Impact of Symptom Clusters on Quality of Life (QOL) Dimensions in Breast Cancer Patients

2.50
Hdl Handle:
http://hdl.handle.net/10755/154635
Type:
Presentation
Title:
Impact of Symptom Clusters on Quality of Life (QOL) Dimensions in Breast Cancer Patients
Abstract:
Impact of Symptom Clusters on Quality of Life (QOL) Dimensions in Breast Cancer Patients
Conference Sponsor:Sigma Theta Tau International
Conference Year:2005
Author:Dodd, Marylin J., RN, PhD, FAAN
P.I. Institution Name:University of California San Francisco
Title:Professor
Co-Authors:Maria H. Cho, RN, PhD; Kayee Alice Bank, RN, MS, CNS; Bruce A. Cooper, PhD; Kathryn A. Lee, RN, PhD, FAAN; Christine Miaskowski, RN, PhD, FAAN
This innovative presentation reports the next generation of symptom management work, symptom clusters (i.e., three or more concurrent related symptoms) experienced by breast cancer patients. These patients have a high prevalence of pain, fatigue, depression, and sleep disturbance that vary in combination and intensity for different groups of patients. The nature of these groups with similar symptom profiles and differences among these groups on QOL and its subscales has not been reported. Purpose:To compare patients with differing symptom clusters and overall QOL and its five subscales at three time points. Methods:80 women with breast cancer, mean age 49 (SD=9.6), were part of an ongoing randomized clinical trial; completed QOL and symptom-specific questionnaires (sleep, fatigue, pain, and depression) at three time points; T1=during cancer treatment, T2=completion of cancer treatment, and T3=end of study. The questionnaires used have established reliability and validity. Cluster analysis identified patient groups, and Kruskal-Wallis test with post hoc pairwise Man-Whitney U-tests compared groups. Results: A cluster analysis on symptom similarities yielded four relatively distinct patient groups: No Symptoms (NS); Pain & Fatigue (PF), moderate severity; Depression, Fatigue & Sleep (DFS) and Pain, Fatigue & Sleep (PFS) symptom clusters, moderate severity; and All Symptoms (AS), high severity. At each time point, significant differences among the symptom cluster groups in overall QOL were found. At T1, comparison between the NS and DFS groups yielded significant difference on overall QOL. At T2, significant differences were found for all subscales, except symptom distress, when comparing NS to AS. At T3, significant differences were found for overall QOL as well as the psychological and physical subscales when comparing NS to DFS, PFS, and AS. Implications for Nursing: Patients with differing symptom profiles were identified that may predict current and future patients' morbidity; a new and promising area in symptom management.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleImpact of Symptom Clusters on Quality of Life (QOL) Dimensions in Breast Cancer Patientsen_GB
dc.identifier.urihttp://hdl.handle.net/10755/154635-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Impact of Symptom Clusters on Quality of Life (QOL) Dimensions in Breast Cancer Patients</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2005</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Dodd, Marylin J., RN, PhD, FAAN</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of California San Francisco</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Professor</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">marylin.dodd@nursing.ucsf.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Maria H. Cho, RN, PhD; Kayee Alice Bank, RN, MS, CNS; Bruce A. Cooper, PhD; Kathryn A. Lee, RN, PhD, FAAN; Christine Miaskowski, RN, PhD, FAAN</td></tr><tr><td colspan="2" class="item-abstract">This innovative presentation reports the next generation of symptom management work, symptom clusters (i.e., three or more concurrent related symptoms) experienced by breast cancer patients. These patients have a high prevalence of pain, fatigue, depression, and sleep disturbance that vary in combination and intensity for different groups of patients. The nature of these groups with similar symptom profiles and differences among these groups on QOL and its subscales has not been reported. Purpose:To compare patients with differing symptom clusters and overall QOL and its five subscales at three time points. Methods:80 women with breast cancer, mean age 49 (SD=9.6), were part of an ongoing randomized clinical trial; completed QOL and symptom-specific questionnaires (sleep, fatigue, pain, and depression) at three time points; T1=during cancer treatment, T2=completion of cancer treatment, and T3=end of study. The questionnaires used have established reliability and validity. Cluster analysis identified patient groups, and Kruskal-Wallis test with post hoc pairwise Man-Whitney U-tests compared groups. Results: A cluster analysis on symptom similarities yielded four relatively distinct patient groups: No Symptoms (NS); Pain &amp; Fatigue (PF), moderate severity; Depression, Fatigue &amp; Sleep (DFS) and Pain, Fatigue &amp; Sleep (PFS) symptom clusters, moderate severity; and All Symptoms (AS), high severity. At each time point, significant differences among the symptom cluster groups in overall QOL were found. At T1, comparison between the NS and DFS groups yielded significant difference on overall QOL. At T2, significant differences were found for all subscales, except symptom distress, when comparing NS to AS. At T3, significant differences were found for overall QOL as well as the psychological and physical subscales when comparing NS to DFS, PFS, and AS. Implications for Nursing: Patients with differing symptom profiles were identified that may predict current and future patients' morbidity; a new and promising area in symptom management.</td></tr></table>en_GB
dc.date.available2011-10-26T13:09:21Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T13:09:21Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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