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Subgroups of Patients With Cancer With Different Symptom Experiences and Quality-of-Life Outcomes: A Cluster Analysis

Christine Miaskowski
Bruce A. Cooper
Steven M. Paul
Marylin Dodd
Kathryn Lee
Bradley E. Aouizerat
Claudia West
Maria Cho
Alice Bank
ONF 2006, 33(5), E79-E89 DOI: 10.1188/06.ONF.E79-E89

Purpose/Objectives: To identify subgroups of outpatients with cancer based on their experiences with the symptoms of fatigue, sleep disturbance, depression, and pain; to explore whether patients in the subgroups differed on selected demographic, disease, and treatment characteristics; and to determine whether patients in the subgroups differed on two important patient outcomes: functional status and quality of life (QOL).

Design: Descriptive, correlational study.

Setting: Four outpatient oncology practices in northern California.

Sample: 191 outpatients with cancer receiving active treatment.

Methods: Patients completed a demographic questionnaire, Karnofsky Performance Status scale, Lee Fatigue Scale, General Sleep Disturbance Scale, Center for Epidemiological Studies-Depression Scale, Multidimensional Quality-of-Life Scale-Cancer, and a numeric rating scale of worst pain intensity. Medical records were reviewed for disease and treatment information. Cluster analysis was used to identify patient subgroups based on patients' symptom experiences. Differences in demographic, disease, and treatment characteristics as well as in outcomes were evaluated using analysis of variance and chi square analysis.

Main Research Variables: Subgroup membership, fatigue, sleep disturbance, depression, pain, functional status, and QOL.

Findings: Four relatively distinct patient subgroups were identified based on patients' experiences with four highly prevalent and related symptoms.

Conclusions: The subgroup of patients who reported low levels of all four symptoms reported the best functional status and QOL.

Implications for Nursing: The findings from this study need to be replicated before definitive clinical practice recommendations can be made. Until that time, clinicians need to assess patients for the occurrence of multiple symptoms that may place them at increased risk for poorer outcomes.