Differences in symptom clusters identified using occurrence rates versus symptom severity ratings in patients at the end of radiation therapy

Differences in symptom clusters based on multidimensional symptom experience and symptom burden in stroke patients

In the study of stroke symptoms, a significant unresolved issue remains: What are the similarities and differences in the use of three symptom dimensions-occurrence, severity, and distress-and symptom burden to identify symptom clusters, and which level is recommended for constructing symptom clusters? This study aimed to identify the number and types of symptom clusters in stroke patients on the basis of these dimensions and to determine the most suitable dimension for extracting symptom clusters. Data were collected from 656 stroke patients via a convenience sampling method at a tertiary-level hospital in Wuhan, China, between August 2023 and March 2024. Exploratory factor analysis was conducted to extract symptom clusters on the basis of the three dimensions of the symptom experience scale and symptom burden. Four similar symptom clusters were identified: the mood disturbance symptom cluster, the physical symptom cluster, the cognitive dysfunction symptom cluster, and the slurred speech and choking cough symptom cluster. The symptom of "fatigue" within the physical symptom cluster was not identified only in the dimension of distress (with a percentage agreement of 83.3%), whereas the symptom composition of other clusters remained consistent across all three symptom dimensions (with a percentage agreement of 100%). Moreover, all four symptom clusters exhibited high consistency in terms of both occurrence and symptom burden, regardless of whether the symptom with the highest factor loading or the overall symptom composition was considered. The use of symptom occurrence and symptom burden is recommended for identifying symptom clusters in stroke patients. Subsequently, trajectory studies of symptom clusters and symptom network analyses should be conducted on the basis of these two dimensions to establish a solid theoretical foundation for future clinical interventions and related scientific research.

Identification of Symptom Profiles in Prostate Cancer Survivors

OBJECTIVES

To identify symptom profiles (e.g., fatigue, sleep disturbance, depression, anxiety, cognitive impairment) among prostate cancer survivors, examine factors associated with the identified symptom profiles, and compare quality-of-life outcomes.

SAMPLE & SETTING

98 prostate cancer survivors who completed primary treatment were enrolled in a randomized parent trial.

METHODS & VARIABLES

Established scales were used to measure symptoms and quality of life. Latent profile analysis was employed to classify patient groups based on symptom experiences. Logistic regression assessed factors associated with symptom profiles.

RESULTS

The mean age of participants was 69 years (SD = 6.8). A high-symptom group (n = 29) and a low-symptom group (n = 69) were identified. Higher perceived stress (odds ratio [OR] = 1.28; p = 0.006), poorer spiritual well-being (OR = 0.84; p = 0.006), and lower household income (OR = 0.12; p = 0.089) were associated with being classified into the high-symptom group. Patients in the high-symptom group reported worse quality of life across all domains (p < 0.05).

IMPLICATIONS FOR NURSING

Prostate cancer survivors experience varying degrees of symptom severity. Understanding the symptom profiles and associated factors can inform nurses about patients in need of symptom management and targeted interventions.

Intolerance of Uncertainty and Its Association With Cancer-Related Symptoms: A Scoping Review

BACKGROUND

Cancer-related symptoms have negative impacts on the health outcomes of adults with cancer. Thus, it is critical to identify who might be at risk. Intolerance of uncertainty (IU) could be the major contributor for cancer-related symptoms; however, this relationship is understudied in the context of cancer.

OBJECTIVE

The purpose of this scoping review was to map the literature that has investigated IU and its link to cancer-related symptoms.

METHODS

This scoping review used the framework proposed by Arksey and O'Malley and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). A comprehensive search was conducted using 5 databases. English-language primary research published focusing on IU and cancer-related symptoms was included in this review.

RESULTS

Of 12 articles included in this review, 11 studies found a positive relationship of IU with affective symptoms, including anxiety, depression, stress, fear, worry, and distress. Additionally, one study showed that higher IU was associated with greater cognitive impairment and that association was mediated by anxiety.

CONCLUSION

Findings from this scoping review support the positive association between IU and cancer-related symptoms. This review further suggests that IU could be a potential risk factor for cancer-related affective and cognitive symptoms.

IMPLICATION FOR PRACTICE

The incidence of affective and cognitive symptoms in cancer survivors is high. Given that IU is associated with these symptoms, IU-focused treatments may be beneficial in this group.

Body image, illness uncertainty and symptom clusters in surgically treated breast cancer survivors: An exploratory factor analysis and correlational study

PURPOSE

To determine the relationship among body image, illness uncertainty, and symptom clusters in surgically treated breast cancer survivors.

METHODS

A correlational, descriptive study was conducted in a convenience sample of 60 women surgically treated breast cancer survivors recruited in a private hospital and a survivor center. A questionnaire of sociodemographic characteristics, MUIS-C Scale, and QLQ-C30 and Module BR-23 were used. Variable characteristics and associations were analyzed with descriptive statistics and Pearson correlation coefficient, and exploratory factor analysis using unweighted least squares and Promax rotation was used for symptom clustering.

RESULTS

A three-factor structure was found: an anxiety symptom cluster, a breast symptom cluster, and an arm symptoms, depression, and fatigue symptom cluster, explaining 46,47% of the variance. Significant correlations were found among body image and illness uncertainty (r = -0,390, p < 0,01), body image and the anxiety symptom cluster (r = 0,613, p < 0,01), illness uncertainty and the anxiety symptom cluster (r = -0,421, p < 0,01), the breast symptom cluster (r = -0,425, p < 0,01), and the arm symptoms - depression - fatigue symptom cluster (r = -0,443, p < 0,01).

CONCLUSION

The relationships among all variables were statistically significant. Nurses providing care to BC survivors need to address the multidimensionality of the symptom experience and its correlates to better assist their patients. Further research is needed to elucidate the biopsychosocial underpinnings of those relationships.

