• Bmc Med Res Methodol · Jan 2008

    The changing causal foundations of cancer-related symptom clustering during the final month of palliative care: a longitudinal study.

    • Karin Olson, Leslie Hayduk, Marilyn Cree, Ying Cui, Hue Quan, John Hanson, Peter Lawlor, and Florian Strasser.
    • Faculty of Nursing, University of Alberta, Edmonton, Alberta, Canada. karin.olson@ualberta.ca
    • Bmc Med Res Methodol. 2008 Jan 1;8:36.

    BackgroundSymptoms tend to occur in what have been called symptom clusters. Early symptom cluster research was imprecise regarding the causal foundations of the coordinations between specific symptoms, and was silent on whether the relationships between symptoms remained stable over time. This study develops a causal model of the relationships between symptoms in cancer palliative care patients as they approach death, and investigates the changing associations among the symptoms and between those symptoms and well-being.MethodsComplete symptom assessment scores were obtained for 82 individuals from an existing palliative care database. The data included assessments of pain, anxiety, nausea, shortness of breath, drowsiness, loss of appetite, tiredness, depression and well-being, all collected using the Edmonton Symptom Assessment System (ESAS). Relationships between the symptoms and well-being were investigated using a structural equation model.ResultsThe model fit acceptably and explained between 26% and 83% of the variation in appetite, tiredness, depression, and well-being. Drowsiness displayed consistent effects on appetite, tiredness and well-being. In contrast, anxiety's effect on well-being shifted importantly, with a direct effect and an indirect effect through tiredness at one month, being replaced by an effect working exclusively through depression at one week.ConclusionSome of the causal forces explaining the variations in, and relationships among, palliative care patients' symptoms changed over the final month of life. This illustrates how investigating the causal foundations of symptom correlation or clustering can provide more detailed understandings that may contribute to improved control of patient comfort, quality of life, and quality of death.

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