cancers in certain geographical areas and environmental risk factors. Cancer Biology Oncology Spatial Analyses Cluster Analyses Breast Cancer Prostate Cancer Spatio-temporal Geographical Information Systems Iran Figures Figure 1 Figure 1 Figure 2 Figure 2 Figure 3 Figure 3 Figure 4 Figure 4 Figure 5 Figure 5 Figure 6 Figure 6 Figure 7 Figure 7 Figure 8 Figure 8 Background Cancers are the second leading cause of death worldwide (1), which can partly be explained by the fact that the world’s population is ageing (2). Furthermore, human exposure to multiple risk factors has increased the cancer burden worldwide (3). Despite advances in timely diagnosis and medical treatment of neoplasms in recent years, malignancies in middle to low-income countries are expected to almost double by 2030 compared to high-income nations (4). If cancer is diagnosed promptly, cures can sometimes be found and life prolonged leading to considerably lower disease burdens (5, 6). However, health systems, particularly in developing countries, are not capable of screening all people to identify patients in the early stages of the disease. Identifying high-risk geographical areas could help decreasing the cost of screening, finding the people at risk and implementing more efficient diagnostic strategies (7). Investigating high-risk areas should also provide valuable knowledge to scientists about the aetiology of some malignancies (3). Cancer of the breast and the prostate are the two most common, gender-specific malignancies worldwide (8). Furthermore, these neoplasms cause high numbers of disability-adjusted life years (DALYs) (9). Risk factors for these two diseases are diverse and interrelated, as they include genetic (10), social-economic (11) as well as lifestyle and environmental factors (12). Further, there are interactions between these risk factors, particularly with those involving the environment (13, 14), whose spatial variation may lead to heterogeneity in the pattern of cancers in a given geographic catchment area. Studies by Wang et al. (15, 16) found a significant spatial variation of prostate cancer incidence and prostate cancer-specific mortality in Pennsylvania, USA. They evaluated potential effects of individual and county-level risk factors and found that spatial variations in prostate cancer-specific mortality rates existed in Pennsylvania with a particularly high risk in the Pen State catchment area. County-level health and environmental factors might contribute to spatial heterogeneity in prostate cancer-specific mortality as shown by Olfatifar et al. (17), who examined spatial clustering of breast cancer at the provincial level in Iran between 2004 and 2010. Their results highlight that the breast tumour incidence varied across the provinces (17). At the same time, Rohani-Rasaf et al. (18) detected some high-risk regions in Tehran, the capital of Iran, both for cancers of the breast and the prostate. Most studies in Iran have applied spatial analyses at a very coarse level (province scale) and the results are therefore not as useful as a finer scale quite naturally. Geographical information systems (GIS) constitute a set of useful tools for the identification of high-risk areas of cancer occurrence as well as investigation of the environmental effects on cancer incidence (19-21). GIS approaches combine spatial and non-spatial data producing geodatabases that make it possible to perform spatial analyses using this data structure (22, 23). For example, spatial autocorrelation is a method of exploratory data analysis which allows detecting spatial data dependence (24). There are two kinds of spatial autocorrelation methods: global and local statistics. Global methods are more sensitive to departures from the null hypothesis, which examine whether data, here patients, are randomly distributed or if there is a spatial pattern. They can identify spatial structures in the pattern of cancer incidence but do not determine where the clusters are. Local cluster statistics, on the other hand, can quantify spatial autocorrelation and clustering, but only in limited areas. These methods may find restricted areas characterized as high-high (HH), high-low (HL), low-low (LL) or low-high (LH) risk of incidence within a region. HH and LL are defined as target areas surrounded by areas with similar incidence rates, while for HL and LH, the target areas are surrounded by areas with dissimilar cancer incidence rates. In other words, HH and LL indicate clusters, while HL and LH point to outliers (25). This study aimed to identify the spatial patterns of cancer of the breast and the prostate and to investigate the potential clustering in gender-specific patterns of these cancers in southern Iran between 2014-2017. Method Study Area and Time : This study was conducted in the province of Kerman, located in southern Iran (Figure 1). The first administrative level of Iran subdivisions is the province, each of which is further divided into counties that are in turn divided into districts. Our study area contained the 22 counties and 58 districts of Kerman Province, which covers an area of 183,285 km² and has, according to the National Census of 2015, a population of 3,164,718 people (26). The study covered the time span of March 2014-March 2017 Data Sources : Data were obtained from two different sources with three different spatial scales (individual, county and district). The individual patient data (supplementary files 1-2) were obtained through the population-based cancer registry of Kerman. They were geocoded and aggregated to both county and district. The digital maps (county and district) were obtained through the mapping organisation of the country. We used a crude incidence per 100,000 people and the age-standardised rate (ASR) per 100,000 people for the descriptive statistics. Inclusion and Exclusion Criteria: We included all residents of Kerman diagnosed with either cancer of the breast or the prostate. Individuals who had come to the province for cancer treatment but lived outside of the province were excluded. Spatial Analyses : For the thematic maps, we used the natural-break classification with five classes. This approach is a data-clustering method designed to determine the best arrangement of values into different classes. This is done by seeking to minimise each class’s average deviation from the class mean, while maximising each class’s deviation from the means of the other groups. In other words, the method seeks to reduce the variance within classes and maximise the variance between them (27). For spatial visualisation, the crude incidence per 100,000 people and the ASR per 100,000 people were used. Spatial Cluster Analysis: Incidence rates of the two target cancers were calculated using total population and number of cases in each county and district of the province. The Local Moran's I statistic (28) was performed to quantify spatial autocorrelation of cancers frequency at county and district level. This test calculates a z -score and p -value to determine whether the apparent similarity (spatial clustering of either high or low values) or dissimilarity (presence of spatial outliers) is more pronounced than one would expect in a random distribution. The null hypothesis states that the cancers are randomly distributed across the study area. A high positive z-score for a feature indicates that the surrounding features have similar values (either high values or low values). However, a low negative z-score for a feature indicates a statistically significant spatial data outlier (28). We used a 95% Confidence Level (CL), and all clusters and outliers found in this study were significant at this CL. We used ArcGIS, v. 10.5 (ESRI, Redlands, CA, USA) and GeoDa (https://spatial.uchicago.edu/geoda) for spatial analyses and Microsoft Excel 2016 for the descriptive analyses. Figure 1: Map of Kerman counties and districts including the distribution of cancer (prostate and breast) patients during 2014-2017 Results There were 1,350 breast cancer patients (including, 42 male cases) and 478 prostate cancer patients in the province of Kerman, Iran during the period March 2014-March 2017. Table 1 shows the crude incidence per 100,000 people and ASR per 100,000 people of these cancers. The ASR of both breast and prostate cancers increased by 29.93 to 32.27 and by 13.93 to 15.47 from 2014 to 2017, respectively. Table 1: Breast and prostate cancer incidence per 100,000 people during different time periods in the province of Kerman, Iran Period 2014-2015 2015- 2016 2016-2017 Cancer: Number Crude rate ASR* Number Crude rate ASR* Number Crude rate ASR* Female Breast 424 26.64 29.93 425 28.71 32.49 459 29.73 32.27 Male Breast 14 0.90 1.52 20 1.02 1.22 8 0.37 0.42 Prostate 151 9.82 13.93 128 8.42 11.29 199 12.36 15.47 *Age-standardised rate As shown in Figure 2, the number of women (after 25 years of age) who developed breast cancer increased rapidly. Furthermore, the highest incidence occurred in the 50-54 age group in the 2014-2015 period, in the 65-69 age group in the 2015-2016 period and in the 75-79 age group in the 2016-2017 period. Figure 2: Age distribution of breast cancer patients in the province of Kerman, Iran After 45 years of age, the number of men with diagnosed prostate cancer increased similarly to that of breast cancer for women after 25 years of age. In contrast, however, the ascent of this cancer in relation to seniority was considerable in all years from 2014 to 2017 (Figure 3). Figure 3: Age distribution of prostate cancer patients in the province of Kerman, Iran The descriptive maps of Figure 4 reveal that the breast cancer incidence was highest in the north-eastern part of the province from 2014 to 2017. However, as the cluster maps show, there were HH clusters of breast cancer in the north-western part of the province from 2014 to 2017; furthermore, there was a LL cluster in the South-East in 2014-2015 and in 2016-2017, but not in the time between these periods. All clusters and outliers were statistically significant ( p <0.05). Figure 4: Breast cancer incidence map at the county level in the province of Kerman, Iran The descriptive maps of Figure 5 reveal that the breast cancer incidence was highest in the North stretching towards the centre of the province. However, as the cluster maps show, there were HH clusters of breast cancer in the north-western part of the province from 2014 to 2015 and 2016 to 2017; furthermore, there were LL clusters in the north-eastern part