Breast cancer symptom profile longitudinal changes: data mining study

OBJECTIVES

Identifying stable co-occurring symptoms in breast cancer (BC) patients during chemotherapy can improve symptom management and the treatment process. This study examines symptom cluster stability in Iranian BC patients receiving chemotherapy and evaluates stability across three-time points within each cluster.

METHODS

This study collected data from three-time points: initial chemotherapy commencement, 2½ months postdiagnosis, and 5 months postdiagnosis. The research used exploratory factor analysis (EFA) in combination with hierarchical cluster analysis (HCA) and K means clustering to address research questions.

RESULTS

In the initial clustering step, EFA identified five clusters with high consistency across three-time points. The first cluster showed depression, anxiety and irritability, while the second cluster was characterised by sexual interest and pain. The third cluster was associated with diarrhoea and vomiting. In the second step, we obtained the HCA item output and two clusters of K means clustering that recorded depression and anxiety symptoms over time. Vomiting, dry mouth, sexual interest, worrying and numbness were observed during the first and second points, but the frequency has decreased since then.

CONCLUSIONS

Cancer's psychological and physiological symptoms, including depression, anxiety, digestive and hormonal issues, remain stable throughout the disease. Palliative care centres can improve patients' quality of life and treatment process by addressing persistent symptoms.

Fatigue During Cancer-Related Radiotherapy and Associations with Activities, Work Ability and Quality of Life: Paying Attention to Subgroups more Likely to Experience Fatigue

BACKGROUND

Having knowledge of which patients are more likely to experience fatigue during radiotherapy and the relationship between fatigue and health-related quality of life (HRQL) is important to improve identification and care of patients experiencing burdensome fatigue.

OBJECTIVE

To identify subgroups of patients, varying in situational, physiological, and psychological factors, who are more likely to experience fatigue an ordinary week of radiotherapy, and to compare patients experiencing and not experiencing fatigue regarding perceived HRQL and functional performance, that is, daily and physical activity and work ability.

METHODS

Cross-sectional study of 457 patients (52% women) undergoing radiotherapy (38% breast, 32% prostate cancer), using self-reported questionnaire data on fatigue, HRQL and functional performance analyzed using multivariable regression models.

RESULTS

Of the 448 patients who answered the fatigue question, 321 (72%) experienced fatigue. Patients reporting any comorbidity or depressed mood were more likely to experience fatigue, relative risk (RR) 1.56 ([95% confidence interval (CI)] 1.13-2.16) and RR 2.57 (CI 1.73-3.83), respectively. Patients with fatigue reported worse HRQL and performed less physical activity, including daily (P = .003), vigorous (P = .003) and moderate (P = .002) activity. Patients with and without fatigue reported 60% versus 40% sickness absence.

CONCLUSION

Patients with depressed mood or comorbidity were more likely to experience fatigue an ordinary week of radiotherapy than other patients were. Patients experiencing fatigue perceived worse HRQL and performed less daily and physical activity compared to patients not experiencing fatigue. Cancer care practitioners may consider paying extra attention to these subgroups of patients.

Social relationships and their associations with affective symptoms of women with breast cancer: A scoping review

BACKGROUND

Problems in affective and cognitive functioning are among the most common concurrent symptoms that breast cancer patients report. Social relationships may provide some explanations of the clinical variability in affective-cognitive symptoms. Evidence suggests that social relationships (functional and structural aspects) can be associated with patients' affective-cognitive symptoms; however, such an association has not been well studied in the context of breast cancer.

PURPOSE

The purpose of this scoping review was to address the following question: What social relationships are associated with affective-cognitive symptoms of women with breast cancer?

METHODS

This scoping review used the framework proposed by Arksey and O'Malley and PRISMA-Sc. Studies published by February 2022 were searched using four databases: MEDLINE (PubMed), Embase (Elsevier), PsycINFO (EBSCOhost), and Web of Science (Clarivate). All retrieved citations were independently screened and eligibility for inclusion was determined by study team members. Extracted data included research aims, design, sample, type and measures of social relationships (functional and structural), and the association between social relationships and affective-cognitive symptoms.

RESULTS

A total of 70 studies were included. Affective symptoms were positively associated with social support, family functioning, quality of relationships, social networks, and social integration, whereas the negative association was found with social constraints.

CONCLUSION

Our findings suggest positive social relationships may mitigate affective symptoms of women with breast cancer. Thus, health care providers need to educate patients about the importance of building solid social relationships and encourage them to participate in a supportive network of friends and family members.

Symptom clusters: Revisiting the concept in nursing care for cancer patients

BACKGROUND

Studies on symptom clusters among cancer patients have been conducted intensively. However, the concept seems not to be well defined, hindering its utilization in clinical practice.

AIM

The aim of this paper is to reconceptualize symptom cluster and discuss areas of future research.

RESULTS

A cluster of symptoms should not be viewed as simply as a group of symptoms appearing together. It should be clinically relevant, and symptom members should be interactive or have a mutual etiology. A cluster is declared as stable if its "quality" or "nature" is remained instead of merely having the same number of symptoms. Importantly, each symptom cluster should have a sentinel symptom. The sentinel symptom could be the one that predicts the presence of the cluster or could be the one that significantly interacts with other symptoms. The search for symptom clusters, which are common among various patient groups, might be helpful in some aspects. However, to better understand them, symptom clusters should be examined in specific populations.

CONCLUSION

The nature of the relationship between symptom members, clinical relevance, sentinel symptom, stability, and prevalence are important features of a symptom cluster. More explorations into these properties by future studies are suggested.

