Symptom clusters are a research priority, because clusters have a greater adverse impact on outcomes than individual symptoms. Interest is stimulated by the possibility of targeting a single intervention to manage multiple symptoms with a common mechanism. The symptom cluster concept suggests that co-occuring symptoms may not be independent entities but interact with each other and group together in a systematic way. A key interest is the complex interrelationships among multiple concurrent symptoms and their causal mechanisms. The identification of clusters could lead to more effective symptom assessment and better cancer management strategies.
Historically, clinicians and researchers acknowledged the presence of multiple symptoms; however, the focus of most research has been on single symptoms. In 2001, Dodd et al. suggested that symptom clusters may have common underlying mechanisms, and proposed that study of clusters could advance cancer symptom management. Research about symptom clusters in supportive and palliative care has rapidly increased since Kim et al. published the concept analysis in 2005. The science of symptom management has thus evolved from a focus on single symptoms to the exploration of symptom clusters.
In this article, we will discuss the current research on conceptual and methodological issues associated with definitions, symptom interrelationships, and outcomes of cancer symptom clusters. We will also comment on the experience of symptom clusters from the patient perspective and explore their clinical implications. Sixteen articles published in 2011 and 2012 were selected for this review. They demonstrated different cluster concepts or introduced new approaches to cluster identification. Theoretical articles were also included as they contribute to a new era of symptom cluster science.
RATIONALE OF SYMPTOM CLUSTER RESEARCH IN CANCER
The symptom cluster concept is not unique to cancer symptom management. Prior to the 20th century, most diseases were diagnosed on the basis of signs and symptoms. After the 20th century, the diagnostic function for symptom clusters has been accepted. For example, cluster methods are used for diagnosis and classification in psychology and psychiatry (e.g., major depression) . Others have used symptom clusters to explore the pathophysiology of syndromes in general medicine (e.g., fibromyalgia, inflammatory bowel syndrome). Some evidence suggests that recognition of specific clusters across the illness continuum could improve treatment outcomes. For example, better recognition of clusters in congestive heart failure might decrease delay in interventions and prevent hospitalization .
Although clusters have been useful to establish diagnostic criteria for many nonmalignant diseases, in oncology the cause of symptoms is more complex because symptoms may arise from the disease, treatment, or other symptoms . Symptom burden for individuals with cancer is also more extensive. A systematic review of 18 studies showed that 30% of patients experienced more than five concurrent symptoms . When multiple concurrent symptoms were observed concurrently, an individual's distress was magnified.
A symptom cluster was defined initially as three or more concurrent symptoms related to each other but which may or may not have a common cause . The definition was later revised so that only two or more related symptoms co-occur and form a stable group and are relatively independent of other clusters . Controversy remains about the minimum number of symptoms for a cluster [7,8]. Both two-symptom [9▪] and three-symptom criterion [10▪▪] has been used to define clusters. Certain symptom pairs have statistical validity across several studies and also clinical relevance. For example, clinically evident symptom pairs of ‘fatigue–drowsiness’ [11–14], ‘anxiety–depression’ [11,14,15], ‘nausea–vomiting’ [16,17], ‘constipation–pain’ [18▪], and ‘cough–dyspnea’  have also been demonstrated statistically as clusters. A study applied four separate analytical techniques to determine consistent clusters in prostate cancer . Emotional distress and fatigue occurred together prominently across all analytical techniques. These two symptoms could represent a cluster in the two-symptom definition. This would not have met the definition if the three-symptom criterion has been applied. ‘Fatigue–pain’ and ‘edema–confusion’ were correlated with poor performance status  and shorter survival [18▪] in cancer, respectively, which supports two-symptom definition. Clinically, it is prudent to view symptom pairs as a cluster in which they interact synergistically in predicting outcomes. Therefore, the definition of a symptom cluster should be broadened to include symptom pairs.
A potential explanation for the variable number of symptoms in a cluster could be differences in the number and type of symptoms measured and statistical methodologies . A review of symptom clusters in lung cancer  determined that the number of symptoms in a cluster ranged from two to 11. In a recent study [23▪▪], exploratory factor analysis (EFA) revealed that clusters comprised six to 14 symptoms, suggesting that there may be no upper limit on the number of symptoms in a cluster. This makes clusters difficult to define and compare, and complicates interpretation of their clinical utility in symptom assessment.
