98%
921
2 minutes
20
Skeletal-related events (SREs) are common in patients with bone metastases from castration-resistant prostate cancer (CRPC). Despite advances in prostate cancer treatment, clinically validated predictive models for SREs in CRPC patients with bone metastases remain elusive. This gap in prognostic tools hinders optimal patient management and treatment planning for this high-risk population. This study aimed to develop a prediction model for SRE by investigating potential risk factors and classifying them into different groups. This model can be used to identify patients at high risk of SREs who need close follow-up. Between 2004 and 2013, 68 male patients with bone metastases from CRPC who were treated at our institute were evaluated for survival without SREs and survival without SREs of the spinal cord. The study analyzed clinical data at enrollment to identify risk factors for initial and spinal SREs. Multivariate analysis revealed that a high count of metastatic vertebrae, along with visceral or lymph node metastases, were significant risk factors. Patients were categorized into four subgroups based on the number of vertebral metastases and presence of visceral or lymph node metastases: 1) extensive vertebral and both types of metastases, 2) extensive vertebral without additional metastases, 3) some vertebral with other metastases, 4) some vertebral without additional metastases. The first SRE and spinal SRE occurred significantly sooner in the first subgroup compared to others. Incidence rates at 12 months for the first SRE were 56%, 40%, 27%, and 5%, and for the first spinal SRE were 47%, 40%, 27%, and 0% respectively. Patients with extensive vertebral and additional metastases require vigilant monitoring to mitigate SREs.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352678 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0328792 | PLOS |
J Clin Oncol
September 2025
Carole Mercier, MD, and Charlotte Billiet, MD, PhD, Department of Radiation Oncology, Iridium Network, Wilrijk, Antwerp, Belgium, Integrated Personalised and Precision Oncology Network, University Antwerp, Antwerp, Belgium; Charlotte Billiet, MD, PhD, Department of Radiation Oncology, Iridium Networ
J Clin Oncol
September 2025
Xingpeng Luo, MD, Bin Li, MD, and Yinglong Xi, MD, Orthopedic Treatment Center, Southern Central Hospital of Yunnan Province (The First People's Hospital of Honghe State), Mengzi City, China; and Zhixiang Chen, MD, Department of Nephrology, Southern Central Hospital of Yunnan Province (The First Peo
Endocr Relat Cancer
September 2025
Endocrinology, Diabetology and Medical Andrology Unit, IRCCS, Humanitas Research Hospital, Rozzano, Milan, Italy.
Bone metastases (BMs) are rare and late event in patients with neuroendocrine tumors (NETs). The aim of our study was to investigate clinical presentation and outcome of BMs in a large cohort of patients with NETs. A retrospective study was performed at two referral centers of Northern Italy (IRCCS Humanitas Research Hospital in Milan and S.
View Article and Find Full Text PDFPalliat Med Rep
April 2025
Department of Oncology, King Faisal Specialist Hospital & Research Centre (KFSH&RC), Jeddah, Saudi Arabia.
Background And Aims: Palliative radiotherapy practice patterns have been reported to vary widely, with a notable underutilization of single fraction treatment schedules. This study aims to investigate the outcomes and care patterns among patients receiving palliative radiotherapy for advanced cancer at a high-volume institution in Saudi Arabia.
Materials And Methods: Electronic records were used to identify patients receiving palliative radiotherapy for advanced cancer between 2018 and 2023.
Front Oncol
August 2025
Department of Nuclear Medicine, General Hospital of Northern Theater Command, Shenyang, Liaoning, China.
Objective: To develop a deep learning radiomics(DLR)model integrating PET/CT radiomics, deep learning features, and clinical parameters for early prediction of bone oligometastases (≤5 lesions) in breast cancer.
Methods: We retrospectively analyzed 207 breast cancer patients with 312 bone lesions, comprising 107 benign and 205 malignant lesions, including 89 lesions with confirmed bone metastases. Radiomic features were extracted from computed tomography (CT), positron emission tomography (PET), and fused PET/CT images using PyRadiomics embedded in the uAI Research Portal.