Symptom clusters experienced by breast cancer patients at various treatment stages: A systematic review

Breast cancer patients often experience symptoms that adversely affect their quality of life. It is understood that many of these symptoms tend to cluster together: while they might have different manifestations and occur during different phases of the disease trajectory, the symptoms often have a common aetiology that is a potential target for intervention. Understanding the symptom clusters associated with breast cancer might usefully inform the development of effective care plans for affected patients. The aim of this paper is to provide an updated systematic review of the known symptom clusters among breast cancer patients during and/or after cancer treatment. A search was conducted using five databases for studies reporting symptom clusters among breast cancer patients. The search yielded 32 studies for inclusion. The findings suggest that fatigue-sleep disturbance and psychological symptom cluster (including anxiety, depression, nervousness, irritability, sadness, worry) are the most commonly-reported symptom clusters among breast cancer patients. Further, the composition of symptom clusters tends to change across various stages of cancer treatment. While this review identified some commonalities, the different methodologies used to identify symptom clusters resulted in inconsistencies in symptom cluster identification. It would be useful if future studies could separately examine the symptom clusters that occur in breast cancer patients undergoing a particular treatment type, and use standardised instruments across studies to assess symptoms. The review concludes that further studies could usefully determine the biological pathways associated with various symptom clusters, which would inform the development of effective and efficient symptom management strategies.

Chronic Obstructive Pulmonary Disease Symptom Cluster Composition, Associated Factors, and Methodologies: A Systematic Review

This systematic review details symptom clusters, their compositions, and associated factors and appraises the methodologies of studies that reported symptom clusters in patients with chronic obstructive pulmonary disease (COPD). Ten studies were eligible for inclusion in this study. Four common symptom clusters were identified. Two theoretical frameworks, four statistical methods, and various symptom assessment tools were used to identify symptom clusters. Factors associated with symptom clusters included demographic, clinical, and biological factors. No studies examined the subjective experiences of symptom clusters. Overall, inconsistencies were identified in the composition of symptom clusters across studies. This may be due to variations in study design, assessment tools, and statistical methods. Future studies should attempt to arrive at a common definition, especially that is theoretically derived, for symptom clusters, standardize the criteria for symptoms for inclusion in the clusters, and focus on patients' subjective experience to inform which clusters are clinically relevant.

Exploring the Potential Role of the Gut Microbiome in Chemotherapy-Induced Neurocognitive Disorders and Cardiovascular Toxicity

Chemotherapy, targeting not only malignant but also healthy cells, causes many undesirable side effects in cancer patients. Due to this fact, long-term cancer survivors often suffer from late effects, including cognitive impairment and cardiovascular toxicity. Chemotherapy damages the intestinal mucosa and heavily disrupts the gut ecosystem, leading to gastrointestinal toxicity. Animal models and clinical studies have revealed the associations between intestinal dysbiosis and depression, anxiety, pain, impaired cognitive functions, and cardiovascular diseases. Recently, a possible link between chemotherapy-induced gut microbiota disruption and late effects in cancer survivors has been proposed. In this review, we summarize the current understanding of preclinical and clinical findings regarding the emerging role of the microbiome and the microbiota-gut-brain axis in chemotherapy-related late effects affecting the central nervous system (CNS) and heart functions. Importantly, we provide an overview of clinical trials evaluating the relationship between the gut microbiome and cancer survivorship. Moreover, the beneficial effects of probiotics in experimental models and non-cancer patients with neurocognitive disorders and cardiovascular diseases as well as several studies on microbiota modulations via probiotics or fecal microbiota transplantation in cancer patients are discussed.

Symptoms and factors associated with symptom clusters among older adults with oral and oropharyngeal cancers at diagnosis

OBJECTIVE: Describe differences in pretreatment symptoms and the composition of symptom clusters in older patients with oral and oropharyngeal cancer. METHODS: In this cross-sectional study, quality of life (QoL) assessments for cancer patients (EORCT QLQ-C30 and QLQ-H & N35) were applied to 161 cases of oral and oropharyngeal cancer at the time of enrollment in an outpatient clinic. They were used to evaluate QoL-related symptoms reported by patients, according to their occurrence. To identify symptom clusters, an exploratory factor analysis (EFA) was performed, and the relationships between these clusters and independent variables were assessed with linear regression models. RESULTS: The most prevalent symptoms were pain (52%), worry (48%), and weight loss (44%). Five factors were extracted from the EFA, of which 3 were noteworthy. The dysphagia cluster was common to both cancer sites, although more frequent in oropharyngeal cancer patients, and included symptoms such as difficulty swallowing, pain, and weight loss. The psychological cluster included symptoms related to feeling worried, nervous, and depressed. The asthenia cluster, in addition to being age-related, may represent the advanced stage or progression of the disease. CONCLUSION: The dysphagia cluster loaded the most symptoms and was common to both cancers. In addition to pain (one of the main symptoms of the dysphagia cluster), psychological symptoms were also important in both groups of patients. Adequate and early control of these symptom clusters at diagnosis could favor better management of symptoms during treatment.

Symptom Clusters in Patients With Gastrointestinal Cancers Using Different Dimensions of the Symptom Experience

CONTEXT

Patients with gastrointestinal (GI) cancers undergoing chemotherapy (CTX) experience multiple cooccurring symptoms.

OBJECTIVES

The aim of this study was to describe the occurrence, severity, and distress of 38 symptoms and to identify symptom clusters based on three symptom dimensions (i.e., occurrence, severity, and distress) in patients with GI cancers receiving CTX (n = 399). We compared whether the numbers and types of symptom clusters differed based on the dimension of the symptom experience used to create the clusters.

METHODS

A modified version of the Memorial Symptom Assessment Scale was used to assess the occurrence, severity, and distress of 38 symptoms before the initiation of the patient's next dose of CTX. Exploratory factor analysis was used to determine the symptom clusters.

RESULTS

These patients experienced 13.0 (±7.1) symptoms before their second or third dose of CTX. For all three symptom dimensions, four symptom clusters were identified, namely psychological distress, CTX-related, GI, and weight change. The number and types of symptom clusters were relatively similar using all three symptom dimensions. However, some variability was found in the specific symptoms within each of the clusters.