Unreported symptoms may also bias our view of the cancer symptom experience and challenge the validity and reliability of current cluster studies. A recent review [24▪▪] of cluster studies examined gastrointestinal (GI) symptom representation within clusters in cancer patients receiving chemotherapy. Forty-two GI clusters were identified in 22 studies. GI clusters were identified in different samples, but with varied composition (e.g., ‘nausea–vomiting’, ‘nausea–vomiting–anorexia’, ‘nausea–anorexia–constipation’). It has been suggested that cluster type and composition might be influenced by the symptom assessment instrument. Difficulty swallowing, early satiety, and mouth sores are common in patients receiving chemotherapy, but infrequently included in symptom assessment instruments. For example, M.D. Anderson Symptom Inventory and Edmonton Symptom Assessment System measured four and two GI symptoms, respectively. Memorial Symptom Assessment Scale (MSAS) and comprehensive checklist measured 10 and 13 GI symptoms, respectively. The authors concluded that studies that measured more GI symptoms using MSAS and comprehensive checklist identified clusters with a broader representation of GI symptoms as would be expected. The findings of this study strongly suggest that comprehensive assessment tools should include all symptoms likely to be experienced in the population of interest.
In animal models, the role of pro-inflammatory cytokines in ‘sickness behavior syndrome’ (fatigue, decreased appetite, sleep disorders, depression) has been well established. Similarities in the symptom profile of sickness behavior and the psychoneurological cluster (i.e., cognitive disturbance, depression, fatigue, insomnia, pain) in cancer lend support to the idea that a common cytokine-based neuroimmunologic mechanism may underlie the psychoneurological cluster [25▪▪]. A recent secondary data analysis [26▪] from a study of 93 women receiving radiotherapy for breast cancer, determined three distinct clusters: ‘fatigue–insomnia–pain’ (FIP), ‘cognitive disturbance–outlook’, and GI. The hypothesized cluster model was verified using confirmatory factor analysis. This result adds validity to previous results identifying the psychoneurological symptom cluster in various cancer populations [27–29].
The common mechanism underlying the psychoneurological symptom cluster is proposed to be inflammatory cytokines for example, interleukin-6 (IL-6), tumor necrosis factor-α (TNF- α), interleukin-1β (IL-1β) which are elevated in cancer as a result of disease or antitumor treatments. The cytokine hypothesis is further supported by findings of two recent clinical studies. Higher levels of C-reactive protein (CRP), IL-6, TNF-α, IL-1β were observed in women receiving chemotherapy for breast cancer . A cross-sectional observational study  in advanced breast cancer (N = 104), investigated the relationships between the ‘depression–fatigue–pain’ (DFP) cluster and hormones of the hypothalamic–pituitary–adrenal (HPA) axis and sympathetic nervous system (SNS). HPA activation was indicated by plasma levels of cortisol and adrenocorticotropic hormone (ACTH), and SNS activation was indicated by plasma epinephrine and norepinephrine. Structural equation modeling (SEM) testing whether hormone levels predicted the shared variance among the DFP cluster demonstrated good fit to the data. Latent variable analysis revealed that elevated neuroendocrine hormone levels predicted the DFP cluster. A review article  also suggested that disruption in HPA axis function may be a common biological pathway underlying a DFP cluster.
Two recent studies examined the association between a DFP cluster and inflammation with somewhat different results. Laird et al.[33▪] investigated a DFP cluster in 436 advanced cancer patients with cachexia. Posthoc cluster analysis identified eight patient cluster groups based on symptom occurrence. The presence of a DFP cluster was associated with reduced physical function, but not with systemic inflammation (as measured by CRP). The second study  investigated the impact of a DFP cluster on survival in hepatobiliary cancer (HBC). Cluster analysis identified three patient cluster groups based on symptom frequency and severity. High levels of DFP were associated with elevated eosinophil levels (as a surrogate measure of inflammation) at 3-month and 6-month follow-ups. Cox regression analysis revealed some disease (i.e., vascular invasion of the tumor, eosinophil levels) and patient-related (i.e., age) predictors of poor survival in HBC. Symptom clusters did not mediate the relationship between eosinophil levels and survival. The investigators concluded that a common underlying immunological mechanism for the DFP cluster might be disease progression (i.e., tumor-associated tissue eosinophilia); however, this has not been replicated across different primary cancer sites. These two studies identified clusters using only the most common symptoms from earlier reports. This approach limits the ability to accurately define a symptom cluster. Furthermore, patients (rather than symptoms) were clustered. Although the theoretical model is intriguing, there is a need for more clinical evidence in humans to validate a common biologic link for the DFP cluster. To confirm the role of cytokines, future studies need to include a wide range of cancer diagnoses and adopt longitudinal prospective studies [25▪▪].