of the province from 2014 to 2015 and from 2016 to 2017. All clusters and outliers in the figure were statistically significant (p <0.05). Figure 5: Breast cancer incidence map at the district level in the province of Kerman, Iran The descriptive maps of Figure 6 reveal that the prostate cancer incidence was highest in the North-East. However, as the cluster maps show, there were HH clusters of prostate cancer in the north-western part of the province from 2014 to 2016; furthermore, there were LL clusters of prostate cancer in the South-East and East of the province from 2014 to 2017. All clusters and outliers in the figure were statistically significant (p <0.05). Figure 6: Prostate cancer incidence map at the county level in the province of Kerman, Iran The descriptive maps of Figure 7 reveal that the prostate cancer incidence was highest in the North-East of the province from 2015 to 2016. However, there was a HH cluster of prostate cancer in the North-West from 2014 to 2015 and some HH clusters in the North-West stretching towards the centre from 2016 to 2017. All clusters and outliers in the figure were statistically significant (p <0.05). Figure 7: Prostate cancer incidence map at the district level in the province of Kerman, Iran The four categories shown in Figures 4-7 correspond to the four quadrants in the Moran scatter plots as shown in Figure 8. If nearby or neighbouring areas are more alike, this is understood as positive spatial autocorrelation. Negative autocorrelation describes patterns in which neighbouring areas are unlike. For example, the first scatter plot (which shows the county level breast cancer for 2014-2015) has a Moran’s value of 0.271 that should be interpreted as a spatial pattern with a cluster tendency (HH and LL). Note that the incidence values have been standardized and are given in standard deviational units (the mean is zero and the standard deviation is 1). Similarly, the spatial lag was computed for those standardized values. Figure 8: Moran’s scatter plots for breast and prostate cancers cluster maps Discussion The main aim of this study was to explore the spatio-temporal patterns of the incidence of breast and prostate cancer at a high-resolution geography scale. To the best of our knowledge, this is the first study to assess spatial variations in the incidence pattern of breast and prostate cancers in Iran. The study area in the South of Iran revealed a high incidence rate of both cancers in north-western Kerman, while it was low in the south-eastern part of the province. The number of people with breast or prostate cancer increased considerably after patients reached 25 and 45 years of age, respectively. Further investigations are needed to assess the drivers in the high-risk areas identified in north-western Kerman. They might be associated with environmental factors and lifestyles (12), poor access to cancer-specific services (29), hereditary reasons (10) and/or socio-economic inequalities (30, 31). Environmental risk factors such as air pollution (32-34) and presence of heavy metals (35, 36) could be linked to the geographic outcome disparities for both cancer forms. We found high-risk areas for the whole study period of breast and prostate cancers in the north-western part of Kerman, an area extending southeast of the Iranian volcano-plutonic copper belt (37) where arsenic contamination is one of the most significant environmental concerns (38). This is the location of the Sarcheshmeh copper industrial plant, the biggest copper mine of Iran, and it is likely that the neighbourhood is contaminated also by other heavy metals. Field studies report widely distributed travertine rocks north of the Sarcheshmeh copper mine indicating the presence of a highly concentrated range of arsenic compounds (38), which could seep into the water system and contaminate the drinking water in nearby urban and rural communities (38, 39). Indeed, the arsenic concentration in the water in these areas is higher than the limit recommended by the World Health Organisation (WHO) for drinking water (38, 40, 41). Arsenic has been categorised as a Group 1 carcinogen factor by the International Agency for Research on Cancer (IARC) (42) and various studies associate arsenic and breast cancer (43-46); its presence in the study area is thus a potential explanation for the increased incidence of breast cancer found. However, it should also be mentioned that other studies do not show any significant association between breast cancer and arsenic (47, 48). However, it is conceivable that he power of this association can change due to local and individual diversities (45). Previous studies indicate a significant association between arsenic-enriched water and prostate cancer incidence (46, 49, 50), while increased levels of copper has been linked with the initiation of prostate cancer (35). Copper smelting and toxic discharges have led to soil pollution, especially in the region of the smelting plant in Sarcheshmeh Copper Complex. Importantly, the most contaminated areas are located in the most common wind directions (51), and it is particularly disturbing that the polluted areas are also used as grazing land enabling toxic elements from this soil to enter the food chain. These elements include various heavy metals in addition to copper and arsenic, e.g., lead, molybdenum and cadmium (51). Therefore, soil, water and nutrition of Rafsanjan and the adjacent townships, located in the north-western part of the province are subject to these potential negative effects. Indeed, previous studies have found associations between heavy metals and both breast and prostate cancers (52-54). The current study strongly recommends examining the hypothesis that exposure to heavy metals, especially arsenic and copper, may be associated with high incidence of gender-specific cancers. In fact, the high incidence of both breast and prostate cancers in north-western Kerman may be associated with these contaminants and this need to be investigated in future studies Air pollution, such as that due to particulate matter, has been shown to be associated with breast cancer (33, 34). Further studies are suggested to confirm the effects of airborne pollution on the risk of breast cancer, especially particulate matter. Fazzo et al. (2016) used a spatial approach to estimate the industrial air pollution impact on 17 selected neoplasms in the territory around the industrial Sicilian area of Priolo, Italy. This area has been defined as a contaminated site of national priority for remediation because of diffuse environmental contamination caused by large industrial settlements, and their study found a higher incidence of breast cancer in the contaminated area compared to the rest of the province (55). Previous studies highlight that poor access to health care services, such as increased incidence of cancer (29, 56), lead to poor health outcomes (57, 58). The high incidence of gender-specific cancers in some regions of the study area may be due to their considerable distance from the provincial capital with limited cancer screening programmes. On the other hand, parts of the study area in the South had the lowest incidence of both cancers investigated here although those affected were located even further away from the provincial capital. However, proximity to health care services does not directly translate into access because of potential factors such as poor socio-economic status and low level of education that also are associated with poor access (57). GIS enable researchers to assess the revealed access to cancer services through combing spatial and non-spatial factors (58-60) and the results suggest measuring access to cancer prevention programmes should be the first step when examining this hypothesis. Previous studies have highlighted the impact of the socio-economic status on the differences in the incidence of cancers of the breast and prostate (61-63). Assessing the impact of socio-economic status on the geographic disparities of the gender-specific cancers incidence in the study area can be done by analysing the overall spatial structure or identifying high-risk areas. This also warrants further studies. Hereditary cancer syndromes, a type of inherited disorder in which there is a higher-than-normal risk of certain types of cancer, are caused by mutations in certain genes passed from parents to children (64-68). Certain such family-related cancers are well-known, e.g., hereditary breast cancer (67) and Lynch syndrome, which is a hereditary non-polyposis colorectal cancer (65). Hereditary cancer screening programmes (69-71) have made it possible to detect many of the approximately 5–10% of breast cancers caused by a genetic predisposition (72, 73) thus making it possible to prevent them before they occur. There are also studies assessing the risk of prostate cancer associated with hereditary cancer syndromes. This highlights the risk of prostate cancer in members of families associated with early-onset diseases of various kinds (68). We strongly recommend researchers and policymakers to perform hereditary cancer screening and genetic testing in areas of the province with a high incidence rate of cancer of either breast or prostate. Spatio-temporal cluster analysis plays a significant role in visualising and quantifying geographical variation in patterns of disease incidence. Global Moran’s I and Getis-Ord General G statistic are both global cluster methods which can be used to investigate the level of spatial autocorrelation of disease patterns, while Local Moran’s I and Getis-Ord Gi* are indicate the location of the clusters. Although Getis-Ord Gi* statistic is used for identifying hotspots and the opposite, Local Moran's I is also effective for assessing statistically significant spatial outliers (74) and has therefore been predominantly applied (28, 75) and successfully assessed the hotspots (76, 77). Those using these methods for analysis of the spatial pattern of incident data should consider aggregating the incident data into polygons. The main question here is the geographical scale that should be used for aggregation because it could affect the results. In this study, we conducted the analyses both at the county and the district level, which are geographical scales providing practically useful information. We recommend other researchers performing cohort studies examining the hypotheses proposed here. Limitations and future course of the study: We included all patients