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:

Prostate-specific antigen increase during dutasteride to indicate the need for prostate biopsy: influence of prostatic inflammation The aim of this study was to analyze the significance of an increase in total prostate-specific antigen (PSA) serum levels despite dutasteride treatment as a predictor of prostate cancer (PC) at biopsy. We focused our attention on the rate of the first PSA increase and on the influence of prostatic inflammation. From 2011 to 2016, 365 men with a previous negative prostate biopsy and persistent elevated PSA levels received dutasteride treatment. The population was followed for a range of 12-48 months. One hundred twelve cases with a confirmed PSA increase >0.5 ng/ml over the nadir value during the follow-up were included in Group A and underwent a new prostate biopsy. In Group A, the PSA increase was associated with PC at the re-biopsy in 66% of cases. The percentage of PSA reduction after 6 months of treatment was not a significant indicator of the risk for PC. The distribution of inflammatory infiltrates significantly (p<00.01) varied from positive to negative prostate biopsies. The relative risk for PC at biopsy significantly increase d according to PSA level during dutasteride. Treatment with dutasteride can help to analyze PSA kinetic. A persistent prostatic inflammation is a factor able to reduce the performance of PSA kinetic during dutasteride treatment.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": ["PC", "prostate cancer", "prostatic inflammation"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["dutasteride", "Prostate-specific antigen", "PSA"], "ClinicalAttribute": ["indicator"], "Eukaryote": [], "Finding": ["PSA reduction", "inflammatory infiltrates"], "Food": [], "HealthCareActivity": ["Treatment", "prostate biopsies", "re-biopsy", "follow-up", "prostate biopsy", "treatment", "biopsy"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": ["population", "men"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["analyze"], "SpatialConcept": [], "Virus": []}