Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life

Skye Dong, Daniel Costa, Phyllis Butow, Melanie Lovell, Meera Agar, Galina Velikova, Paulos Teckle, Allison Tong, Niall Tebbutt, Stephen Clarke, Kim van der Hoek, Madeleine King, Peter Fayers

    Research output: Contribution to journalArticlepeer-review

    50 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)88-98
    Number of pages11
    JournalJournal of Pain and Symptom Management
    Volume51
    Issue number1
    DOIs
    Publication statusPublished - 1 Jan 2016

    Keywords

    • advanced cancer
    • EORTC QLQ-C30
    • quality of life
    • statistical methods
    • Symptom clusters

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