with breast and prostate cancer in the province of Kerman during 2014-2017. However, we did not have the migration data and used the current address of patients at the time of cancer diagnosis as the patients’ residence. However, some patients might have lived in other regions in the years that might have affected their health. Conclusions We identified a great deal of spatial variations with significant clusters in the patterns of cancer of the breast and the prostate. This suggests that policymakers need to develop prevention strategies tailored to areas where the risk of these conditions are greater than elsewhere. Further, there is a need to conduct further research to test the causal relationship between environmental risk factors and cancer incidence. Abbreviations GIS: Geographical information systems; HH: High-High; LL: Low-Low; HL: High-Low; LH: Low-High; WHO: World Health Organization; IARC: International Agency for Research on Cancer; Declarations Ethics approval and consent to participate: This study has been approved by Ethical Committee of Kerman University of Medical Sciences (number= IR.KMU.REC.1397.290). For retrospective study, the need for consent to participate was deemed unnecessary according to Ethical Committee of Kerman University of Medical Scicnes. Consent for publication: Not applicable Availability of data and materials: The cancers data have been uploaded as supplementary files. However, due to protect the patients’ data, the latitude/longitude of patients’ location has been removed. Competing interests: The authors declare that they have no competing interests. Funding: This study received funding from Kerman University of Medical Sciences (number= 97000230). The funder provided the cost of geocoding and cleaning the data. Authors’ contributions: M.M and L.A provided the data and funding. B.K and N.F conducted spatial analyses. H.R.M and A.B and F.K geocoded the data. A.D drafted the introduction part of the manuscript. V.Z calculated the age-specific incidence rates and cleaned the data. R.B and N.B and S.E revised the text. B.H drafted the discussion part of the manuscript. B.K drafted the method and result sections of the manuscript, designed the study and reviewed the literature and was the research leader. The author(s) read and approved the final manuscript. Acknowledgements: We would like to thank Kerman University of Medical Sciences for funding this study. Authors’ information: B.K is an assistant professor at Mashhad University of Medical Sciences. He has been working on health geographical information systems and different aspects of geo-spatial data sciences. 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Prevalence of Mismatch Repair-Deficient Colorectal Adenoma/Polyp in Early-Onset, Advanced Cases: a Cross-Sectional Study Based on Iranian Hereditary Colorectal Cancer Registry. Journal of gastrointestinal cancer. 2020. Ozanne EM, Loberg A, Hughes S, Lawrence C, Drohan B, Semine A, et al. Identification and management of women at high risk for hereditary breast/ovarian cancer syndrome. The breast journal. 2009;15(2):155-62. Beebe-Dimmer JL, Kapron AL, Fraser AM, Smith KR, Cooney KA. Risk of Prostate Cancer Associated With Familial and Hereditary Cancer Syndromes. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2020;38(16):1807-13. Thompson DJ, Genovese G, Halvardson J, Ulirsch JC, Wright DJ, Terao C, et al. Genetic predisposition to mosaic Y chromosome loss in blood. Nature. 2019;575(7784):652-7. Miki Y, Swensen J, Shattuck-Eidens D, Futreal PA, Harshman K, Tavtigian S, et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science (New York, NY). 1994;266(5182):66-71. Wooster R, Bignell G, Lancaster J, Swift S, Seal S, Mangion J, et al. Identification of the breast cancer susceptibility gene BRCA2. Nature. 1995;378(6559):789-92. Pal T, Permuth-Wey J, Betts JA, Krischer JP, Fiorica J, Arango H, et al. BRCA1 and BRCA2 mutations account for a large proportion of ovarian carcinoma cases. Cancer. 2005;104(12):2807-16. Claus EB, Schildkraut JM, Thompson WD, Risch NJ. The genetic attributable risk of breast and ovarian cancer. Cancer. 1996;77(11):2318-24. Goovaerts P, Jacquez GM. Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York. International Journal of Health Geographics. 2004;3(1):14. Zhang C, Luo L, Xu W, Ledwith V. Use of local Moran's I and GIS to identify pollution hotspots of Pb in urban soils of Galway, Ireland. Science of the total environment. 2008;398(1-3):212-21. Li K, Lin G-Z, Li Y, Dong H, Xu H, Song S-F, et al. Spatio-temporal analysis of the incidence of colorectal cancer in Guangzhou, 2010–2014. Chinese journal of cancer. 2017;36(1):60. Goovaerts P, Jacquez GM. Detection of temporal changes in the spatial distribution of cancer rates using local Moran’s I and geostatistically simulated spatial neutral models. Journal of Geographical Systems. 2005;7(1):137-59. Supplementary Files BreastData.xlsx BreastData.xlsx ProstateData.xlsx ProstateData.xlsx Cite Share Download PDF Status: Published Journal Publication published 30 Nov, 2020 Read the published version in BMC Cancer → Version 4 posted Submission checks completed at journal 21 Nov, 2020 Editorial decision: Accept 19 Nov, 2020 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.","description":"","filename":"Fig6.JPG","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/da124ddd18158b4d605ece90.JPG"},{"id":3983732,"identity":"ff6fe226-c1c5-4a31-aa0f-d11ac8327eb5","added_by":"auto","created_at":"2020-12-03 14:18:41","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":109340,"visible":true,"origin":"","legend":"Prostate cancer incidence map at the district level in the province of Kerman, Iran. The figure was created by authors. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.","description":"","filename":"Fig7.JPG","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/83857de390f58103df468d68.JPG"},{"id":3983712,"identity":"aa09c3c1-6ec0-4680-b4d5-5dc0c2151ef7","added_by":"auto","created_at":"2020-12-03 14:18:09","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":109340,"visible":true,"origin":"","legend":"Prostate cancer incidence map at the district level in the province of Kerman, Iran. The figure was created by authors. Note: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.","description":"","filename":"Fig7.JPG","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/5b757eb77dee667976ad87ba.JPG"},{"id":3983733,"identity":"125a1ad8-caeb-4dc8-8698-8c64932e551e","added_by":"auto","created_at":"2020-12-03 14:18:41","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":304550,"visible":true,"origin":"","legend":"Moran’s scatter plots for breast and prostate cancers cluster maps.","description":"","filename":"Fig8final.jpg","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/bdfad50b69acb98a7b3abf1c.jpg"},{"id":3983713,"identity":"68dd7863-3fc4-4e46-b3e9-3f09a688783d","added_by":"auto","created_at":"2020-12-03 14:18:09","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":304550,"visible":true,"origin":"","legend":"Moran’s scatter plots for breast and prostate cancers cluster maps.","description":"","filename":"Fig8final.jpg","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/6775d48d3d415999917114e8.jpg"},{"id":13621443,"identity":"21c9f07f-b8aa-43b6-9f53-2bef45f4b8ae","added_by":"auto","created_at":"2021-09-17 07:10:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1595870,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/1d422613-e0ef-4721-8e5b-11881b0b0cf0.pdf"},{"id":3983724,"identity":"bc013295-98f7-4cac-a304-d6c6f26f366b","added_by":"auto","created_at":"2020-12-03 14:18:39","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":60471,"visible":true,"origin":"","legend":"","description":"","filename":"BreastData.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/3fdbc2a2de5719dfd4394293.xlsx"},{"id":3983704,"identity":"6b83a218-276b-4a9d-9ad4-00939f8075e6","added_by":"auto","created_at":"2020-12-03 14:18:08","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":60471,"visible":true,"origin":"","legend":"","description":"","filename":"BreastData.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/40b07bc9e2980d7517f2da35.xlsx"},{"id":3983726,"identity":"de50e137-b249-4989-8c12-e66ff3901672","added_by":"auto","created_at":"2020-12-03 14:18:39","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":27281,"visible":true,"origin":"","legend":"","description":"","filename":"ProstateData.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/8497b0c2ae82908aaa69891b.xlsx"},{"id":3983706,"identity":"ed2fe6f9-43f2-48ac-919d-d755352400d8","added_by":"auto","created_at":"2020-12-03 14:18:08","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":27281,"visible":true,"origin":"","legend":"","description":"","filename":"ProstateData.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-39825/v4/08e9f0b0889b42bde471599e.xlsx"}],"financialInterests":"","formattedTitle":"Spatio-temporal mapping of breast and prostate cancers in South Iran from 2014-2017","fulltext":[{"header":"Background","content":"\u003cp\u003eCancers are the second leading cause of death worldwide (1), which can partly be explained by the fact that the world\u0026rsquo;s population is ageing (2). Furthermore, human exposure to multiple risk factors has increased the cancer burden worldwide (3). Despite advances in timely diagnosis and medical treatment of neoplasms in recent years, malignancies in middle to low-income countries are expected to almost double by 2030 compared to high-income nations (4). If cancer is diagnosed promptly, cures can sometimes be found and life prolonged leading to considerably lower disease burdens (5, 6). However, health systems, particularly in developing countries, are not capable of screening all people to identify patients in the early stages of the disease. Identifying high-risk geographical areas could help decreasing the cost of screening, finding the people at risk and implementing more efficient diagnostic strategies (7). Investigating high-risk areas should also provide valuable knowledge to scientists about the aetiology of some malignancies (3).