An alternative methodology for identification of symptom clusters is provided by qualitative studies of the symptom experience. There are three studies [35,36,37▪] available which used a qualitative approach to cancer symptom clusters. One  explored symptoms associated with chemotherapy-related nausea in cancer patients using content analysis based on participants’ narratives. The study provided preliminary evidence to support a cluster of ‘nausea–vomiting–feeling bloated–anorexia–taste changes–intolerance of smells’ in a sample of patients with various cancers who had experienced nausea during their chemotherapy. The second  reported a respiratory cluster of ‘breathlessness–cough-fatigue’ in advanced lung cancer. The cluster was associated with other symptoms, including anxiety, depression, and sleep problems. These results suggest that there may be complex inter-cluster dynamics. Lopez et al.[37▪] conducted qualitative longitudinal interviews over a 12-month period in gynecological cancer. Several narrative symptom clusters were identified through content analysis: tiredness, sleeplessness, pain, depression, and weakness. Participants differentiated the symptoms of tiredness from weakness. This suggests that fatigue descriptors are not synonymous and may, in fact, describe different dimensions of fatigue . The results of the study suggest that tiredness and weakness should be assessed separately, as they may necessitate different management strategies. Although causal relationships cannot be ascertained from these qualitative studies, they can provide a stronger conceptual basis for identification of symptom clusters. To strengthen the scientific base and advance the cluster research, we need to explore the symptom cluster experience from the perspective of the patient.
The question of whether symptom clusters are stable or change over time is clinically important for prognostication, screening, and treatment [10▪▪]. Cluster stability is difficult to evaluate given the variability of disease and clinical characteristics, treatments, and methods to collect and analyze data. Conceptually, stability may refer to consistent/replicated symptom clusters across different populations and individuals over time [23▪▪]. Longitudinal stability is usually determined by recognizing similar symptom profiles over time. However, it is unclear whether all symptoms in a cluster should present simultaneously . Kirkova and Walsh  suggested that at least 75% of the symptoms within the initial cluster including the most prevalent (the sentinel) symptom must be present over time. Two studies addressed the issue of consistency over time by identifying ‘core’ or defining symptoms within the cluster [19,23▪▪]. In a prospective longitudinal study of 219 cancer outpatients [23▪▪], EFA identified several symptom clusters 1 month (T1), 3 months (T2), and 12 months (T3) after chemotherapy. The study employed a unique analytical approach to examine cluster stability. Separate factor analyses were conducted at each of the three time points. Symptoms that repeated as part of the same cluster across time points were defined as core symptoms. For example, the symptoms comprising the musculoskeletal/lethargy cluster varied at each time point; however, fatigue, weakness, muscle soreness, and feeling heavy were consistent across time points; so these were defined as core symptoms. The study had two important findings: certain clusters (e.g., oral discomfort, GI, aerodigestive) were replicated over time independent of treatment type, primary site, and functional status; and a core set of concurrent symptoms were present consistently within each cluster. The stability of fatigue, insomnia, anorexia, nausea, and vomiting in the GI cluster may suggest an underlying cause of cytokine production similar to the sickness-behavior symptom cluster . This may support the validity of common neuroimmunologic mechanisms .
The second study  involved 143 patients with various cancers and provided 504 symptom assessments throughout the treatment course. Six symptom clusters were identified at the first assessment were maintained across four time points with slight variations. For example, core symptoms of cough and dyspnea in the respiratory clusters, nausea and vomiting in the GI clusters, and weight loss, dysphagia, anorexia, and feeling bloated in the nutritional clusters remained stable. Some symptoms were associated with multiple clusters (i.e., nausea in GI and nutritional clusters). The authors concluded that there was relative stability of the clusters, with some ‘secondary’ symptoms changing over time. These studies [19,23▪▪] are important in the debate. Both studies proposed a refinement in the definition of symptom cluster to involve stability as a necessary aspect. They proposed that consistent clusters are those that have similar core symptoms across times.
There is ongoing research into ‘sentinel’ symptoms within a cluster that could help streamline cluster assessment and management. A sentinel symptom can be defined as an indicator or marker of the presence of a symptom cluster that may lead to the assessment of other relevant symptoms within a particular cluster [10▪▪,42]. There is conflicting evidence that the presence of a sentinel symptom is correlated with a symptom cluster . Brown et al.[10▪▪] identified a cluster of ‘anorexia–cough–dyspnea–fatigue–pain’ in women with lung cancer with all stages after surgery. The five-symptom cluster was experienced by 64% of the women. The presence or absence of the five-symptom cluster was correlated with the occurrence of pain (r = 0.63). The researchers suggested that healthcare providers use the presence of pain as an indicator to further assess women for other symptoms in the cluster. However, the study evaluated only prevalence to define interrelationships between sentinel and nonsentinel symptoms. Symptom severity or distress might alter composition, and thus cluster assessment.