CONCLUSION

Our findings suggest that patients with GI cancers experience multiple cooccurring symptoms. Consistent with previous studies of patients with a variety of cancer diagnoses, psychological and GI clusters are common. Clinicians need to assess for and tailor interventions for these symptom clusters.

Consensus in Identification and Stability of Symptom Clusters Using Different Symptom Dimensions in Newly Diagnosed Acute Myeloid Leukemia Patients Undergoing Induction Therapy

CONTEXT

An unresolved issue in symptom cluster (SC) research is that the numbers and types of SCs vary based on the multiple dimensions of the experienced symptoms that are used for SC identification.

OBJECTIVE

This study aimed to identify SCs using the ratings of occurrence, severity, and distress in newly diagnosed acute myeloid leukemia (AML) patients at three stages of their induction therapy (i.e., T1, T2, and T3). Then, we evaluated the consensus among the numbers and types of symptoms in each SC identified by multiple dimensions over time.

METHOD

The Chinese version of the Memorial Symptom Assessment Scale was used to evaluate the occurrence, severity, and distress ratings of 32 symptoms in patients newly diagnosed with AML during their induction therapy. Exploratory factor analysis was used for SCs identification.

RESULTS

Using the three dimensions in the AML patients (n = 126), four SCs were identified at T1 and T3 and three SCs were identified at T2. The number of symptoms in individual SCs varied over time, whereas the specific symptoms in SCs remained similar over time. The severity ratings fit the data better than did the ratings of occurrence and distress.

CONCLUSION

These findings provided insights into the most common SCs in AML patients undergoing induction therapy by multidimensional evaluation and could lay the foundation for future targeted symptom interventions. Further studies are needed to explore the mechanisms of SCs in AML patients undergoing the chemotherapy.

The Effect of the Pain Symptom Cluster on Performance in Women Diagnosed with Advanced Breast Cancer: The Mediating Role of the Psychoneurological Symptom Cluster

BACKGROUND

Pain, depression, anxiety, sleep disturbances, and constipation were reported in different symptom clusters at different stages of breast cancer. Managing symptom clusters rather than individual symptoms can improve performance status.

AIM

The study examined the effect of pain symptom cluster (pain and constipation) on performance when mediated by the psychoneurological symptom cluster (depression, anxiety, and sleep disturbances) using age as a moderator.

DESIGN

A secondary analysis.

SETTINGS

Palliative care center at a tertiary medical center in northeast Ohio.

PARTICIPANTS

Eighty-six women diagnosed with advanced breast cancer.

METHOD

A quantitative cross-sectional approach.

RESULTS

Ordinal logistic regression showed that pain symptom cluster did not have a significant mediation effect on performance. Odds ratio indicated that subjects with pain symptom cluster were 63% more likely to be bedridden (odds ratio = 1.63, confidence interval = .69-3.84). Women who reported pain symptom cluster were 5% more likely to have psychoneurological symptom cluster (odds ratio = 1.05, confidence interval = .400-2.774). Stratified analysis of age showed no differences in performance. Post-hoc analysis showed that the components of pain symptom cluster had a significant effect on psychoneurological symptom cluster (odds ratio: 3 [1.18-7.62]).

CONCLUSIONS

Pain, constipation, depression, anxiety, and sleep disturbances were highly prevalent in women with advanced breast cancer. However, they tended to cluster in different symptom clusters. Although some findings were not significant, they all supported the direction of the tested hypotheses. Variations in symptom clusters research, including methodology, instruments, statistical tests, and chosen symptom cluster correlation coefficient, should be addressed.

Cluster Analysis of Symptoms of Bangladeshi Women with Breast Cancer

Background:

Breast cancer (BC) patients may experience multiple symptoms due to the disease itself, cancer treatment or combination of both.

Aim:

The aim of the present study was to express multiple symptoms experienced by the patients with BC as clusters.

Methods:

This was a retrospective study. We examined symptom profiles of 120 patients with BC who attended the Centre for Palliative Care, Bangabandhu Sheikh Mujib Medical University in Dhaka, Bangladesh, from January 2009 to December 2013. We included all case sheets of BC patients, which had documentation of needed information. Following symptoms were analyzed: pain, nausea, loss of appetite, constipation, weakness, cough, breathlessness, sleeplessness, lymphedema, sadness, anxiety, and depression. Hierarchical cluster analysis was used to identify the natural groupings within the set.

Results:

We could identify three clusters, namely (1) “neuropsychiatric,” (2) “gastro-respiratory,” and (3) “miscellaneous” symptom clusters. The symptoms in cluster 2 comprised of cough, breathlessness, nausea, and constipation. Cluster 1 was characterized by pain, depression, anxiety, weakness, sleeplessness, and loss of appetite. Cluster 2 was comprised of cough, breathlessness, nausea, and constipation. Cluster 3 consisted of two symptoms lymphedema and sadness. The results revealed that the multiple symptoms of patients with BC experienced had been clustered together. Neuropsychiatric symptoms and weakness formed a significant strong relationship with each other.

Conclusion:

Knowledge obtained from this study could be beneficial for better understanding, assessment, and management of symptom clusters in women with BC. It may also help patients to plan ahead for them to seek management of concurrent symptoms to improve their quality of life.

Stability of Symptom Clusters in Patients With Breast Cancer Receiving Chemotherapy

CONTEXT

Patients with breast cancer who undergo chemotherapy (CTX) experience between 10 and 32 concurrent symptoms. An evaluation of how these symptoms cluster together and how these symptom clusters change over time may provide insights into how to treat these multiple co-occurring symptoms.

OBJECTIVES

The purposes of this study were to determine the occurrence rates and severity ratings for 38 common symptoms, evaluate for differences in the number and types of symptom clusters, and evaluate for changes over time in these symptom clusters (i.e., before CTX, the week after CTX, and two weeks after CTX).

METHODS

At each of the assessments, a modified version of the Memorial Symptom Assessment Scale was used to assess the occurrence and severity of the 38 symptoms. Exploratory factor analyses were used to extract the symptom clusters.