\u003c/p\u003e\n\u003cp\u003eCancer of the breast and the prostate are the two most common, gender-specific malignancies worldwide (8). Furthermore, these neoplasms cause high numbers of disability-adjusted life years (DALYs) (9). Risk factors for these two diseases are diverse and interrelated, as they include genetic (10), social-economic (11) as well as lifestyle and environmental factors (12). Further, there are interactions between these risk factors, particularly with those involving the environment (13, 14), whose spatial variation may lead to heterogeneity in the pattern of cancers in a given geographic catchment area. Studies by Wang et al. (15, 16) found a significant spatial variation of prostate cancer incidence and prostate cancer-specific mortality in Pennsylvania, USA. They evaluated potential effects of individual and county-level risk factors and found that spatial variations in prostate cancer-specific mortality rates existed in Pennsylvania with a particularly high risk in the Pen State catchment area. County-level health and environmental factors might contribute to spatial heterogeneity in prostate cancer-specific mortality as shown by \u003ca href=\"https://www.researchgate.net/profile/Meysam_Olfatifar?_sg%5B0%5D=LRnmisc1O29stPbVV36dFindOpOJAfXFb0YTjAl4QvEIScwBXWC8Y_AvmUKGU_YHLEUF60U.qed4GSoopBeF01s8PsGyzTd3ZJYrKAzxZAcZUkFQ8pgY6t4LEt3v_vJAwqeCyHBNQIPQSMkSO7BE1JN7fbouZA\u0026amp;_sg%5B1%5D=CONkc8LgpSm0j7FMzsPSkJRZxNKgifg2fXdbk_Jwlpb7KnhPQtpugxHDfSYWm8pguCBGfTo.6Blz2HkhNmjbVfYPvx4z0wC4jHzJcUU0R_loH6sThJJlUo2oKCf6MdsyBkXs_DgInW6F8CtTOvCn3wKoFhy5Pw\"\u003eOlfatifar\u003c/a\u003e et al. (17), who examined spatial clustering of breast cancer at the provincial level in Iran between 2004 and 2010. Their results highlight that the breast tumour incidence varied across the provinces (17). At the same time, Rohani-Rasaf et al. (18) detected some high-risk regions in Tehran, the capital of Iran, both for cancers of the breast and the prostate. Most studies in Iran have applied spatial analyses at a very coarse level (province scale) and the results are therefore not as useful as a finer scale quite naturally.\u003c/p\u003e\n\u003cp\u003eGeographical information systems (GIS) constitute a set of useful tools for the identification of high-risk areas of cancer occurrence as well as investigation of the environmental effects on cancer incidence (19-21). GIS approaches combine spatial and non-spatial data producing geodatabases that make it possible to perform spatial analyses using this data structure (22, 23). For example, spatial autocorrelation is a method of exploratory data analysis which allows detecting spatial data dependence (24). There are two kinds of spatial autocorrelation methods: global and local statistics. Global methods are more sensitive to departures from the null hypothesis, which examine whether data, here patients, are randomly distributed or if there is a spatial pattern. They can identify spatial structures in the pattern of cancer incidence but do not determine where the clusters are. Local cluster statistics, on the other hand, can quantify spatial autocorrelation and clustering, but only in limited areas. These methods may find restricted areas characterized as high-high (HH), high-low (HL), low-low (LL) or low-high (LH) risk of incidence within a region. HH and LL are defined as target areas surrounded by areas with similar incidence rates, while for HL and LH, the target areas are surrounded by areas with dissimilar cancer incidence rates. In other words, HH and LL indicate clusters, while HL and LH point to outliers (25). This study aimed to identify the spatial patterns of cancer of the breast and the prostate and to investigate the potential clustering in gender-specific patterns of these cancers in southern Iran between 2014-2017.\u003c/p\u003e"},{"header":"Method","content":"\u003ch2\u003e\u003cem\u003eStudy Area and Time\u003c/em\u003e:\u003c/h2\u003e\n\u003cp\u003eThis study was conducted in the province of Kerman, located in southern Iran (Figure 1). The first administrative level of Iran subdivisions is the province, each of which is further divided into counties that are in turn divided into districts. Our study area contained the 22 counties and 58 districts of Kerman Province, which covers an area of 183,285 km\u0026sup2; and has, according to the National Census of 2015, a population of 3,164,718\u0026nbsp;people (26). The study covered the time span of March 2014-March 2017\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eData Sources\u003c/em\u003e:\u003c/h2\u003e\n\u003cp\u003eData were obtained from two different sources with three different spatial scales (individual, county and district). The individual patient data (supplementary files 1-2) were obtained through the population-based cancer registry of Kerman. They were geocoded and aggregated to both county and district. The digital maps (county and district) were obtained through the mapping organisation of the country.\u003c/p\u003e\n\u003cp\u003eWe used a crude incidence per 100,000 people and the age-standardised rate (ASR) per 100,000 people for the descriptive statistics.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eInclusion and Exclusion Criteria:\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eWe included all residents of Kerman diagnosed with either cancer of the breast or the prostate. Individuals who had come to the province for cancer treatment but lived outside of the province were excluded.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eSpatial Analyses\u003c/em\u003e:\u003c/h2\u003e\n\u003cp\u003eFor the thematic maps, we used the natural-break classification with five classes. This approach is a\u0026nbsp;\u003ca href=\"https://en.wikipedia.org/wiki/Data_clustering\"\u003edata-clustering\u003c/a\u003e\u0026nbsp;method designed to determine the best arrangement of values into different classes. This is done by seeking to minimise each class\u0026rsquo;s average deviation from the class mean, while maximising each class\u0026rsquo;s deviation from the means of the other groups. In other words, the method seeks to reduce the\u0026nbsp;\u003ca href=\"https://en.wikipedia.org/wiki/Variance\"\u003evariance\u003c/a\u003e\u0026nbsp;within classes and maximise the variance between them (27). For spatial visualisation, the crude incidence per 100,000 people and the ASR per 100,000 people were used.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eSpatial Cluster Analysis:\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eIncidence rates of the two target cancers were calculated using total population and number of cases in each county and district of the province. The Local Moran's \u003cem\u003eI\u003c/em\u003e statistic (28) was performed to quantify spatial autocorrelation of cancers frequency at county and district level. This test calculates a \u003cem\u003ez\u003c/em\u003e-score and \u003cem\u003ep\u003c/em\u003e-value to determine whether the apparent similarity (spatial clustering of either high or low values) or dissimilarity (presence of spatial outliers) is more pronounced than one would expect in a random distribution. The null hypothesis states that the cancers are randomly distributed across the study area. A high positive z-score for a feature indicates that the surrounding features have similar values (either high values or low values). However, a low negative z-score for a feature indicates a statistically significant spatial data outlier (28). We used a 95% Confidence Level (CL), and all clusters and outliers found in this study were significant at this CL.\u003c/p\u003e\n\u003cp\u003eWe used ArcGIS, v. 10.5 (ESRI, Redlands, CA, USA) and GeoDa (https://spatial.uchicago.edu/geoda) for spatial analyses and Microsoft Excel 2016 for the descriptive analyses.\u003c/p\u003e\n\u003cp\u003eFigure 1: Map of Kerman counties and districts including the distribution of cancer (prostate and breast) patients during 2014-2017\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThere were 1,350 breast cancer patients (including, 42 male cases) and 478 prostate cancer patients in the province of Kerman, Iran during the period March 2014-March 2017. Table 1 shows the crude incidence per 100,000 people and ASR per 100,000 people of these cancers. The ASR of both breast and prostate cancers increased by 29.93 to 32.27 and by 13.93 to 15.47 from 2014 to 2017, respectively.\u003c/p\u003e\n\u003cp\u003eTable 1: Breast and prostate cancer incidence per 100,000 people during different time periods in the province of Kerman, Iran\u003c/p\u003e\n\u003ctable border=\"1\" width=\"654\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e\u003cstrong\u003ePeriod\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"193\"\u003e\n\u003cp\u003e\u003cstrong\u003e2014-2015\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"188\"\u003e\n\u003cp\u003e\u003cstrong\u003e2015- 2016\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"185\"\u003e\n\u003cp\u003e\u003cstrong\u003e2016-2017\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCancer: \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eNumber\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003eCrude rate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003eASR*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eNumber\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003eCrude rate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003eASR*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003eNumber\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003eCrude rate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003eASR*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003eFemale Breast\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e424\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e26.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e29.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e425\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e28.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e32.49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e459\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e29.73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e32.27\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003eMale Breast\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e0.90\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e1.52\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e1.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.42\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp; Prostate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e151\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u0026nbsp;9.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e13.