Biobehavioral correlates of multidimensional fatigue in men with prostate cancer: A secondary data analysis

Eur J Oncol Nurs. 2025 Aug 6;78:102963. doi: 10.1016/j.ejon.2025.102963. Online ahead of print.

ABSTRACT

PURPOSE: The purpose of this secondary analysis was to 1) examine trajectories of multidimensional cancer-related fatigue (CRF) in men with prostate cancer during and after radiation treatment completion, and 2) identify biobehavioral correlates (demographic, clinical, co-occurring symptoms, and biologic [inflammatory cytokines]) for the different CRF dimensions.

METHODS: Data were obtained from a descriptive, longitudinal IRB-approved study investigating the biology of CRF in men with prostate cancer receiving radiation therapy. Data were included from 68 participant medical records, self-report questionnaires, and blood samples. Multidimensional CRF was assessed using the MFSI-SF questionnaire. Data were collected at: baseline (T1), completion of radiation therapy (T2), 6 months (T3) and 24 months (T4) after completion of radiation therapy. Spearman Rank correlations between MFSI-SF subscale scores and patient reported outcomes and biomarker values were computed for each time point.

RESULTS: Most dimensions (general, physical, mental) of CRF worsened during treatment, with the exception of improved emotional fatigue. After treatment completion, most CRF dimensions (general, physical, mental) improved, while emotional fatigue remained steady. During treatment, co-occurring symptoms (anxiety, depression, pain, difficulty sleeping) were each observed to be associated with different CRF dimensions. After treatment completion, prostate cancer risk group, co-occurring symptoms, and IL-8 were observed to be associated with different CRF dimensions.

CONCLUSION: The findings support that there may be unique correlates, including biologic correlates, for the different dimensions of CRF. Understanding the different dimensions of CRF is critical for development of tailored assessments and interventions targeted to the unique CRF dimensions to optimize management.

PMID:40849968 | DOI:10.1016/j.ejon.2025.102963