Differences in Symptom Clusters Identified Using Occurrence Rates Versus Symptom Severity Ratings in Patients at the End of Radiation Therapy

School of Nursing, University of California, San Francisco, California 94143-0610, USA.
Cancer nursing (Impact Factor: 1.97). 10/2009; 32(6):429-36. DOI: 10.1097/NCC.0b013e3181b046ad
Source: PubMed


The purposes of this study were to identify the number and types of symptom clusters using yes/no responses from the Memorial Symptom Assessment Scale, identify the number and types of symptom clusters using severity scores from the Memorial Symptom Assessment Scale, compare the identified symptom clusters derived using severity scores to those derived using occurrence ratings, and evaluate for differences in symptom cluster severity scores between patients with breast and prostate cancer at the end of radiation therapy. Separate exploratory factor analyses were performed to determine the number of symptom clusters based on symptom occurrence rates and symptom severity ratings. Although specific symptoms within each symptom cluster were not identical, 3 very similar symptom clusters (ie, "mood-cognitive" symptom cluster, "sickness-behavior" symptom cluster, "treatment-related" symptom cluster) were identified regardless of whether occurrence rates or severity ratings were used to create the symptom clusters at the end of radiation therapy. However, the factor solution derived using the severity ratings fit the data better. Significant differences in severity scores for all 3 symptom clusters were found between patients with breast and prostate cancer. For all 3 symptom clusters, the patients with breast cancer had higher symptom cluster severity scores than the patients with prostate cancer.

Download full-text


Available from: Kathryn A Lee, Sep 08, 2014
  • Source
    • "While advances in treatment have dramatically improved the rate of survival for women with BC, a large proportion of women undergoing treatment report multiple co-occurring symptoms that can be a significant source of distress [2] [3]. Research has shown that these multiple co-occurring symptoms, or symptom clusters, can have a profound negative impact on quality of life [4] [5]. Specifically , symptoms of fatigue, depression, sleep disturbances , and pain are prevalent across stages of disease and BC treatment [6]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: To examine how symptom cluster subgroups defined by extreme discordant composite scores, cut-off scores, or a median split influence statistical associations with peripheral cytokine levels in women with breast cancer. Systemic cytokine dysregulation has been posited as a potential biological mechanism underlying symptom clusters in women with breast cancer. Symptom characteristics may play an important role in identifying cytokines of significant etiological importance, however, there is no consensus regarding the ideal subgrouping technique to use. A secondary analysis of data collected from a cross-sectional descriptive study of women with stage I-II breast cancer was used to examine and compare the relationships between peripheral cytokine levels and symptom subgroups defined by extreme discordant composite scores, cut-off scores, or a median split. Participant symptom scores were transformed into a composite score to account for variability in symptom intensity, frequency and interference. Cytokine levels in subgroups defined by composite scores within the highest and lowest 20% were contrasted with those composed from cut-off scores and a median split. Subgroups defined by the composite score or cut-off scores resulted in similar statistical relationships with cytokine levels in contrast to the median split technique. The use of a median split for evaluating relationships between symptoms clusters and cytokine levels may increase the risk of a type I error. Composite and cut-off scores represent best techniques for defining symptom cluster subgroups in women with breast cancer. Using a consistent approach to defining symptom clusters across studies may assist in identifying relevant biological mechanisms.
    Full-text · Article · Oct 2013 · Advances in Breast Cancer Research
  • [Show abstract] [Hide abstract]
    ABSTRACT: Clinical experience suggests that many symptoms occur together. In this paper, we examine the rationale and evidence base for symptom clusters in different medical fields, particularly the cluster phenomenon in cancer. Cancer symptom clusters are a reality. Various symptoms that cluster clinically have also been verified statistically. Specific clusters such as nausea-vomiting, anxiety-depression, and cough-dyspnea are evident on both clinical observation and in research investigation. Fatigue-pain and fatigue-insomnia-pain have also been demonstrated statistically as clusters. Another proposed cluster 'depression-fatigue-pain' seems relevant to clinical practice. Other clusters may serve only as theoretical models that illustrate possible common biological etiologies in cancer; they need to be validated in future research. Analysis of the literature is complicated by considerable inconsistencies across studies. Discrepancies between clinically defined and statistically obtained clusters raise important questions. We must consider the analytical techniques used, and how methodology might influence cluster occurrence and composition. Further research is warranted to establish universally accepted statistical methods and assessment tools for symptom cluster research.
    No preview · Article · Jun 2010 · Palliative Medicine
  • [Show abstract] [Hide abstract]
    ABSTRACT: To provide an integrative review of the literature on the science of symptom clusters in patients with cancer and establish implications for future studies. Sixty-one articles about cancer symptom clusters were selected for review from results of a search in MEDLINE, CINAHL, PsycINFO, Sociological Abstracts and Cochrane databases from 1950 to 2010. This review discusses the current research on the definitions, theoretical frameworks, measurements, outcomes, and interventions of symptom clusters in oncology. Although symptom clusters were identified as groups of several related and coexisted symptoms, researchers had different opinion on the least number of and relationships among symptoms in a cluster. Four theoretical frameworks were used, but none of them were specific to guide research in symptom clusters for general cancer population. Most-common symptom approach and all-possible symptom approach had their own characteristics and methods for cluster identification. Functional status and quality of life were major outcomes that were negatively associated with the number or severity of symptom clusters. Interventions with multiple or central symptoms in clusters were two potential ways to improve patients' symptom experience. Despite advances in understanding of symptom clusters, further research is needed to define clusters operationally, and to develop appropriate theoretical frameworks. Methods of cluster identification need further comparison to see which offers the best understanding of symptom clusters. More studies with cross-sectional or longitudinal designs are necessary to explore influences of symptom clusters on patient outcomes, and interventions on symptom clusters.
    No preview · Article · Dec 2010 · European journal of oncology nursing: the official journal of European Oncology Nursing Society
Show more