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e128\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e8.42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e11.29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e199\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e12.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e15.47\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Age-standardised rate\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs shown in Figure 2, the number of women (after 25 years of age) who developed breast cancer increased rapidly. Furthermore, the highest incidence occurred in the 50-54 age group in the 2014-2015 period, in the 65-69 age group in the 2015-2016 period and in the 75-79 age group in the 2016-2017 period.\u003c/p\u003e\n\u003cp\u003eFigure 2: Age distribution of breast cancer patients in the province of Kerman, Iran\u003c/p\u003e\n\u003cp\u003eAfter 45 years of age, the number of men with diagnosed prostate cancer increased similarly to that of breast cancer for women after 25 years of age. In contrast, however, the ascent of this cancer in relation to seniority was considerable in all years from 2014 to 2017 (Figure 3).\u003c/p\u003e\n\u003cp\u003eFigure 3: Age distribution of prostate cancer patients in the province of Kerman, Iran\u003c/p\u003e\n\u003cp\u003eThe descriptive maps of Figure 4 reveal that the breast cancer incidence was highest in the north-eastern part of the province from 2014 to 2017. However, as the cluster maps show, there were HH clusters of breast cancer in the north-western part of the province from 2014 to 2017; furthermore, there was a LL cluster in the South-East in 2014-2015 and in 2016-2017, but not in the time between these periods. All clusters and outliers were statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eFigure 4: Breast cancer incidence map at the county level in the province of Kerman, Iran\u003c/p\u003e\n\u003cp\u003eThe descriptive maps of Figure 5 reveal that the breast cancer incidence was highest in the North stretching towards the centre of the province. However, as the cluster maps show, there were HH clusters of breast cancer in the north-western part of the province from 2014 to 2015 and 2016 to 2017; furthermore, there were LL clusters in the north-eastern part of the province from 2014 to 2015 and from 2016 to 2017. All clusters and outliers in the figure were statistically significant (p \u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eFigure 5: Breast cancer incidence map at the district level in the province of Kerman, Iran\u003c/p\u003e\n\u003cp\u003eThe descriptive maps of Figure 6 reveal that the prostate cancer incidence was highest in the North-East. However, as the cluster maps show, there were HH clusters of prostate cancer in the north-western part of the province from 2014 to 2016; furthermore, there were LL clusters of prostate cancer in the South-East and East of the province from 2014 to 2017. All clusters and outliers in the figure were statistically significant (p \u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eFigure 6: Prostate cancer incidence map at the county level in the province of Kerman, Iran\u003c/p\u003e\n\u003cp\u003eThe descriptive maps of Figure 7 reveal that the prostate cancer incidence was highest in the North-East of the province from 2015 to 2016. However, there was a HH cluster of prostate cancer in the North-West from 2014 to 2015 and some HH clusters in the North-West stretching towards the centre from 2016 to 2017. All clusters and outliers in the figure were statistically significant (p \u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eFigure 7: Prostate cancer incidence map at the district level in the province of Kerman, Iran\u003c/p\u003e\n\u003cp\u003eThe four categories shown in Figures 4-7 correspond to the four quadrants in the Moran scatter plots as shown in Figure\u0026nbsp;8.\u0026nbsp;If nearby or neighbouring areas are more alike, this is understood as positive spatial autocorrelation. Negative autocorrelation describes patterns in which neighbouring areas are unlike. For example, the first scatter plot (which shows the county level breast cancer for 2014-2015) has a Moran\u0026rsquo;s value of 0.271 that should be interpreted as a spatial pattern with a cluster tendency (HH and LL). Note that the incidence values have been standardized and are given in standard deviational units (the mean is zero and the standard deviation is 1). Similarly, the spatial lag was computed for those standardized values.\u003c/p\u003e\n\u003cp\u003eFigure 8: Moran\u0026rsquo;s scatter plots for breast and prostate cancers cluster maps\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe main aim of this study was to explore the spatio-temporal patterns of the incidence of breast and prostate cancer at a high-resolution geography scale. To the best of our knowledge, this is the first study to assess spatial variations in the incidence pattern of breast and prostate cancers in Iran. The study area in the South of Iran revealed a high incidence rate of both cancers in north-western Kerman, while it was low in the south-eastern part of the province. The number of people with breast or prostate cancer increased considerably after patients reached 25 and 45 years of age, respectively. Further investigations are needed to assess the drivers in the high-risk areas identified in north-western Kerman. They might be associated with environmental factors and lifestyles (12), poor access to cancer-specific services (29), hereditary reasons (10) and/or socio-economic inequalities (30, 31).\u003c/p\u003e\n\u003cp\u003eEnvironmental risk factors such as air pollution (32-34) and presence of heavy metals (35, 36) could be linked to the geographic outcome disparities for both cancer forms. We found high-risk areas for the whole study period of breast and prostate cancers in the north-western part of Kerman, an area extending southeast of the Iranian\u0026nbsp;volcano-plutonic copper belt (37) where arsenic contamination is one of the most significant environmental concerns (38). This is the location of the Sarcheshmeh copper industrial plant, the biggest copper mine of Iran, and it is likely that the neighbourhood is contaminated also by other heavy metals. Field studies report widely distributed travertine rocks north of the Sarcheshmeh copper mine indicating the presence of a highly concentrated range of arsenic compounds (38), which could seep into the water system and contaminate the drinking water in nearby urban and rural communities (38, 39). Indeed, the arsenic concentration in the water in these areas is higher than the limit recommended by the World Health Organisation (WHO) for drinking water (38, 40, 41). Arsenic has been categorised as a Group 1 carcinogen factor by the International Agency for Research on Cancer (IARC) (42) and various studies associate arsenic and breast cancer (43-46); its presence in the study area is thus a potential explanation for the increased incidence of breast cancer found. However, it should also be mentioned that other studies do not show any significant association between breast cancer and arsenic (47, 48). However, it is conceivable that he power of this association can change due to local and individual diversities (45).\u003c/p\u003e\n\u003cp\u003ePrevious studies indicate a significant association between arsenic-enriched water and prostate cancer incidence (46, 49, 50), while increased levels of copper has been linked with the initiation of prostate cancer (35). Copper smelting and toxic discharges have led to soil pollution, especially in the region of the smelting plant in Sarcheshmeh Copper Complex. Importantly, the most contaminated areas are located in the most common wind directions (51), and it is particularly disturbing that the polluted areas are also used as grazing land enabling toxic elements from this soil to enter the food chain. These elements include various heavy metals in addition to copper and arsenic, e.g., lead, molybdenum and cadmium (51). Therefore, soil, water and nutrition of Rafsanjan and the adjacent townships, located in the north-western part of the province are subject to these potential negative effects. Indeed, previous studies have found associations between heavy metals and both breast and prostate cancers (52-54). The current study strongly recommends examining the hypothesis that exposure to heavy metals, especially arsenic and copper, may be associated with high incidence of gender-specific cancers. In fact, the high incidence of both breast and prostate cancers in north-western Kerman may be associated with these contaminants and this need to be investigated in future studies\u003c/p\u003e\n\u003cp\u003eAir pollution, such as that due to particulate matter, has been shown to be associated with breast cancer (33, 34). Further studies are suggested to confirm the effects of airborne pollution on the risk of breast cancer, especially particulate matter. Fazzo et al. (2016) used a spatial approach to estimate the industrial air pollution impact on 17 selected neoplasms in the territory around the industrial Sicilian area of Priolo, Italy. This area has been defined as a contaminated site of national priority for remediation because of diffuse environmental contamination caused by large industrial settlements, and their study found a higher incidence of breast cancer in the contaminated area compared to the rest of the province (55).\u003c/p\u003e\n\u003cp\u003ePrevious studies highlight that poor access to health care services, such as increased incidence of cancer (29, 56), lead to poor health outcomes (57, 58). The high incidence of gender-specific cancers in some regions of the study area may be due to their considerable distance from the provincial capital with limited cancer screening programmes. On the other hand, parts of the study area in the South had the lowest incidence of both cancers investigated here although those affected were located even further away from the provincial capital. However, proximity to health care services does not directly translate into access because of potential factors such as poor socio-economic status and low level of education that also are associated with poor access (57). GIS enable researchers to assess the revealed access to cancer services through combing spatial and non-spatial factors (58-60) and the results suggest measuring access to cancer prevention programmes should be the first step when examining this hypothesis. Previous studies have highlighted the impact of the socio-economic status on the differences in the incidence of cancers of the breast and prostate (61-63). Assessing the impact of socio-economic status on the geographic disparities of the gender-specific cancers incidence in the study area can be done by analysing the overall spatial structure or identifying high-risk areas. This also warrants further studies.