Background: The open-label, single-arm enzalutamide expanded access program (EAP) in the United States and Canada evaluated the safety of enzalutamide in patients with metastatic castration-resistant prostate cancer (mCRPC) who had previously received docetaxel.
Methods: Patients (n = 507) received enzalutamide 160 mg/day until disease progression, intolerable adverse events (AEs), or commercial availability occurred. AEs and other safety variables were assessed on day 1, weeks 4 and 12, and every 12 weeks thereafter. Data following transition to commercial drug were not collected.
Results: Median age was 71 years (range 43-97); 426 patients (83.9%) had a baseline ECOG score of ≤1. In addition to docetaxel, the majority of patients had received prior prostate cancer treatments such as abiraterone (76.1%) or cabazitaxel (28.6%). Median study treatment duration was 2.6 months (range 0.03-9.07). The most frequently reported reasons for discontinuation were commercial availability of enzalutamide (46.7%) and progressive disease (33.7%). A total of 88.2% of patients experienced AEs; 45.4% experienced AEs with a maximum grade of 1 or 2. Fatigue (39.1%), nausea (22.7%), and anorexia (14.8%) were the most commonly reported AEs. Seizure was reported in four patients (0.8%). The most commonly reported event leading to death was progression of metastatic prostate cancer (7.7%).
Conclusion: In this heavily pretreated EAP population with progressive mCRPC, enzalutamide was well tolerated and the safety profile was consistent with that of the AFFIRM trial.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5024054 | PMC |
http://dx.doi.org/10.1002/pros.22965 | 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.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!