Introduction: Having a better understanding of predictors of cancer-related fatigue makes it easier to early identify patients at risk of suffering from long-term fatigue. The aim of this longitudinal study was to identify factors that predict long-term fatigue 6 months after discharge from a rehabilitation clinic using a multidimensional conceptualization.
Method: A mixed sample of cancer survivors (N = 948) were recruited while in-patient at a rehabilitation clinic. The follow-up survey was administered 6 months after they were discharged from the clinic. Fatigue was assessed with the EORTC QLQ-FA12. Predictive values were estimated using hierarchical multiple linear regression analyses.
Results: Mean fatigue scores were 20.7 (cognitive fatigue), 30.9 (emotional fatigue), and 53.2 (physical fatigue) at baseline and significantly lower at follow-up (Cohen's d 0.12-0.31). Baseline levels of fatigue and depression were identified as important predictors of all dimensions of fatigue. Partnership and time since diagnosis predicted only the levels of physical fatigue. The regression models explained between 36% and 45% of variance in fatigue.
Conclusion: Levels of fatigue in early stages as well as psychosocial issues could enable clinicians to identify patients with elevated long-term fatigue and thus to provide optimal care for improving patients' quality of life. Findings of different associates of individual dimensions of fatigue support the multidimensional concept of fatigue.
Keywords: Cancer; Depression; Fatigue; Longitudinal design; Oncology; Predictors.