\u003c/p\u003e\n\u003cp\u003eHereditary cancer syndromes, a type of inherited disorder in which there is a higher-than-normal risk of certain types of cancer, are caused by mutations in certain genes passed from parents to children (64-68). Certain such family-related cancers are well-known, e.g., hereditary breast cancer (67) and Lynch syndrome, which is a hereditary non-polyposis colorectal cancer (65). Hereditary cancer screening programmes (69-71) have made it possible to detect many of the approximately 5\u0026ndash;10% of breast cancers caused by a genetic predisposition (72, 73) thus making it possible to prevent them before they occur. There are also studies assessing the risk of prostate cancer associated with hereditary cancer syndromes. This highlights the risk of prostate cancer in members of families associated with early-onset diseases of various kinds (68). We strongly recommend researchers and policymakers to perform hereditary cancer screening and genetic testing in areas of the province with a high incidence rate of cancer of either breast or prostate.\u003c/p\u003e\n\u003cp\u003eSpatio-temporal cluster analysis plays a significant role in visualising and quantifying geographical variation in patterns of disease incidence. Global Moran\u0026rsquo;s \u003cem\u003eI\u003c/em\u003e and Getis-Ord General G statistic are both global cluster methods which can be used to investigate the level of spatial autocorrelation of disease patterns, while Local Moran\u0026rsquo;s \u003cem\u003eI\u003c/em\u003e and Getis-Ord Gi* are indicate the location of the clusters. Although Getis-Ord Gi* statistic is used for identifying hotspots and the opposite, Local Moran's \u003cem\u003eI\u003c/em\u003e is also effective for assessing statistically significant spatial outliers (74) and has therefore been predominantly applied (28, 75) and successfully assessed the hotspots (76, 77). Those using these methods for analysis of the spatial pattern of incident data should consider \u003ca href=\"ms-its:c:\\program%20files%20(x86)\\arcgis\\desktop10.6\\help\\ArcInfoMain.chm::/spatial_statistics_toolbox.chm::/005p00000011000000.htm#GUID-AF3205B7-D9AE-4C14-AFE9-E672092200BE\"\u003eaggregating the incident data\u003c/a\u003e into polygons. The main question here is the geographical scale that should be used for aggregation because it could affect the results. In this study, we conducted the analyses both at the county and the district level, which are geographical scales providing practically useful information. We recommend other researchers performing cohort studies examining the hypotheses proposed here.\u003c/p\u003e\n\u003ch2\u003eLimitations and future course of the study:\u003c/h2\u003e\n\u003cp\u003eWe included all patients with breast and prostate cancer in the province of Kerman during 2014-2017. However, we did not have the migration data and used the current address of patients at the time of cancer diagnosis as the patients\u0026rsquo; residence. However, some patients might have lived in other regions in the years that might have affected their health.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe identified a great deal of spatial variations with significant clusters in the patterns of cancer of the breast and the prostate. This suggests that policymakers need to develop prevention strategies tailored to areas where the risk of these conditions are greater than elsewhere. Further, there is a need to conduct further research to test the causal relationship between environmental risk factors and cancer incidence.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eGIS: Geographical information systems; HH: High-High; LL: Low-Low; HL: High-Low; LH: Low-High; WHO: World Health Organization; IARC: International Agency for Research on Cancer;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate:\u003c/p\u003e\n\u003cp\u003eThis study has been approved by Ethical Committee of Kerman University of Medical Sciences (number= IR.KMU.REC.1397.290). For retrospective study, the need for consent to participate was deemed unnecessary according to Ethical Committee of Kerman University of Medical Scicnes.\u003c/p\u003e\n\u003cp\u003eConsent for publication:\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials:\u003c/p\u003e\n\u003cp\u003eThe cancers data have been uploaded as supplementary files. However, due to protect the patients\u0026rsquo; data, the latitude/longitude of patients\u0026rsquo; location has been removed.\u003c/p\u003e\n\u003cp\u003eCompeting interests:\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding:\u003c/p\u003e\n\u003cp\u003eThis study received funding from Kerman University of Medical Sciences (number= 97000230). The funder provided the cost of geocoding and cleaning the data.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions:\u003c/p\u003e\n\u003cp\u003eM.M and L.A provided the data and funding. B.K and N.F conducted spatial analyses. H.R.M and A.B and F.K geocoded the data. A.D drafted the introduction part of the manuscript. V.Z calculated the age-specific incidence rates and cleaned the data. R.B and N.B and S.E revised the text. B.H drafted the discussion part of the manuscript. B.K drafted the method and result sections of the manuscript, designed the study and reviewed the literature and was the research leader. The author(s) read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements:\u003c/p\u003e\n\u003cp\u003eWe would like to thank Kerman University of Medical Sciences for funding this study.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; information:\u003c/p\u003e\n\u003cp\u003eB.K is an assistant professor at Mashhad University of Medical Sciences. He has been working on health geographical information systems and different aspects of geo-spatial data sciences.\u003c/p\u003e\n\u003cp\u003eN.B is a Senior Research Fellow and spatial epidemiologist at the Australian National University (ANU) with a particular interest in geo-spatial analysis and modelling.\u003c/p\u003e\n\u003cp\u003eR.B is the editor-in-chief of the Geospatial Health Journal and has much experience in spatial epidemiology.\u003c/p\u003e\n\u003cp\u003eB.H is a faculty member at Neyshabur University of Medical Sciences and junior researcher at Mashhad University of Medical Sciences. 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Revealed access to haemodialysis facilities in northeastern Iran: Factors that matter in rural and urban areas. Geospat Health. 2017;12(2):584.\u003c/li\u003e\n\u003cli\u003eMohaghegh P, Yavari P, Akbari ME, Abadi A, Ahmadi F, Shormeij Z. Relationships between Family Levels of Socioeconomic Status and Distribution of Breast Cancer Risk Factors. Iran J Cancer Prev. 2015;8(1):53-9.\u003c/li\u003e\n\u003cli\u003eVicens GR, Zafra MS, Moreno-Crespi J, Ferrer BC, Marcos-Gragera R. Incidence variation of prostate and cervical cancer according to socioeconomic level in the Girona Health Region. BMC Public Health. 2014;14:1079.\u003c/li\u003e\n\u003cli\u003eShafique K, Oliphant R, Morrison DS. The impact of socio-economic circumstances on overall and grade-specific prostate cancer incidence: a population-based study. Br J Cancer. 2012;107(3):575-82.\u003c/li\u003e\n\u003cli\u003eGoshayeshi L, Ghaffarzadegan K, Khooei A, Esmaeilzadeh A, Rahmani Khorram M, Mosannen Mozaffari H, et al. Prevalence and clinicopathological characteristics of mismatch repair-deficient colorectal carcinoma in early onset cases as compared with late-onset cases: a retrospective cross-sectional study in Northeastern Iran. BMJ open. 2018;8(8):e023102.\u003c/li\u003e\n\u003cli\u003eGoshayeshi L, Khooiee A, Ghaffarzadegan K, Rahmani Khorram M, Bishehsari F, Hoseini B, et al. Screening for Lynch Syndrome in Cases with Colorectal Carcinoma from Mashhad. Archives of Iranian medicine. 2017;20(6):332-7.\u003c/li\u003e\n\u003cli\u003eKhorram MR, Goshayeshi L, Maghool F, Bergquist R, Ghaffarzadegan K, Eslami S, et al. Prevalence of Mismatch Repair-Deficient Colorectal Adenoma/Polyp in Early-Onset, Advanced Cases: a Cross-Sectional Study Based on Iranian Hereditary Colorectal Cancer Registry. Journal of gastrointestinal cancer. 2020.\u003c/li\u003e\n\u003cli\u003eOzanne EM, Loberg A, Hughes S, Lawrence C, Drohan B, Semine A, et al. Identification and management of women at high risk for hereditary breast/ovarian cancer syndrome. The breast journal. 2009;15(2):155-62.\u003c/li\u003e\n\u003cli\u003eBeebe-Dimmer JL, Kapron AL, Fraser AM, Smith KR, Cooney KA. Risk of Prostate Cancer Associated With Familial and Hereditary Cancer Syndromes. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2020;38(16):1807-13.\u003c/li\u003e\n\u003cli\u003eThompson DJ, Genovese G, Halvardson J, Ulirsch JC, Wright DJ, Terao C, et al. Genetic predisposition to mosaic Y chromosome loss in blood. Nature. 2019;575(7784):652-7.\u003c/li\u003e\n\u003cli\u003eMiki Y, Swensen J, Shattuck-Eidens D, Futreal PA, Harshman K, Tavtigian S, et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science (New York, NY). 1994;266(5182):66-71.\u003c/li\u003e\n\u003cli\u003eWooster R, Bignell G, Lancaster J, Swift S, Seal S, Mangion J, et al. Identification of the breast cancer susceptibility gene BRCA2. Nature. 1995;378(6559):789-92.\u003c/li\u003e\n\u003cli\u003ePal T, Permuth-Wey J, Betts JA, Krischer JP, Fiorica J, Arango H, et al. BRCA1 and BRCA2 mutations account for a large proportion of ovarian carcinoma cases. Cancer. 2005;104(12):2807-16.\u003c/li\u003e\n\u003cli\u003eClaus EB, Schildkraut JM, Thompson WD, Risch NJ. The genetic attributable risk of breast and ovarian cancer. Cancer. 1996;77(11):2318-24.\u003c/li\u003e\n\u003cli\u003eGoovaerts P, Jacquez GM. Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York. International Journal of Health Geographics. 2004;3(1):14.\u003c/li\u003e\n\u003cli\u003eZhang C, Luo L, Xu W, Ledwith V. Use of local Moran's I and GIS to identify pollution hotspots of Pb in urban soils of Galway, Ireland. Science of the total environment. 2008;398(1-3):212-21.