Abstract

BackgroundCancer related fatigue (CRF) and pain are debilitating conditions in cancer patients. Both have been associated with the personality or temperament and with the mental health status of patients. It remains unclear how these factors interact when combined in a single, comprehensive model. MethodsIn this study, we used a multivariate network approach to gain a better understanding of their interconnection. We estimated a glasso and a relative importance network in a sample of 3923 cancer patients (mean age = 58.3 years; 50.5 % women) using visual analogue scales to assess CRF and pain, the HADS to assess anxiety and depression, and the TEMPS-M to assess affective temperament. ResultsWhile affective temperament showed bivariate associations with CRF and pain, it was only indirectly connected to them in the glasso network model, mediated through depression and to a smaller extent through anxiety. The relative importance network revealed that CRF and pain most strongly contributed to the prediction of each other, followed by depression and anxiety. LimitationsOther variables including disease progression, type of therapy, and the tumor macroenvironment (patient income, educational level etc.) might influence the observed associations but were not considered in our analysis. Our analysis is based on cross-sectional data and causal interpretations should be done carefully. ConclusionsTemperament as predictor of CRF and pain seems of little importance when depression and anxiety are considered. Understanding the depression-fatigue-pain cluster as vicious cycle underlines the necessity to address all these conditions in parallel with a multimodal combination of treatments.

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