EFFECTS OF CLUSTERS ON OUTCOMES
A recent study [44▪] examined the relationship between symptom clusters and chemotherapy-induced neuropathic pain (CINP) among 40 patients with breast cancer. Using cluster analysis, two patient cluster groups were identified based on the severity of depression, fatigue, insomnia, and pain. One group experienced a high level of all symptoms, whereas another group experienced a low level of all symptoms. The high and low symptom groups were further subdivided on the basis of having or not having CINP. The subgroup with high symptoms went on to develop CINP (22.5%). The low cluster subgroup did not develop CINP (35%). The study has important clinical implications for oncologic and supportive care research. Individuals in the high symptom group could be more susceptive to the development of CINP. Another question that could be addressed in future studies is whether early management of severe symptoms could prevent or reduce the severity of CINP.
Oh et al.[9▪] proposed that multiple clusters had a synergistic effect in predicting functional performance. The study involved 110 patients with various cancers. Direct and indirect associations between functional performance and depression, fatigue, insomnia, and pain were assessed using path analysis by SEM. Other than pain, each symptom individually had a direct effect on functional status. Depression also had an indirect effect on functional performance via fatigue (’depression–fatigue’ cluster). Other indirect effects were determined through many paths (clusters), for example, the indirect effect of pain on functional performance occurred via seven paths: ‘pain–insomnia–fatigue’, ‘pain–depression–fatigue’, ‘pain–insomnia–depression–fatigue’ and so on. The overall effect of multiple clusters on functional performance was also significant. The study suggested ‘sickness behavior’ to be a possible common biologic link between depression, fatigue, insomnia, and pain. Although contextually appropriate, the methodology for symptom cluster identification in this study suffers from limited number of symptoms assessed . Furthermore, all single effects of symptoms and the synergistic effects of clusters explained a small amount of variance (24%) in functional performance.
Little is known about the possible prognostic role of symptom clusters on cancer survival. Two studies [16,18▪] investigated the relationship between symptom clusters and survival in advanced cancer. The first study  identified four clusters in 437 patients: neuropsychological (sleep problems, depression, anxiety), anorexia–cachexia (anorexia, tiredness, weight loss), confusional (confusion, agitation, urinary incontinence), and GI (nausea, vomiting). An important finding was the significant association between length of survival and the number of symptoms within a cluster. For example, individuals who experienced all three symptoms of a neuropsychological cluster had shorter survival than those who had only two symptoms (21 vs 35 days, respectively). This suggests that anxiety, depression, and insomnia should be assessed and followed up together. The second study [18▪] explored seven clusters in 922 patients. Three of the seven clusters were found to be predictors of shorter survival: fatigue/anorexia–cachexia (easy fatigue, lack of energy, weakness, dry mouth, anorexia, early satiety, taste change, weight loss), aerodigestive (cough, dyspnea, hoarseness, dysphagia), and debility (edema, confusion). Both studies revealed that survival was shorter as the number of clusters present increased. This supports the concept that symptom burden is associated with cancer survival. The findings of the two studies emphasize the importance of measurement of symptom burden in clinical practice.
This review of recent literature has provided important evidence to the science of symptom clusters. Both qualitative and quantitative evidence suggests that a psychoneurological symptom cluster, similar to sickness behavior in animals, occurs with cytotoxic chemotherapy and advanced disease. This cluster has been associated with poorer functional outcomes, and in one study, individuals with this cluster were found to be more susceptible to the development of chemotherapy-induced neuropathic pain. Two recent studies addressed the problem of cluster stability by identifying ‘core’ and ‘sentinel’ symptoms that endured over time. New evidence has identified symptom pairs as important contributors to functional decline, suggesting that the symptom cluster definition should include pairs as well as multiple symptoms. Finally, investigators are continued that symptom measures should be evaluated for bias to prevent under-representation of symptom clusters.
Future research can be guided by the review presented in this article. Scientists are encouraged to evaluate symptom pairs as well as multiple symptoms as clusters that could negatively impact patient outcomes. New methods are available for the examination of symptom cluster stability over time. Future research on the psychoneurological symptom cluster could be expanded to focus on the underlying bio-behavioral mechanisms in order to advance toward rational strategies for managing this cluster.
I would like to thank Andrea M Barsevick, PhD, RN and Declan Walsh, MD for their support and guidance in the preparation of this review and Barbara Hullihen, BS and Shirley Thomas, MD for their valuable comments. Cleveland Clinic The Harry R. Horvitz Center for Palliative Medicine and Supportive Oncology, Cleveland, Ohio, USA is a WHO Demonstration Project in Palliative Medicine and an ESMO Designated Center of Integrated Oncology and Palliative Care.
Conflicts of interest
There are no conflicts of interest.
REFERENCES AND RECOMMENDED READING
Papers of particular interest, published within the annual period of review, have been highlighted as:
- ▪ of special interest
- ▪▪ of outstanding interest
Additional references related to this topic can also be found in the Current World Literature section in this issue (p. 119).
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