Introduction: As the transgender patient population continues to increase, urologists and other providers who treat genitourinary malignancies will increasingly encounter cases of prostate cancer in transgender women. Little exists in the current literature to help summarize the challenges and opportunities which face this unique patient population. Similarly, little exists to provide guidance on how we may best diagnose, manage, and follow transgender women diagnosed with prostate cancer. We sought to review the available literature in hopes of providing a resource for providers moving forward.
Materials And Methods: We collaboratively reviewed the currently available literature, guidelines, and statements of best practice to compile a comprehensive review of this emerging and important topic.
Results: Transgender persons face numerous systemic barriers to care with well documented increased risks of suicide and poor health outcomes. Though uncommon, the diagnosis of prostate cancer in transgender women is often associated with significant disease. While many options for management remain in line with standard guidelines, the unique aspects of care in this population-prior/current hormone usage, gender-affirming surgical procedures etc.-must be considered. Surgical, radiation, and hormonal treatments all play a potential role in appropriate treatment. Longitudinal studies are currently lacking and clinical trials are often structured with exclusive language which may lead to further marginalization of this patient population.
Conclusion: Transgender persons will almost certainly continue to grow as a population encountered and treated by healthcare professionals. Better training and understanding are needed to ensure all healthcare needs are met as best possible. Prostate cancer represents an area in which great strides may be made to improve both diagnosis and treatment. Urologists, and others who manage urologic cancers, must take the lead to improve the care of transgender persons with genitourinary malignancies.
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http://dx.doi.org/10.1016/j.urolonc.2018.09.011 | DOI Listing |
PLoS One
January 2025
Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, United Kingdom.
Introduction: Undiagnosed chronic disease has serious health consequences, and variation in rates of underdiagnosis between populations can contribute to health inequalities. We aimed to estimate the level of undiagnosed disease of 11 common conditions and its variation across sociodemographic characteristics and regions in England.
Methods: We used linked primary care, hospital and mortality data on approximately 1.
Ann Nucl Med
January 2025
Department of Biomedical Sciences, Humanitas University, Milan, Italy.
The purpose of this systematic review was to evaluate the role of PSMA PET/CT in intermediate-risk prostate cancer (PCa) patients, to determine whether it could help improve treatment strategy and prognostic stratification. A systematic literature search up to May 2024 was conducted in the PubMed, Embase and Scopus databases. Articles with mixed risk patient populations, review articles, editorials, letters, comments, or case reports were excluded.
View Article and Find Full Text PDFJ Neurooncol
January 2025
Department of Neurosurgery, Allegheny Health Network, Neuroscience Institute, Pittsburgh, PA, United States.
Langenbecks Arch Surg
January 2025
Department for the Promotion of Medical Device Innovation, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Purpose: Assessing surgical skills is vital for training surgeons, but creating objective, automated evaluation systems is challenging, especially in robotic surgery. Surgical procedures generally involve dissection and exposure (D/E), and their duration and proportion can be used for skill assessment. This study aimed to develop an AI model to acquire D/E parameters in robot-assisted radical prostatectomy (RARP) and verify if these parameters could distinguish between novice and expert surgeons.
View Article and Find Full Text PDFInsights Imaging
January 2025
Department of Radiology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, China.
Objective: To evaluate the feasibility of utilizing artificial intelligence (AI)-predicted biparametric MRI (bpMRI) image features for predicting the aggressiveness of prostate cancer (PCa).
Materials And Methods: A total of 878 PCa patients from 4 hospitals were retrospectively collected, all of whom had pathological results after radical prostatectomy (RP). A pre-trained AI algorithm was used to select suspected PCa lesions and extract lesion features for model development.
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