Carolyn S Harris1, Kord M Kober1, Bruce Cooper1, Yvette P Conley2, Anand A Dhruva3, Marilyn J Hammer4, Steven Paul1, Jon D Levine3, Christine A Miaskowski5,6. 1. School of Nursing, University of California, 2 Koret Way - N631Y, San Francisco, CA, 94143-0610, USA. 2. School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA. 3. School of Medicine, University of California, San Francisco, CA, USA. 4. Dana-Farber Cancer Institute, Boston, MA, USA. 5. School of Nursing, University of California, 2 Koret Way - N631Y, San Francisco, CA, 94143-0610, USA. chris.miaskowski@ucsf.edu. 6. School of Medicine, University of California, San Francisco, CA, USA. chris.miaskowski@ucsf.edu.
Abstract
PURPOSE: Relatively few studies have evaluated for symptom clusters across multiple dimensions. It is unknown whether the symptom dimension used to create symptom clusters influences the number and types of clusters that are identified. Study purposes were to describe ratings of occurrence, severity, and distress for 38 symptoms in a heterogeneous sample of oncology patients (n = 1329) undergoing chemotherapy; identify and compare the number and types of symptom clusters based on three dimensions (i.e., occurrence, severity, and distress); and identify common and distinct clusters. METHODS: A modified version of the Memorial Symptom Assessment Scale was used to assess the occurrence, severity, and distress ratings of 38 symptoms in the week prior to patients' next cycle of chemotherapy. Symptom clusters for each dimension were identified using exploratory factor analysis. RESULTS: Patients reported an average of 13.9 (±7.2) concurrent symptoms. Lack of energy was both the most common and severe symptom while "I don't look like myself" was the most distressing. Psychological, gastrointestinal, weight gain, respiratory, and hormonal clusters were identified across all three dimensions. Findings suggest that psychological, gastrointestinal, and weight gain clusters are common while respiratory and hormonal clusters are distinct. CONCLUSIONS: Psychological, gastrointestinal, weight gain, hormonal, and respiratory clusters are stable across occurrence, severity, and distress in oncology patients receiving chemotherapy. Given the stability of these clusters and the consistency of the symptoms across dimensions, the use of a single dimension to identify these clusters may be sufficient. However, comprehensive and disease-specific inventories need to be used to identify distinct clusters.
PURPOSE: Relatively few studies have evaluated for symptom clusters across multiple dimensions. It is unknown whether the symptom dimension used to create symptom clusters influences the number and types of clusters that are identified. Study purposes were to describe ratings of occurrence, severity, and distress for 38 symptoms in a heterogeneous sample of oncology patients (n = 1329) undergoing chemotherapy; identify and compare the number and types of symptom clusters based on three dimensions (i.e., occurrence, severity, and distress); and identify common and distinct clusters. METHODS: A modified version of the Memorial Symptom Assessment Scale was used to assess the occurrence, severity, and distress ratings of 38 symptoms in the week prior to patients' next cycle of chemotherapy. Symptom clusters for each dimension were identified using exploratory factor analysis. RESULTS: Patients reported an average of 13.9 (±7.2) concurrent symptoms. Lack of energy was both the most common and severe symptom while "I don't look like myself" was the most distressing. Psychological, gastrointestinal, weight gain, respiratory, and hormonal clusters were identified across all three dimensions. Findings suggest that psychological, gastrointestinal, and weight gain clusters are common while respiratory and hormonal clusters are distinct. CONCLUSIONS: Psychological, gastrointestinal, weight gain, hormonal, and respiratory clusters are stable across occurrence, severity, and distress in oncology patients receiving chemotherapy. Given the stability of these clusters and the consistency of the symptoms across dimensions, the use of a single dimension to identify these clusters may be sufficient. However, comprehensive and disease-specific inventories need to be used to identify distinct clusters.
Authors: Patsy Yates; Christine Miaskowski; Janine K Cataldo; Steven M Paul; Bruce A Cooper; Kimberly Alexander; Bradley Aouizerat; Laura Dunn; Christine Ritchie; Alexandra McCarthy; Helen Skerman Journal: J Pain Symptom Manage Date: 2015-01-10 Impact factor: 3.612
Authors: Muthukkumaran Thiagarajan; Caryn Mei Hsien Chan; Ho Gwo Fuang; Tan Seng Beng; M A Atiliyana; N A Yahaya Journal: Asian Pac J Cancer Prev Date: 2016