RESULTS

Although across the two symptom dimensions (i.e., occurrence and severity) and the three assessments, eight distinct symptom clusters were identified, only five were relatively stable across both dimensions and across time (i.e., psychological, hormonal, nutritional, gastrointestinal, and epithelial). Two of the additional clusters varied by time but not by symptom dimension (i.e., sickness behavior and weight change). The CTX neuropathy cluster was identified only at the assessment performed in the week after CTX.

CONCLUSION

These findings provide insights into the most common symptom clusters in patients undergoing CTX for breast cancer. In addition, the most common symptoms within each cluster appear to be relatively stable across the two dimensions, as well as across time.

Differences in symptom clusters before and twelve months after breast cancer surgery

PURPOSE

Given the inter-relatedness among symptoms, research efforts are focused on an evaluation of symptom clusters. The purposes of this study were to evaluate for differences in the number and types of menopausal-related symptom clusters assessed prior to and at 12-months after surgery using ratings of occurrence and severity and to evaluate for changes in these symptom clusters over time.

METHODS

Prior to and at 12 months after surgery, 392 women with breast cancer completed the Menopausal Symptoms Scale. Exploratory factor analyses were used to identify the symptom clusters.

RESULTS

Of the 392 women evaluated, the mean number of symptoms (out of 46) was 13.2 (±8.5) at enrollment and 10.9 (±8.2) at 12 months after surgery. Using occurrence and severity, three symptom clusters were identified prior to surgery. Five symptom clusters were identified at 12 months following surgery. Two symptom clusters (i.e., pain/discomfort and hormonal) were relatively stable across both dimensions and time points. Two symptom clusters were relatively stable across both dimensions either prior to surgery (i.e., sleep/psychological/cognitive) or at 12 months after surgery (i.e., sleep). The other four clusters (i.e., irritability, psychological/cognitive, cognitive, psychological) were identified at one time point using a single dimension.

CONCLUSIONS

While some menopausal-related symptom clusters were consistent across time and dimensions, the majority of symptoms clustered together differently depending on whether they were evaluated prior to or at 12 months after breast cancer surgery. An increased understanding of how symptom clusters change over time may assist clinicians to focus their symptom assessments and management strategies.

Differences in Symptom Clusters Identified Using Ratings of Symptom Occurrence vs. Severity in Lung Cancer Patients Receiving Chemotherapy

CONTEXT

An important question in symptom clusters research is whether the number and types of symptom clusters vary based on the specific dimension of the symptom experience used to create the clusters.

OBJECTIVES

Given that lung cancer patients undergoing chemotherapy (CTX) report an average of 14 co-occurring symptoms and studies of symptom clusters in these patients are limited, the purpose of this study, in lung cancer patients undergoing CTX (n = 145), was to identify whether the number and types of symptom clusters differed based on whether symptom occurrence rates or symptom severity ratings were used to create the clusters.

METHODS

A modified version of the Memorial Symptom Assessment Scale was used to assess for the occurrence and severity of 38 symptoms, one week after the administration of CTX. Exploratory factor analysis was used to extract the symptom clusters.

RESULTS

Both the number and types of symptom clusters were relatively similar using symptom occurrence rates or symptom severity ratings. Five symptom clusters were identified using both symptom occurrence rates and severity ratings (i.e., sickness behavior, lung cancer specific, psychological, nutritional, and epithelial). Across these two dimensions, the specific symptoms within each of the symptom clusters were relatively similar.

CONCLUSIONS

Identification of symptom clusters in patients with lung cancer may assist with the development of more targeted symptom management interventions. Future studies are warranted to determine if symptom clusters change over a cycle of CTX in patients with lung cancer.

Differences in symptom clusters identified using symptom occurrence rates versus severity ratings in patients with breast cancer undergoing chemotherapy

PURPOSE

One of the unanswered questions in symptom clusters research is whether the number and types of symptom clusters vary based on the dimension of the symptom experience used to create the clusters. Given that patients with breast cancer receiving chemotherapy (CTX), report between 10 and 32 concurrent symptoms and studies of symptom clusters in these patients are limited, the purpose of this study, in breast cancer patients undergoing CTX (n = 515), was to identify whether the number and types of symptom clusters differed based on whether symptom occurrence rates or symptom severity ratings were used to create the clusters.

METHODS

A modified version of the Memorial Symptom Assessment Scale was used to assess for the occurrence and severity of 38 symptoms, one week after the administration of CTX. Exploratory factor analysis was used to extract the symptom clusters.

RESULTS

Both the number and types of symptom clusters were similar using symptom occurrence rates or symptom severity ratings. Five symptom clusters were identified using symptom occurrence rates (i.e., psychological, hormonal, nutritional, gastrointestinal, epithelial). Six symptom clusters (i.e., psychological, hormonal, nutritional, gastrointestinal, epithelial, chemotherapy neuropathy) were identified using symptom severity ratings. Across the two dimensions, the specific symptoms within each of the symptom clusters were similar.

CONCLUSIONS

Identification of symptom clusters in patients with breast cancer may be useful in guiding symptom management interventions. Future studies are warranted to determine if symptom clusters remain stable over a cycle of CTX in patients with breast cancer.

Longitudinal Examination of Symptom Profiles Among Breast Cancer Survivors

CONTEXT

Identification of cancer patients with similar symptom profiles may facilitate targeted symptom management.

OBJECTIVES

To identify subgroups of breast cancer survivors based on differential experience of symptoms, examine change in subgroup membership over time, and identify relevant characteristics and quality of life (QOL) among subgroups.

METHODS

Secondary analyses of data from 653 breast cancer survivors recruited within eight months of diagnosis who completed questionnaires at five time points. Hidden Markov modeling was used to 1) formulate symptom profiles based on prevalence and severity of eight symptoms commonly associated with breast cancer and 2) estimate probabilities of changing subgroup membership over 18 months of follow-up. Ordinal repeated measures were used to 3) identify patient characteristics related to subgroup membership and 4) evaluate the relationship between symptom subgroup and QOL.

