The identification of multiple symptom clusters and their effects on functional performance in cancer patients.
OBJECTIVE
To identify cancer-related symptom clusters, to explore their inter-relationships and to examine the effects of single symptoms and the synergistic effects of symptom clusters on functional performance using path analysis by structural equation modelling in patients with various types of cancer.


BACKGROUND
Recent studies suggest that cancer patients frequently experience three or more concurrent related symptoms and that this clustering of symptoms is likely to have negative synergistic impacts on outcomes, because of the complicated dynamics of clusters.


METHODS
A cross-sectional design.


METHODS
One hundred and ten patients with various types of cancer were recruited as in- and out-patients at a University Hospital in Incheon, South Korea. Data collection was performed using a questionnaire and by direct interview. Pain, insomnia, fatigue, depression and functional performance were measured.


RESULTS
The developed model was composed of antecedents, symptom clusters and outcomes. Of the symptoms often encountered as clusters in cancer patients, insomnia, depression and fatigue were found to have significant single (direct) effects on functional performance. Seven symptom clusters were identified between pain and functional performance, three between insomnia and functional performance and one between depression and functional performance. These single symptoms and symptom clusters were found to have significant synergistic effects on functional performance and to explain 24% of functional performance variance.


CONCLUSIONS
Multiple cancer-related symptom clusters may occur and the dynamics within symptom clusters is complicated. Our findings provide sound evidence regarding the importance of assessing and managing clusters of symptoms simultaneously rather than focusing on single symptoms.


CONCLUSIONS
A comprehensive understanding of symptom clusters in cancer patients would help establish valid diagnostic symptom cluster entities and aid the development of subjective/objective phenotypic criteria for symptom cluster based diagnoses and of nursing care protocols for managing symptom clusters.
Department of Nursing, Inha University, Incheon, Korea.
HyunSoo
H
Oh
YoungMin
Y
Seo
HyeSun
H
Jeong
WhaSook
W
Seo
D000328:Adult; D000368:Aged; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009369:Neoplasms / Q000453:epidemiology* / Q000473:pathology; D056910:Republic of Korea / Q000453:epidemiology