You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

The Impact of Diabetes on the Risk of Prostate Cancer Development according to Body Mass Index: A 10-year Nationwide Cohort Study Purpose: We examined the association between obesity and prostate cancer both with and without diabetic patients included in the analysis using nationally representative data of the Korean population from the National Health Insurance System (NHIS). Materials and Methods: Of the 424,712 participants who underwent health examinations in 2002-2008, 139,519 men ≥40 years old and without prostate cancer were followed from the beginning of 2002 to the end of 2012. Multivariate adjusted Cox regression analysis was conducted to examine the hazard ratio (HR) and 95% confidence interval (CI) for the association between prostate cancer and body mass index (BMI) both with and without diabetes. Results: The HR for prostate cancer according to the existence of diabetes was stratified by BMI in both age - and multivariable-adjusted models. In the population without diabetes, the HR for prostate cancer significantly increased as BMI increased beyond the reference range in a model adjusted for age and multiple variables; however, the increase in the HR was small. In the population with diabetes, the HR for prostate cancer significantly increased as BMI increased from < 18.5 kg/m(2) to within the reference range (18.5 to 22.9) in the multivariable-adjusted model. In addition, a marked decrease in HR in the population with BMI of < 18.5 kg/m(2) was seen compared to the reference or higher BMI population. Conclusion: This population -based study shows the evidence of association between obesity and development of prostate cancer, and the risk increases vary according to the change of BMI category and the existence of diabetes.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["diabetic", "Diabetes", "prostate cancer", "diabetes", "obesity", "Prostate Cancer"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": ["BMI", "body mass index", "Body Mass Index"], "Eukaryote": [], "Finding": ["risk increases"], "Food": [], "HealthCareActivity": ["health examinations", "National Health Insurance System", "NHIS"], "InjuryOrPoisoning": [], "IntellectualProduct": ["Cox regression analysis"], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["participants", "Korean population", "men \u226540 years old", "population"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": [], "SpatialConcept": [], "Virus": []}