RESULTS

A seven-subgroup model provided the best fit: 1) low symptom burden, 2) mild fatigue, 3) mild fatigue and mild pain, 4) moderate fatigue and moderate pain, 5) moderate fatigue and moderate psychological, 6) moderate fatigue, mild pain, mild psychological, and 7) high symptom burden. Seventy percent of survivors remained in the same subgroup over time. In multivariable analyses, chemotherapy and greater illness intrusiveness were significantly related to greater symptom burden, while not being married or partnered, no difficulty paying for basics, and greater social support were protective. Higher symptom burden was associated with lower QOL. Survivors who reported psychological symptoms had significantly lower QOL than did survivors with pain symptoms.

CONCLUSION

Cancer survivors can be differentiated by their symptom profiles.

Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations

An overview of proceedings, findings, and recommendations from the workshop on "Advancing Symptom Science Through Symptom Cluster Research" sponsored by the National Institute of Nursing Research (NINR) and the Office of Rare Diseases Research, National Center for Advancing Translational Sciences, is presented. This workshop engaged an expert panel in an evidenced-based discussion regarding the state of the science of symptom clusters in chronic conditions including cancer and other rare diseases. An interdisciplinary working group from the extramural research community representing nursing, medicine, oncology, psychology, and bioinformatics was convened at the National Institutes of Health. Based on expertise, members were divided into teams to address key areas: defining characteristics of symptom clusters, priority symptom clusters and underlying mechanisms, measurement issues, targeted interventions, and new analytic strategies. For each area, the evidence was synthesized, limitations and gaps identified, and recommendations for future research delineated. The majority of findings in each area were from studies of oncology patients. However, increasing evidence suggests that symptom clusters occur in patients with other chronic conditions (eg, pulmonary, cardiac, and end-stage renal disease). Nonetheless, symptom cluster research is extremely limited and scientists are just beginning to understand how to investigate symptom clusters by developing frameworks and new methods and approaches. With a focus on personalized care, an understanding of individual susceptibility to symptoms and whether a "driving" symptom exists that triggers other symptoms in the cluster is needed. Also, research aimed at identifying the mechanisms that underlie symptom clusters is essential to developing targeted interventions.

Symptom clusters during palliative chemotherapy and their influence on functioning and quality of life

INTRODUCTION

Symptom management in patients undergoing palliative chemotherapy is challenging, as patients may suffer from cancer symptoms as well as symptoms related to chemotherapy. Symptom clusters are interrelated symptoms occurring simultaneously that exert a negative impact on survival. Identification of symptom clusters and effective symptom management for patients receiving palliative chemotherapy is crucial.

OBJECTIVES

The purpose of this study was to identify symptom clusters among cancer patients undergoing palliative chemotherapy and examine the relationship between symptom clusters and functioning and quality of life (QOL) in these patients.

METHODS

A total of 300 patients undergoing palliative chemotherapy participated in the study. Symptom experience during previous palliative chemotherapy was evaluated using a symptom questionnaire including 20 symptoms. The European Organization for Research and Treatment of Cancer Quality of Life-C30 was used to measure patients' symptoms, functioning and QOL. Factor and hierarchical cluster analyses were performed to identify symptom clusters. Structural equation modeling was used to identify relationships between symptom clusters, functioning and QOL in patients.

RESULTS

Four symptoms clusters including 14 symptoms were identified of the 20 symptoms experienced by patients undergoing palliative chemotherapy. The emotional cluster had negative influence on role and social functioning. The nausea and vomiting/appetite/taste change cluster had a negative impact on role functioning. The fatigue/cognitive and other cluster (dyspnea, pain, constipation, neuropathy, and sleep disturbance) negatively influenced physical functioning. Among the functioning subscales, only role functioning had a direct influence on QOL. Indirect relationships between symptom clusters and QOL were mediated by physical and role functioning. The final model, which consisted of four symptom clusters and three functioning subscales, accounted for 23.3% of the variance in the QOL.

CONCLUSIONS

Four symptom clusters occurring during palliative chemotherapy demonstrated negative influences on functioning and QOL. Differential contributions of symptom clusters to functioning were identified that eventually contributed to QOL through role functioning. The identified symptom clusters and their relationships with functioning and QOL may help guide approaches to symptom management. Implementation of interventions targeting symptom clusters would contribute to improving functioning and QOL in patients.

Unmet supportive care needs and desire for assistance in patients receiving radiation treatment: Implications for oncology nursing

Unmet supportive care needs can contribute to emotional distress and reduced quality of life for cancer patients. We undertook a supportive care needs assessment for patients undergoing radiation therapy to provide a basis for program planning. A self-report supportive care needs survey was completed by a convenience sample of 115 patients on days five, seven and 16 during their course of radiation. The most frequently identified physical unmet needs at all three times were fatigue (33%-49%), dry and itchy skin (24%-37%), and sleep difficulties (23%-30%). The number of patients citing these unmet needs increased significantly over the study time period. Within the emotional domain, worry (34.5%) was cited most frequently on day five. The number of individuals expressing worry did not decrease significantly by day 16. Across all domains and individual items, there was wide variation in the percentage of individuals who had an unmet need and also indicated they wanted help with that unmet need. This pattern remained consistent over time. This study emphasizes the need for a defined or intentional process to assess supportive care needs and patient desire for assistance or help with unmet needs.

Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life

CONTEXT

Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters.

OBJECTIVES

To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life.

METHODS

Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30.

RESULTS

Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning.

CONCLUSIONS

The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential.

Cancer symptom clusters: an exploratory analysis of eight statistical techniques

CONTEXT

Statistical methods to identify symptom clusters (SC) have varied between studies. The optimal statistical method to identify SC is unknown.

