Treatment-related symptom clusters in breast cancer: a secondary analysis

This study investigated treatment-related symptom clusters and the influence of selected demographic/clinical variables on symptom clustering in breast cancer patients across a treatment trajectory. A secondary analysis of 282 breast cancer patients receiving chemotherapy or radiotherapy was done to determine the clustering of oncologic treatment-related symptoms at selected time points of treatment. Two distinct clusters were identified: a psychoneurological cluster and an upper gastrointestinal cluster. The clustering of symptoms was generally stable across the treatment trajectory. The clustering, however, was weaker when the time lapse after the completion of treatment became longer. Demographic and clinical variables did not significantly influence symptom clustering. Psychoneurological symptoms had a tendency to occur together across the treatment trajectory, as did upper gastrointestinal symptoms. Effective symptom assessment/management strategies need to take into account this co-occurrence of symptoms. The findings from this study underscore the need for further investigation of the common biological basis of symptoms to attain more effective management of multiple symptoms.     

Mexican Americans' diabetes symptom prevalence,burden, and clusters

AimsType 2 diabetes mellitus (T2DM), serious and increasingly prevalent among Mexican Americans, produces symptoms related to high and low glucose levels, medication side effects, and long-term complications. This secondary analysis explored symptom prevalence, differences among symptom burden levels, and how symptoms clustered.MethodsClinical measurements and survey data (demographic, quality of life, and the symptom subscale of the Diabetes Symptom Self-Management Inventory) collected from Mexican American adults with T2DM (n = 71) were analyzed for symptom prevalence, differences across levels of symptom burden, and symptom clusters. Agglomerative hierarchical and k-means clustering analyses were performed on a Gower matrix. Internal validation methods and rank aggregation were used to identify the best clustering method of the two techniques and to identify symptoms that clustered together.ResultsParticipants reported mean = 14 symptoms; tiredness and trouble sleeping were most prevalent. People with high symptom burden had significantly lower quality of life and perceptions of worse diabetes severity. Hierarchical clustering produced three symptom clusters: cluster 1 = 9 symptoms (e.g. intense thirstiness, dry mouth); cluster 2 = 9 symptoms (e.g., itching skin, weight gain, noise or light sensitivity); cluster 3 = 13 symptoms (e.g., nervous, headache, trouble concentrating, and memory loss).ConclusionMexican Americans with T2DM report several co-occurring symptoms. Quality of life is significantly worse for people with high symptom burden. Three distinct symptom clusters were identified. Studies with larger samples are needed to further diabetes symptom science. Clinicians should assess and address patients' co-occurring symptoms as a potential means of decreasing symptom burden and improving quality of life.     

Symptom clusters in advanced illness

OBJECTIVES: To review the four sets of symptom clusters commonly seen in patients with advanced illness, and their definitions, associated symptomatology, and management. DATA SOURCES: Research and review articles and textbooks. CONCLUSION: Symptoms of patients with advanced illness tend to occur not isolation, but in symptom clusters. The ability to cluster symptoms in both assessment and management reduces the use of polypharmacy, systemic toxicities, and improves the patient's quality of life. IMPLICATIONS FOR NURSING PRACTICE: It is important that the nurse providing symptom management for the oncology patient understand the importance of clustering certain symptoms together.     

The identification of multiple symptom clusters and their effects on functional performance in cancer patients

Aims and objectives. To identify cancer-related symptom clusters, to explore their inter-relationships and to examine the effects of single symptoms and the synergistic effects of symptom clusters on functional performance using path analysis by structural equation modelling in patients with various types of cancer. Background. Recent studies suggest that cancer patients frequently experience three or more concurrent related symptoms and that this clustering of symptoms is likely to have negative synergistic impacts on outcomes, because of the complicated dynamics of clusters. Design. A cross-sectional design. Methods. One hundred and ten patients with various types of cancer were recruited as in- and out-patients at a University Hospital in Incheon, South Korea. Data collection was performed using a questionnaire and by direct interview. Pain, insomnia, fatigue, depression and functional performance were measured. Results. The developed model was composed of antecedents, symptom clusters and outcomes. Of the symptoms often encountered as clusters in cancer patients, insomnia, depression and fatigue were found to have significant single (direct) effects on functional performance. Seven symptom clusters were identified between pain and functional performance, three between insomnia and functional performance and one between depression and functional performance. These single symptoms and symptom clusters were found to have significant synergistic effects on functional performance and to explain 24% of functional performance variance. Conclusions. Multiple cancer-related symptom clusters may occur and the dynamics within symptom clusters is complicated. Our findings provide sound evidence regarding the importance of assessing and managing clusters of symptoms simultaneously rather than focusing on single symptoms. Relevance to clinical practice. A comprehensive understanding of symptom clusters in cancer patients would help establish valid diagnostic symptom cluster entities and aid the development of subjective/objective phenotypic criteria for symptom cluster based diagnoses and of nursing care protocols for managing symptom clusters.     