\u003c/li\u003e\n\u003cli\u003eLi K, Lin G-Z, Li Y, Dong H, Xu H, Song S-F, et al. Spatio-temporal analysis of the incidence of colorectal cancer in Guangzhou, 2010\u0026ndash;2014. Chinese journal of cancer. 2017;36(1):60.\u003c/li\u003e\n\u003cli\u003eGoovaerts P, Jacquez GM. Detection of temporal changes in the spatial distribution of cancer rates using local Moran\u0026rsquo;s I and geostatistically simulated spatial neutral models. Journal of Geographical Systems. 2005;7(1):137-59.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Spatial Analyses, Cluster Analyses, Breast Cancer, Prostate Cancer, Spatio-temporal, Geographical Information Systems, Iran","lastPublishedDoi":"10.21203/rs.3.rs-39825/v4","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-39825/v4","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground:\u003c/p\u003e\u003cp\u003eThe most common gender-specific malignancies are cancers of the breast and the prostate. In developing countries, cancer screening of all at risk is impractical because of healthcare resource limitations. Thus, determining high-risk areas might be an important first screening step. This study explores incidence patterns of potential high-risk clusters of breast and prostate cancers in southern Iran.\u003c/p\u003e\u003cp\u003eMethods:\u003c/p\u003e\u003cp\u003eThis cross-sectional study was conducted in the province of Kerman, South Iran. Patient data were aggregated at the county and district levels calculating the incidence rate per 100,000 people both for cancers of the breast and the prostate. We used the natural-break classification with five classes to produce descriptive maps. A spatial clustering analysis (Anselin Local Moran’s \u003cem\u003eI\u003c/em\u003e) was used to identify potential clusters and outliers in the pattern of these cancers from 2014 to 2017.\u003c/p\u003e\u003cp\u003eResults:\u003c/p\u003e\u003cp\u003eThere were 1,350 breast cancer patients (including, 42 male cases) and 478 prostate cancer patients in the province of Kerman, Iran during the study period. After 45 years of age, the number of men with diagnosed prostate cancer increased similarly to that of breast cancer for women after 25 years of age. The age-standardised incidence rate of breast cancer for women showed an increase from 29.93 to 32.27 cases per 100,000 people and that of prostate cancer from 13.93 to 15.47 cases per 100,000 during 2014-2017. Cluster analysis at the county level identified high-high clusters of breast cancer in the north-western part of the province for all years studied, but the analysis at the district level showed high-high clusters for only two of the years. With regard to prostate cancer, cluster analysis at the county and district levels identified high-high clusters in this area of the province for two of the study years.\u003c/p\u003e\u003cp\u003eConclusions:\u003c/p\u003e\u003cp\u003eNorth-western Kerman had a significantly higher incidence rate of both breast and prostate cancer than the average, which should help in designing tailored screening and surveillance systems. Furthermore, this study generates new hypotheses regarding the potential relationship between increased incidence of cancers in certain geographical areas and environmental risk factors.\u003c/p\u003e","manuscriptTitle":"Spatio-temporal mapping of breast and prostate cancers in South Iran from 2014-2017","msid":"","msnumber":"","nonDraftVersions":[{"code":4,"date":"2020-12-03 14:18:06","doi":"10.21203/rs.3.rs-39825/v4","editorialEvents":[{"type":"communityComments","content":0},{"type":"checksComplete","content":"","date":"2020-11-21T12:52:29+00:00","index":"","fulltext":""},{"type":"decision","content":"Accept","date":"2020-11-20T00:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":3,"date":"2020-11-13 18:46:40","doi":"10.21203/rs.3.rs-39825/v3","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2020-11-13T00:00:00+00:00","index":2,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-11-13T00:00:00+00:00","index":2,"fulltext":"Recommendation: Reviewer's comments unavailable pending editorial decision\n"},{"type":"reviewersInvited","content":"","date":"2020-11-09T00:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-11-09T00:00:00+00:00","index":1,"fulltext":""},{"type":"editorAssigned","content":"","date":"2020-11-08T00:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-11-07T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-11-07T23:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":2,"date":"2020-09-18 18:53:59","doi":"10.21203/rs.3.rs-39825/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2020-11-04T00:00:00+00:00","index":8,"fulltext":"Recommendation: Reviewer's comments unavailable pending editorial decision\n"},{"type":"editorInvitedReview","content":"","date":"2020-11-02T00:00:00+00:00","index":6,"fulltext":"Recommendation: Reviewer's comments unavailable pending editorial decision\n"},{"type":"editorInvitedReview","content":"","date":"2020-10-23T12:00:00+00:00","index":7,"fulltext":"Recommendation: Reviewer's comments unavailable pending editorial decision\n"},{"type":"reviewerAgreed","content":"","date":"2020-10-23T12:00:00+00:00","index":8,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-10-19T12:00:00+00:00","index":5,"fulltext":"Recommendation: Reviewer's comments unavailable pending editorial decision\n"},{"type":"reviewerAgreed","content":"","date":"2020-10-18T12:00:00+00:00","index":7,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-10-12T12:00:00+00:00","index":6,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-10-07T12:00:00+00:00","index":4,"fulltext":"Recommendation: Reviewer's comments unavailable pending editorial decision\n"},{"type":"reviewerAgreed","content":"","date":"2020-10-05T12:00:00+00:00","index":4,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-10-05T12:00:00+00:00","index":5,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-10-05T12:00:00+00:00","index":3,"fulltext":"Recommendation: Reviewer's comments unavailable pending editorial decision\n"},{"type":"reviewerAgreed","content":"","date":"2020-10-05T12:00:00+00:00","index":3,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-09-27T12:00:00+00:00","index":2,"fulltext":"Recommendation: Reviewer's comments unavailable pending editorial decision\n"},{"type":"reviewerAgreed","content":"","date":"2020-09-20T12:00:00+00:00","index":2,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-09-20T12:00:00+00:00","index":1,"fulltext":"Recommendation: Reviewer's comments unavailable pending editorial decision\n"},{"type":"reviewerAgreed","content":"","date":"2020-09-18T12:00:00+00:00","index":1,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-09-16T12:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2020-09-16T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-09-15T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-09-15T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2020-07-10 14:44:47","doi":"10.21203/rs.3.rs-39825/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2020-09-08T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-08-17T12:00:00+00:00","index":7,"fulltext":"Recommendation: Accept after minor essential revisions\nForm responses:\n---\n\nComments to Author:\n---\nThis is a really interesting and novel piece of work. I have two suggestions regarding the manuscript;\n\nThe results section doesn't read as a section of continuous prose due to each section beginning with sentences such as \"Figure 4 shows the space-time pattern of breast cancer incidence at the county level\". This information is already present in the figure caption so these lines could be lost and the figure referenced later in the paragraph instead. Example \"The descriptive maps (Figure 4) revealed that the incidence was highest in the North-East of the province from March 2014 to March 2017. However, as the cluster maps show, there were HH clusters of breast cancer in the North-West of the province from March 2014 to March 2017; furthermore, there was LL cluster in the South-East of the province from March 2014 to March 2015 and March 2016 to March 2017.\"\n\nIn the discussion there is no mention of whether the areas with low incidence could actually have incidence comparable to that of the other regions but the diagnoses are not made or recorded. Is this possible? Are there lower levels of attendance at healthcare services in general in these regions?\n\n\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\n* Declaration of competing interests: **I declare that I have no competing interests.**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"editorInvitedReview","content":"","date":"2020-08-15T12:00:00+00:00","index":6,"fulltext":"Recommendation: Accept after minor essential revisions\nForm responses:\n---\n\nComments to Author:\n---\nThe submitted paper \"Spatio-temporal mapping of breast and prostate cancer in South Iran during 2014-2017\" aimed to identify the spatial pattern of breast and prostate cancers and to investigate the potential clustering in gender-specific incidents pattern of thses cancers in south Iran between 2014-2017.Generally speaking，it is a very important epidemiologic study to identify high-risk geographical areas for breast and prostate cancer in south Iran. All the spatial analyses and the descriptive analyses were detailed. But there some minor defects in this paper. For publication，I would suggest that the authors to add those relevant portions and correct the numerical errors. I would be happy to consider accepting it after minor revision.\n\nComments\n\n1. In \"Background\", a number 4 was missing in the last sentence(line 12).\n\n2. In \" Spatial Cluster Analysis\" ,the the author mentioned that the Local Moran's I statistic was performed to quantify spatial autocorrelation of cancers frequency at county and district level, and a z-score and p-value were calculated to determine whether the apparent similarity or dissimilarity. But in this manuscript the author did not provide those values ?\n\n3. In \" Results\" , it's necessary to add some diagrams such as scatterplot and QQ plot to demonstrate the process of outlier detection and data feature exploration.\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Declaration of competing interests: **I declare that I have no competing interests**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please publish my name with my report.