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Purpose: This qualitative study aimed to explore the experiences of patients with cancer and bone metastases who participated in a personalized exercise program.
Methods: Individual interviews were conducted through purposeful sampling of patients who attended the 3-month supervised exercise program. Using a phenomenological approach, semi-structured questions were developed to investigate the benefits, risks, facilitators, and barriers related to exercise. Data were analyzed using inductive thematic analysis.
Results: Thirteen patients with mixed cancer types participated in the study. Patients recognized the physical and psychological benefits of exercise, such as improvements in physical fitness, bone health, reduction of symptoms, especially pain and fatigue, and increase in self-confidence. While they did not perceive any disadvantage from participating in the program, they acknowledged the risk of bone fractures or exacerbation of lesions if the intervention is not tailored and supervised. The program's structure, including the involvement of dedicated specialists, has been reported as a fundamental pillar. Among the modulators for participation and adherence, comorbidities associated with bone metastases, logistic barriers, and lack of social support may be obstacles. Conversely, recommendations from the oncologist, personal motivation, and peer support were found to be facilitators of practice.
Conclusions: Patients with bone metastases expressed a broad range of benefits from participation in a structured exercise program. Several modulators may affect uptake and adherence and thus should be considered when designing a dedicated program.
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http://dx.doi.org/10.1002/cam4.70865 | DOI Listing |
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.