Please use this identifier to cite or link to this item: http://ahro.austin.org.au/austinjspui/handle/1/16589
Title: Symptom clusters in advanced cancer patients: an empirical comparison of statistical methods and the impact on quality of life
Authors: Dong, Skye T;Costa, Daniel SJ;Butow, Phyllis N;Lovell, Melanie R;Agar, Meera;Velikova, Galina;Teckle, Paulos;Tong, Allison;Tebbutt, Niall C;Clarke, Stephen J;van der Hoek, Kim;King, Madeleine T;Fayers, Peter M
Issue Date: Jan-2016
EDate: 2015-08-25
Citation: Journal of Pain and Symptom Management 2016; 51(1): 88-98
Abstract: CONTEXT: Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. OBJECTIVES: To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. METHODS: Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. RESULTS: Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. CONCLUSIONS: The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential.
URI: http://ahro.austin.org.au/austinjspui/handle/1/16589
DOI: 10.1016/j.jpainsymman.2015.07.013
PubMed URL: https://www.ncbi.nlm.nih.gov/pubmed/26300025
Type: Journal Article
Subjects: Symptom clusters
EORTC QLQ-C30
Statistical methods
Advanced cancer
Quality of life
Appears in Collections:Journal articles

Files in This Item:
There are no files associated with this item.


Items in AHRO are protected by copyright, with all rights reserved, unless otherwise indicated.