Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/16589
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dc.contributor.authorDong, Skye T-
dc.contributor.authorCosta, Daniel SJ-
dc.contributor.authorButow, Phyllis N-
dc.contributor.authorLovell, Melanie R-
dc.contributor.authorAgar, Meera-
dc.contributor.authorVelikova, Galina-
dc.contributor.authorTeckle, Paulos-
dc.contributor.authorTong, Allison-
dc.contributor.authorTebbutt, Niall C-
dc.contributor.authorClarke, Stephen J-
dc.contributor.authorvan der Hoek, Kim-
dc.contributor.authorKing, Madeleine T-
dc.contributor.authorFayers, Peter M-
dc.date2015-08-25-
dc.date.accessioned2017-02-28T23:50:34Z-
dc.date.available2017-02-28T23:50:34Z-
dc.date.issued2016-01-
dc.identifier.citationJournal of Pain and Symptom Management 2016; 51(1): 88-98en_US
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/16589-
dc.description.abstractCONTEXT: 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.en_US
dc.subjectSymptom clustersen_US
dc.subjectEORTC QLQ-C30en_US
dc.subjectStatistical methodsen_US
dc.subjectAdvanced canceren_US
dc.subjectQuality of lifeen_US
dc.titleSymptom clusters in advanced cancer patients: an empirical comparison of statistical methods and the impact on quality of lifeen_US
dc.typeJournal Articleen_US
dc.identifier.journaltitleJournal of Pain and Symptom Managementen_US
dc.identifier.affiliationSchool of Psychology, University of Sydney, Sydney, New South Wales, Australiaen_US
dc.identifier.affiliationPsycho-Oncology Co-operative Research Group (PoCoG), University of Sydney, Sydney, New South Wales, Australiaen_US
dc.identifier.affiliationDepartment of Palliative Care, Braeside Hospital, HammondCare, Sydney, New South Wales, Australiaen_US
dc.identifier.affiliationHammondCare, Greenwich Hospital, Sydney, New South Wales, Australiaen_US
dc.identifier.affiliationThe University of Sydney Medical School, Sydney, New South Wales, Australiaen_US
dc.identifier.affiliationUniversity of NSW, South West Sydney Clinical School, Sydney, New South Wales, Australiaen_US
dc.identifier.affiliationDiscipline of Palliative and Supportive Services, Flinders University, Adelaide, South Australia, Australiaen_US
dc.identifier.affiliationSt James's Hospital, Leeds, UKen_US
dc.identifier.affiliationCanadian Centre for Applied Research in Cancer Control, BC Cancer Research Centre, Vancouver, Canadaen_US
dc.identifier.affiliationSchool of Population and Public Health, University of British Columbia, Canadaen_US
dc.identifier.affiliationSydney School of Public Health, University of Sydney, Sydney, New South Wales, Australiaen_US
dc.identifier.affiliationOlivia Newton-John Cancer and Wellness Centre, Austin Health, Heidelberg, Victoria, Australiaen_US
dc.identifier.affiliationDepartment of Medical Oncology, Royal North Shore Hospital, Sydney, New South Wales, Australiaen_US
dc.identifier.affiliationCentral Clinical School, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australiaen_US
dc.identifier.affiliationUniversity of Aberdeen, Aberdeen, UKen_US
dc.identifier.affiliationDepartment of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norwayen_US
dc.identifier.pubmedurihttps://pubmed.ncbi.nlm.nih.gov/26300025en_US
dc.identifier.doi10.1016/j.jpainsymman.2015.07.013en_US
dc.type.contentTexten_US
dc.type.austinJournal Articleen_US
local.name.researcherTebbutt, Niall C
item.openairetypeJournal Article-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptMedical Oncology-
crisitem.author.deptOlivia Newton-John Cancer Wellness and Research Centre-
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