Geospatial analysis of population-based incidence of multiple myeloma in the United States |
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| Institution: | 1. Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA;2. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA;1. Department of Social Medicine, Public Health and Healthcare Management, Dnipro State Medical University, Dnipro, Ukraine;2. Cancer Registry of Dnipropetrovsk region, Dnipro, Ukraine;3. Communal enterprise \"Dnipro Regional Clinical Oncology Dispensary\" of the Dnipropetrovsk Regional Council, Dnipro, Ukraine;4. Department of Public Health of the Dnipro City Council, Dnipro, Ukraine;1. Department of Surgery, Flinders University, Adelaide, Australia;2. Department of Urology, Austin Health, Melbourne, Australia;3. Urology Unit, Flinders Medical Centre, Adelaide, Australia;4. Flinders Health and Medical Research Institute, Flinders University, Adelaide, Australia;5. Discipline of Medicine, University of Adelaide, Adelaide, Australia;1. Department of Public Health, and Department of Endocrinology of the Children''s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children’s Health, Hangzhou 310058, China;2. Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China;3. Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China;1. Department of Hematology, Institut d’hématologie de Basse-Normandie, University Hospital, Normandy University, School of Medicine, Caen, France;2. Department of Research, University Hospital, Caen, France;3. ANTICIPE U1086 Inserm-University of Caen, Centre François Baclesse, Caen, France;4. Laboratory of Hematology, University Hospital, Caen, France;5. Registre Régional des Hémopathies malignes de Basse-Normandie, University Hospital of Caen, Caen, France;1. John P. Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA;2. The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA;3. Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA;4. The Joint Pathology Center, National Capital Region Medical Directorate, Defense Health Agency, Silver Spring, MD, USA;5. Department of Surgery, Walter Reed National Military Medical Center, Bethesda, Maryland |
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| Abstract: | BackgroundWe investigated the spatial patterns of multiple myeloma (MM) incidence in the United States (US) between 2013 and 2017 to improve understanding of potential environmental risk factors for MM.MethodsWe analyzed the average county-level age-adjusted incidence rates (“ASR”) of MM between 2013 and 2017 in 50 states and the District of Columbia using the U.S. Cancer Statistics Public Use Databases. We firstly divided the ASR into quintiles and described spatial patterns using a choropleth map. To identify global and local clusters of the ASR, we performed the Spatial Autocorrelation (Global Moran’s I) analysis and the Anselin’s Local Indicator of Spatial Autocorrelation (LISA) analysis. We compared the means of selected demographic and socioeconomic factors between the clusters and counties of the whole US using Welch one-sided t-test.ResultsWe identified distinct spatial dichotomy of the ASR across counties. High ASR were observed in counties in the Southeast of the US as well as the Capital District (metropolitan areas surrounding Albany) and New York City in the state of New York, while low ASR were observed in counties in the Southwest and West of the US. The ASR showed a significant positive spatial autocorrelation. We identified two major high-high local clusters of the ASR in Georgia and Southern Carolina and five major low-low local clusters of the ASR in Alabama, Arizona, New Hampshire, Ohio, Oregon, and Tennessee. The racial population distribution may partly explain the spatial distribution of MM incidence in the US.ConclusionFindings from this study showed distinct spatial distribution of MM in the US and two high-high and five low-low local clusters. The non-random distribution of MM suggests that environmental exposures in certain regions may be important for the risk of MM. |
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| Keywords: | Multiple myeloma Spatial analysis Environmental exposure |
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