Neuromuscular, Psychological, and Sleep Predictors of Cancer-Related Fatigue in Cancer Patients

Cancer-related fatigue (CRF) is the most reported side effect of cancer and its treatments. This distressing sense of exhaustion critically impairs quality of life and can persist for years after treatment completion. Mechanisms of CRF are multidimensional (eg, physical, psychological, or behavioral), suggesting the need for a complex assessment. Nevertheless, CRF remains assessed mainly with 1-dimensional questionnaires. The purpose of this study was to test whether neuromuscular parameters enhance a model including well-known predictors of CRF. Forty-five participants with cancer history completed self-assessment questionnaires about quality of life, CRF, sleep disturbances, and emotional symptoms. They also completed a 5-minute handgrip fatiguing test composed of 60 maximal voluntary contractions to assess neuromuscular fatigability. Hierarchical linear regression analyses were performed to determine whether the neuromuscular fatigability threshold improved the FA12 score prediction beyond that provided by anxiety/depression and sleep disturbances. The hierarchical linear regression analysis evidenced that a model including anxiety/depression, sleep disturbances, and neuromuscular fatigability explained 56% of CRF variance. In addition, the results suggest that the mechanisms leading to CRF may be different from one person to another. Results revealed that sleep disturbances, emotional symptoms, and neuromuscular fatigability were the most important CRF predictors in cancer patients. This information could be useful for healthcare professionals offering tailored, individual support to patients with CRF. Mechanisms of cancer-related fatigue (CRF) are multidimensional. Hierarchical linear regression analyses were performed to test a multidimensional model of CRF including psychological, sleep, and neuromuscular fatigability in 45 cancer patients. Final model including anxiety/depression, sleep disturbances, and neuromuscular fatigability explained 56% of CRF variance. This could be useful for healthcare professionals offering tailored individual support to patients with CRF.