OBJECTIVES

Our primary objective was to explore whether eight different statistical techniques applied to a single data set produced different SC. A secondary objective was to investigate whether SC identified by these techniques resembled those from our original study.

METHODS

We reanalyzed a symptom data set of 1000 patients with advanced cancer. Eight separate cluster analyses were conducted on both prevalence and severity of 38 symptoms. Hierarchical cluster analysis identified clusters at r-values of 0.6, 0.5, and 0.4. For prevalence and severity, the Spearman correlation and Kendall tau-b correlation, respectively, measured the similarity (distance) between symptom pairs. Sensitivity analysis of the prevalence data was done with Cohen kappa coefficient as a similarity measure. The K-means clustering method validated clusters.

RESULTS

Hierarchical cluster analysis identified similar cluster configurations from the 38 symptoms using an r-value of 0.6, 0.5, or 0.4. A cutoff point of 0.6 yielded seven clusters. Five of them were identical at all three r-values used: (1) fatigue/anorexia-cachexia: anorexia, dry mouth, early satiety, fatigue, lack of energy, taste changes, weakness, and weight loss (>10%); (2) gastrointestinal: belching, bloating, dyspepsia, and hiccough; (3) nausea/vomiting: nausea and vomiting; (4) aerodigestive: cough, dysphagia, dyspnea, hoarseness, and wheeze; (5) neurologic: confusion, hallucinations, and memory problems. Regardless of the threshold, there were always some symptoms (e.g., pain) that did not cluster with any others. Seven clusters were validated by K-means analysis.

CONCLUSION

Seven SC identified from both prevalence and severity data were consistently present irrespective of the statistical analysis used. There were only minor variations in the number of clusters and their symptom composition between analytical techniques. All seven clusters originally identified were confirmed. Four consistent SC were found in all analyses: aerodigestive, fatigue/anorexia-cachexia, nausea/vomiting, and upper GI. Our results support the clinical importance of the SC concept.

Avaliação da intervenção cognitivo-comportamental em gestão do stress em pacientes com fadiga oncológica, em radioterapia

Apresentam-se os resultados relativos a padrões de regulação emocional, percepção e satisfação com o suporte social após intervenção cognitivo-comportamental em gestão do stress (IGSCC) em pacientes em radioterapia com fadiga oncológica. Compara-se o grupo de controlo (n=35 radioterapia sem IGSCC) e o grupo experimental (n=35 radioterapia com IGSCC) no início e fim do tratamento tendo em conta variáveis sociodemográficas, Escala de ansiedade, depressão e stress, Escala de perceção e satisfação com o suporte social e o Termómetro da emoção. No grupo experimental, após IGSCC, há descida significativa (p<.001) da ansiedade, depressão e stress e aumento da percepção e satisfação com o suporte social. No grupo de controlo há subida significativa (p<.001) da desregulação emocional (ansiedade, depressão e stress) e subida da insatisfação com o suporte social. Salienta-se a eficácia da IGSCC sobre estados emocionais e percepção e satisfação com o suporte social em pacientes em radioterapia e com fadiga oncológica.

Screening for depressed mood in patients with cancer using the MD Anderson Symptom Inventory: investigation of a practical approach for the oncologist

PURPOSE

Depression is a significant concern in outpatient oncology care, yet clinicians face practical challenges in accurately and efficiently screening patients for it. This study investigated whether a single item or multiple items from an existing multisymptom scale, the MD Anderson Symptom Inventory (MDASI), might serve as effective initial screens for depressed mood.

METHODS

Data were collected from two cohorts of patients. Cohort 1 comprised 187 patients with non-small-cell lung cancer who completed the Beck Depression Inventory II; cohort 2 comprised 281 patients with renal cell carcinoma who completed the Center for Epidemiologic Studies Depression Scale. All patients completed the MDASI. Single-item and multiple-item MDASI solutions were identified using cohort 1 and validated in cohort 2. Sensitivity and specificity of the solutions were assessed through binary linear regression; cut points were identified using receiver operating characteristic analysis.

RESULTS

The MDASI single item "sadness" was the best solution identified in cohort 1 for screening for depressed mood relative to other affective items (distress, enjoyment of life, mood). At a cut point ≥ 4 (0 to 10 scale), the "sadness" item exhibited a clinically acceptable specificity of 81.5%, sensitivity of 72.0%, a negative predictive value of 95.0%, and a positive predictive value of 37.5%. This solution was successfully validated in cohort 2.

CONCLUSION

The MDASI "sadness" item has modest sensitivity and high negative predictive value and can serve as a useful initial screen for depressed mood. This approach may improve the efficiency and acceptability of depression screening for both clinicians and patients.

The Evaluation of a New Supportive Care Screening Tool for Radiation Therapy Patients

OBJECTIVES

Individuals undergoing radiation therapy for cancer may experience a wide range of supportive care needs that are frequently not addressed. A screening tool was designed and tested for psychometric properties (technical characteristics) to assist radiation therapists to quickly identify those patients who require additional intervention during the course of their radiation treatment, allowing early and timely referral and facilitating the provision of quality, in-depth, and patient-centred supportive care.

METHODOLOGY

A comprehensive and itemized screening tool was designed to identify the patient concerns and distress level, capture the patient desire to be helped with specific concerns, and inform the centre of alternative help provided. The tool was administered simultaneously with the standardized instrument quality-of-life questionnaire. One hundred and fifteen radiation therapy patients completed both instruments on three occasions; the first two were 2 days apart, and the third, 2 weeks later. To test the new tool for reliability and sensitivity, the agreement between the responses on the first two occasions and those between the first and third occasions were analysed for both instruments. Correlations between the responses on the two instruments were also examined for concurrent validity.

