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JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
RESEARCH SUPPORT, U.S. GOV'T, P.H.S.
Symptom clusters and their effect on the functional status of patients with cancer.
Oncology Nursing Forum 2001 April
PURPOSE/OBJECTIVES: To determine the effect of the symptom cluster of pain, fatigue, and sleep insufficiency on functional status during three cycles of chemotherapy.
DESIGN: Prospective, longitudinal.
SETTING: 23 outpatient offices and clinics.
SAMPLE: 93 patients with cancer. The typical participant was female (72%), married/partnered (65%), white (87%), and middle-aged (55.4 years), with an average of 14.8 years of education.
METHODS: The Quality of Life-Cancer (QOL-CA) version instrument and the Karnofsky Performance Scale (KPS) were completed by 93 outpatients receiving chemotherapy at baseline (Time 1) and at the end of the third cycle (Time 2). Three items (pain, tires easily, sleeps enough to meet needs) from the QOL-CA questionnaire were used to measure the symptom cluster.
MAIN RESEARCH VARIABLES: Symptom cluster, outcome, functional status, chemotherapy.
FINDINGS: A hierarchical multiple regression model explained 48.4% of the variance in functional status. The KPS at Time 1 explained 30.8% of the variance in KPS at Time 2 (p < 0.001). After KPS at Time 1 was partialled out from KPS at Time 2, the four independent variables entered in the next step were considered predictors of the change in functional status between Time 1 and Time 2. Age explained 11.8% of the change (p = 0.001), pain explained 10.7% of the change (p = 0.002), and fatigue explained 7.3% of the change (p = 0.011). Sleep insufficiency statistically was not significant, only explaining 1% of the change (p = 0.344).
CONCLUSION: This study provides beginning insights into the effect of a symptom cluster on patients' functional status.
IMPLICATIONS FOR NURSING PRACTICE: Healthcare professionals need to be aware of the presence of symptom clusters and their possible synergistic adverse effect on patients' future morbidity.
DESIGN: Prospective, longitudinal.
SETTING: 23 outpatient offices and clinics.
SAMPLE: 93 patients with cancer. The typical participant was female (72%), married/partnered (65%), white (87%), and middle-aged (55.4 years), with an average of 14.8 years of education.
METHODS: The Quality of Life-Cancer (QOL-CA) version instrument and the Karnofsky Performance Scale (KPS) were completed by 93 outpatients receiving chemotherapy at baseline (Time 1) and at the end of the third cycle (Time 2). Three items (pain, tires easily, sleeps enough to meet needs) from the QOL-CA questionnaire were used to measure the symptom cluster.
MAIN RESEARCH VARIABLES: Symptom cluster, outcome, functional status, chemotherapy.
FINDINGS: A hierarchical multiple regression model explained 48.4% of the variance in functional status. The KPS at Time 1 explained 30.8% of the variance in KPS at Time 2 (p < 0.001). After KPS at Time 1 was partialled out from KPS at Time 2, the four independent variables entered in the next step were considered predictors of the change in functional status between Time 1 and Time 2. Age explained 11.8% of the change (p = 0.001), pain explained 10.7% of the change (p = 0.002), and fatigue explained 7.3% of the change (p = 0.011). Sleep insufficiency statistically was not significant, only explaining 1% of the change (p = 0.344).
CONCLUSION: This study provides beginning insights into the effect of a symptom cluster on patients' functional status.
IMPLICATIONS FOR NURSING PRACTICE: Healthcare professionals need to be aware of the presence of symptom clusters and their possible synergistic adverse effect on patients' future morbidity.
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