**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"editorInvitedReview","content":"","date":"2020-08-04T12:00:00+00:00","index":2,"fulltext":"Recommendation: Reject\nForm responses:\n---\n\nComments to Author:\n---\nTitle: Spatio-temporal mapping of breast and prostate cancer in South Iran during 2014-2017\n\nDate: 5.08.2020\nReviewer's report:\nThis is a paper that might be of interest for those in the related field. I have some comments and suggestions which may improve the quality of the manuscript.\n.\n1. Abstract\nBackground:\nThis sentence is not necessary \"In developing countries, screening of Methods:\n- all population at risk of cancers is impractical because of the healthcare resource limitations\".\n- What is the primary source of these data?\n\nConclusion: Authors have mentioned \"North-West Kerman had a significantly higher incidence rate of both breast and prostate cancer\" compared to what? National or international figure?\nThe conclusion is definite, with this type of study design recommendation should be mentioned with caution\n2. Introduction\nThe first two sentences are not related to the topic\nThe first paragraph presents justification should be moved to the end of the intro\nLines 54-60 on page 4 and lines 4-9 page 5, should jump to the methods section\n3. Method and materials\nThe last sentence of the data source should move to the analysis section\nSubheadings could be combined for the analysis section\nWhich standard population has been used for the calculation of the ASR, more explanation is needed.\nFigure 1 end of the methods section should move to the results section\n4. Results\n- too many figures have presented separately, they could be combined in fewer pictures with a, b, c, ..\nAge distribution of the cancers is not related to the topic.\nNeeds major restructuring\n\n5. Discussion\nThe main issue with this part is\nBecause the period for the study is short, the study design is descriptive, any comparison or justification of the results should be presented with caution, authors should explain the discussion with a consideration of these limitations\nLimitation of the study should be addressed clearly\n\n * Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Declaration of competing interests: **I declare that I have no competing interests.**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **No**\n* Is the presentation of the work clear?: **No**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"editorInvitedReview","content":"","date":"2020-08-04T12:00:00+00:00","index":5,"fulltext":"Recommendation: Major revisions required\nForm responses:\n---\n\nComments to Author:\n---\n-Add more on the basic of this disease in the introduction\n-Discus role of imaging in patients with breast and prostate cancer using these ref\n-Razek AA, Lattif MA, Denewer A, Farouk O, Nada N. Assessment of axillary lymph nodes in patients with breast cancer with diffusion-weighted MR imaging in combination with routine and dynamic contrast MR imaging. Breast Cancer 2016;23:525-32.\n-Abdel Razek AA, Gaballa G, Denewer A, Tawakol I. Diffusion weighted MR imaging of the breast. Acad Radiol 2010;17:382-6.\n-English language correction through the manuscript\n-Discus merits and limitations of technique appiled\n-Update of references as most of references are old using these ref\n--Razek AAKA, El-Adalany MA, El-Metwally D. Role of diffusion-weighted imaging in prediction of nipple-areolar complex invasion by breast cancer. Clin Imaging 2020;69:45-49.\n-Abdel Razek A, Zaki M, Bayoumi D, Taman S, AbdelWahab K, Alghandour R. Diffusion tensor imaging parameters in differentiation recurrent breast cancer from post-operative changes in patients with breast-conserving surgery. Eur J Radiol 2019;111:76-80.\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Declaration of competing interests: **I declare that I have no competing interests'**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please publish my name with my report.**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"reviewerAgreed","content":"","date":"2020-08-03T12:00:00+00:00","index":5,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-08-03T12:00:00+00:00","index":9,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-08-03T12:00:00+00:00","index":8,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-08-03T12:00:00+00:00","index":7,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-08-03T12:00:00+00:00","index":6,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-07-27T12:00:00+00:00","index":4,"fulltext":"Recommendation: Accept after minor essential revisions\nForm responses:\n---\n\nComments to Author:\n---\nIn the current manuscript entitled \"Spatio-temporal mapping of breast and prostate cancer in South Iran during 2014-2017\" the authors have demonstrated that North-West Kerman had a significantly higher incidence rate of both breast and prostate cancer. The authors also provide a future perspective that this study generates new hypotheses to test potential relationships between environmental risk factors and incidence of cancers in areas with higher cancer risk. The study may help to design tailored screening and surveillance systems. However, there are few comments which need to be addressed for the possible publication with BMC Cancer\n\n1. Linguistic errors are there in the article which should be rectified.\n2. The manuscript represents that data of 2014-2017 which seems to be of old school. The authors are suggested to add recent data which will be more reliable.\n3. Since cancer is a multifactorial outcome, the authors should also consider the status of subjects enrolled/studied for example how much of subjects were regularly using alcohol, smoking etc. which are causative factors of cancer.\n\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Declaration of competing interests: **I declare that I have no competing interests**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **No**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"editorInvitedReview","content":"","date":"2020-07-27T12:00:00+00:00","index":3,"fulltext":"Recommendation: Accept after minor essential revisions\nForm responses:\n---\n\nComments to Author:\n---\nThe methods are original and results doubtless important for Iranian medical community.* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Declaration of competing interests: **i have no competing interests**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **No**\n"},{"type":"reviewerAgreed","content":"","date":"2020-07-26T12:00:00+00:00","index":4,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-07-25T12:00:00+00:00","index":1,"fulltext":"Recommendation: Major revisions required\nForm responses:\n---\n\nComments to Author:\n---\n1.The title of the manuscript could be changed to -'Spatio-temporal mapping of breast and prostate cancer in South Iran from 2014-2017'\n2.In background section,Kindly rephrase the following grammatically incorrect sentence-'The majority of deaths occur due to non-communicable diseases such as cancers, the second leading cause of death worldwide'\n3.The word 'Cancers' is being repeatedly \u0026 excessively used in every line in the first \u0026 2nd paragraph in background section,it can be limited in its usage.\n4.The following sentence in Background section is not very clear in its message-'It seems that one of the most efficient ways of decreasing the cost of screening, finding the people at risk and implementing more efficient diagnostic strategies is identifying high-risk geographical area'.Kindly phrase it better.\n5.Please use proper punctuations in the following sentence in 2nd paragraph,background section-'At the same time, Rohani-Rasaf et al. (18) detected some high-risk regions in the capital of Iran Tehran for both breast and prostate cancers''\n6.Kindly do a spell check in the following very poorly written sentence in the background section-'Most studies in Iran applied spatial analyses at very coarse level (province scale) and this is, to best of our knowledge, the frist study that investiages the spatial clustering in the pattern of breast and prostate cancers incidence at a finer graography scale in the South part of Iran'.\n7.I presume,the authors meant to write '2014' in the last sentence in the background section-'This study aims to identify the spatial pattern of breast and prostate cancers and to investigate the potential clustering in gender-specific incidents pattern of thses cancers in south Iran between 201-2017'.\n8.Kindly mention the inclusion \u0026 exclusion criteria of the study in the 'Methods' section\n9.Please mention the limitations and future course of the study at the end of the discussion section.\n10.The study has a very interesting premise,unfortunately the manuscript is very amateurishly written with spelling mistakes and poor written english language throughout the manuscript.* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Declaration of competing interests: **'I declare that I have no competing interests'**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please publish my name with my report.**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **No**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"reviewerAgreed","content":"","date":"2020-07-22T12:00:00+00:00","index":3,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-07-20T12:00:00+00:00","index":2,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-07-17T12:00:00+00:00","index":1,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-07-13T12:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2020-07-13T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-07-09T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-07-09T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f41fc7a-c885-44ad-9b63-0940d0d20c13","owner":[],"postedDate":"December 3rd, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":1074633,"name":"Cancer Biology"},{"id":1074634,"name":"Oncology"}],"tags":[],"updatedAt":"2020-12-06T15:02:40+00:00","versionOfRecord":{"articleIdentity":"rs-39825","link":"https://doi.org/10.1186/s12885-020-07674-8","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2020-11-30 15:00:58","publishedOnDateReadable":"November 30th, 2020"},"versionCreatedAt":"2020-12-03 14:18:06","video":"","vorDoi":"10.1186/s12885-020-07674-8","vorDoiUrl":"https://doi.org/10.1186/s12885-020-07674-8","workflowStages":[]},"version":"v4","identity":"rs-39825","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-39825","identity":"rs-39825","version":["v4"]},"buildId":"i_I_jhV-QviBjPLXJga9V","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}