Symptom clusters in chronic obstructive pulmonary disease: A systematic review

AimTo conduct a comprehensive literature review to identify symptom clusters commonly present in Chronic obstructive pulmonary disease (COPD) patients.BackgroundCOPD is the fourth leading cause of death worldwide. Substantial research has been studied regarding single symptoms that burden patients with this disease and the profound impacts that these symptoms can have on physical and psychological health. However, these symptoms rarely occur in isolation and limited research has been conducted identifying clinically significant relationships or clusters of symptoms associated with COPD afflicted patients.MethodsPubMed, Web of Science, and Embase databases were used to identify potential articles limited to records published between 2005 and 2018 with human-conducted trials on adults with COPD, examining symptom clusters in this population. Only 5 studies met inclusion criteria.ResultsAcross the five studies, 596 participants were included with a mean age of 70.49. Two themes emerged including psychological symptom clusters and respiratory-related symptom clusters. Anxiety-related symptoms appeared to be a common theme among psychological symptom clusters and varied greatly based on instrument selection. Inconsistent results were found in respiratory-related symptom clusters, but included difficulty breathing as a common symptom component. Only one study examined for stability of symptoms over time.ConclusionThere were inconsistent results across all studies which may be contributed to the heterogeneity amongst patients, instruments administered, and statistical approach. Future research should be conducted to further elucidate COPD related symptom clusters, their effects on somatic and cognitive health, and the stability of these symptom clusters over time.     

Symptom clustering in hospitalised older palliative cancer patients: A cross-sectional study

BackgroundAccurate detection of symptoms is essential in palliative care. Identification of clustering of symptom is valuable to develop target interventions. This area is largely understudied in older palliative cancer patients.ObjectivesTo identify symptom clustering in older palliative cancer patients, and patient groups based on the clustering of symptoms, and to evaluate the difference in functional dependence and experiencing life as not meaningful between the identified patient groups.DesignA cross-sectional study.SettingGeriatric and non-geriatric wards of seven acute care hospitals.Participants400 palliative cancer patients aged 65 years and older.MethodsSymptoms were collected using a validated instrument which assesses physical, psychological, functional, social, and existential symptoms by means of a structured interview with a researcher. An agglomerative hierarchical clustering analysis was used to analyse the data.ResultsThe cluster analysis revealed five groups of symptoms: (1) urological and gastrointestinal symptoms, and their treatment complications, (2) psychological and existential symptoms, (3) pain, constipation, sleeplessness and airway problems, (4) functionality problems, and (5) fatigue-related symptoms. Three patient groups were identified: (1) symptom-free group, (2) physical discomfort group, and (3) physical and psychological discomfort group. In the last group, significant more patients had a geriatric risk profile and less of them received chemotherapy. Patients in this group were more often functionally dependent and experienced their life as not meaningful.ConclusionFive groups of symptoms were identified. Three patient groups were identified which reported different levels of functionality and experiencing life as meaningful. Healthcare professionals should be triggered to detect symptom clusters and be alert to the presence of the other symptoms in the cluster when identifying one symptom. They should also be alert to patients with a geriatric risk profile because of their higher risk of experiencing physical and psychological symptoms and the influence these symptoms have on being functionally dependent and experiencing life as not meaningful.     

The state of science in the study of cancer symptom clusters

PurposeTo provide an integrative review of the literature on the science of symptom clusters in patients with cancer and establish implications for future studies.MethodsSixty-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.ResultsThis 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.ConclusionsDespite 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.     

Significance of Symptom Clustering in Palliative Care of Advanced Cancer Patients

Patients with advanced cancer often experience multiple concurrent symptoms. To explore this symptom clustering and its associated parameters, we prospectively surveyed 427 consecutive patients on admission to the Palliative Care Unit. There were 222 males (52.0%) and 205 females (48.0%), with a median age of 66 years (range: 27–93 years). The main tumor sites were lung (19.9%), liver (18.0%), and colorectum (11.0%). The median survival was 13 days (1–418 days). Symptoms were assessed using a face-valid Symptom Reporting Form. We identified five symptom clusters by exploratory factor analysis. Clusters were named “loss of energy,” “poor intake,” “autonomic dysfunction,” “aerodigestive impairment,” and “pain complex.” We used nonhierarchical cluster analysis to divide the 394 patients with complete data into six groups. Each group was characterized by a particular pattern that was composed of different symptom clusters. Survival, functional performance, bone metastasis, and fluid accumulation were significantly associated with symptom clustering in six groups of patients. The severity of psychological distress also related to their physical deterioration. These data suggest that different underlying mechanisms associate with symptom clustering. Further elucidation of these processes may assist in symptom management.     

Symptom Clusters and Quality of Life in Patients With Breast Cancer Receiving Endocrine Therapy in China

ObjectivesBreast cancer patients undergoing endocrine therapy experience various symptoms that have long-term effects on their quality of life. However, which symptom clusters are expressed and affect patients’ quality of life remain significantly controversial. Therefore, we aimed to explore symptom clusters among breast cancer patients receiving endocrine therapy and identify the impact of these clusters on their quality of life.Data SourcesThis secondary analysis of data from a cross-sectional study aimed to explore the symptom experiences and quality of life of breast cancer patients receiving endocrine therapy. The participants were invited to complete the Functional Assessment of Cancer Therapy–Breast (FACT-B) and Endocrine Subscale (ES). Principal component analysis, Spearman correlation analyses, and multiple linear regression were used to explore symptom clusters and identify their influence on quality of life.ConclusionData from 613 participants were obtained, and 19 symptoms were included in the principal component analysis, which identified five symptom clusters: the systemic, pain and emotional, sexual, vaginal, and vasomotor symptom clusters. Adjustment for covariates revealed that the systemic and pain and emotional symptom clusters were negative predictors of quality of life. The fitted model explained approximately 38.1% of the variance.Implications for Nursing PracticeThis study demonstrated that breast cancer patients receiving endocrine therapy experienced symptoms that tended to occur in five clusters (i.e., systemic, pain and emotional, sexual, vaginal, and vasomotor symptoms). Developing interventions for the systemic and pain and emotional symptom clusters may effectively improve patients’ quality of life.