RESULTS

McNemar's test and the simple kappa coefficient both showed high agreement between item scores on the new screening tool when the first and the second occasions were compared. When the first and the third occasions were compared, the former test showed a shift from high agreement to lesser agreement across the item scores. The latter showed a shift in more than 97.7% of the items from a higher agreement to a lesser agreement. The new tool's sensitivity to change was further reinforced by the data from the validated quality-of-life questionnaire, which showed a similar change over time; the Pearson product moment correlation coefficient fell on average from 0.75 to 0.58 for the first and the second comparisons respectively, with all P values less than .0001. Concurrent validity was found to be acceptable.

CONCLUSIONS

The new screening tool was found to be reliable and sensitive, with acceptable validity. It is anticipated that the screening intervention will allow radiation therapists to standardize and formalize their approach to supportive care in radiation therapy outpatient clinics and enhance their capacity to identify and address patient concerns in a timely manner.

A Conceptual Model of Psychoneurological Symptom Cluster Variation in Women with Breast Cancer: Bringing Nursing Research to Personalized Medicine

Personalized medicine applies knowledge about the patient's individual characteristics in relation to health and intervention outcomes, including treatment response and adverse side-effects, to develop a tailored treatment plan. For women with breast cancer, personalized medicine has substantially improved the rate of survival, however, a high proportion of these women report multiple, co-occurring psychoneurological symptoms over the treatment trajectory that adversely affect their quality of life. In a subset of these women, co-occurring symptoms referred to as symptoms clusters, can persist long after treatment has ended. Over the past decade, research from the field of nursing and other health sciences has specifically examined the potential underlying mechanisms of the psychoneurological symptom cluster in women with breast cancer. Recent findings suggest that epigenetic and genomic factors contribute to inter-individual variability in the experience of psychoneurological symptoms during and after breast cancer treatment. While nursing research has been underrepresented in the field of personalized medicine, these studies represent a shared goal; that is, to improve patient outcomes by considering the individual's risk of short- and long-term adverse symptoms. The aim of this paper is to introduce a conceptual model of the individual variations that influence psychoneurological symptoms in women with breast cancer, including perceived stress, hypothalamic-pituitary adrenocortical axis dysfunction, inflammation, as well as epigenetic and genomic factors. The proposed concepts will help bring nursing research and personalized medicine together, in hopes that this hitherto neglected and understudied area of biomedical research convergence may ultimately lead to the development of more targeted clinical nursing strategies in breast cancer patients with psychoneurological symptoms.

Symptom clusters in patients with metastatic cancer: a literature review

This article reviews the literature reporting empirically determined symptom clusters in patients with metastatic cancer. A literature search was conducted on symptom clusters within heterogeneous metastatic cancer patient populations using MEDLINE, EMBASE, and CINAHL. Studies examining predetermined symptom clusters were excluded. A total of eight relevant studies published between 2005 and 2011 were identified. The number of symptom clusters extracted varied from two to eight clusters per study, comprising of two to eight symptoms per cluster. There were no clusters consistently identified within all eight studies. Notable differences in symptoms assessed, assessment tools, statistical analysis, patient demographics were observed between the studies. The lack of consensus among the inter-study symptom clusters are likely due to the differences in patient population as well as study methodology. Further exploration in metastatic symptom cluster research will ideally improve patient outcomes by facilitating improved symptom management in future clinical practice.

Symptom Cluster Research in Women with Breast Cancer: A Comparison of Three Subgrouping Techniques

Aims

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.

Background

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.

Design

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.

Methods

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.

Results

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.

Conclusion

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.

Identification of cancer-related symptom clusters: an empirical comparison of exploratory factor analysis methods

CONTEXT

Symptom clusters, important for symptom management strategies, have been determined empirically by various analytical methods. Guidance to select methods from the options available in standard statistical packages is limited.

OBJECTIVES

To compare alternative common factor analysis (FA) extraction methods appropriate to the data, to assess whether or not they determine similar symptom clusters, and to propose analytical approaches that are useful in this clinical context.

METHODS

Within one month of commencing chemotherapy, outpatients from oncology and hematology clinics (n = 202) reported their symptom experience on a modified Rotterdam Symptom Checklist. Symptom distress levels in the past week were rated on a scale of one (not at all) to four (very much). In a secondary data analysis of 42 symptoms, the associations between symptoms and factors were determined using alternative common FA methods: principal axis factoring, unweighted least squares, image factor analysis, and alpha factor analysis (AFA). Symptom inclusion in a cluster was based on the interpretation of pattern and structure coefficients, and importantly, clinical relevance of the grouping.

RESULTS

Five symptom clusters were commonly identified across methods: musculoskeletal discomforts/lethargy, oral discomforts, upper gastrointestinal discomforts, vasomotor symptoms, and gastrointestinal toxicities. In AFA, three additional clusters were lethargy, somatic symptoms, and treatment-related symptom clusters.

CONCLUSION

The most parsimonious solution resulted from principal axis factoring, but for large numbers of symptoms, AFA may be superior by identifying symptom clusters more useful for symptom management. Interpreting complex symptom relationships may lead to the investigation of pathophysiological mechanisms and intervention opportunities. Future studies should include psychological and cognitive symptoms.

Associations between pro- and anti-inflammatory cytokine genes and breast pain in women prior to breast cancer surgery

The purposes of this study were to determine the occurrence rate for preoperative breast pain; describe the characteristics of this pain; evaluate for differences in demographic and clinical characteristics; and evaluate for variations in pro- and anti-inflammatory cytokine genes between women who did and did not report pain. Patients (n = 398) were recruited prior to surgery and completed self-report questionnaires on a number of pain characteristics. Genotyping was done using a custom genotyping array. Women (28.2%) who reported breast pain were significantly younger (P < .001); more likely to be nonwhite (P = .032); reported significantly lower Karnofsky Performance Status scores (P = .008); were less likely to be postmenopausal (P = .012); and had undergone significantly more biopsies (P = .006). Carriers of the minor allele for a single nucleotide polymorphism in interleukin (IL)1-receptor 1 (IL1R1) (rs2110726) were less likely to report breast pain prior to surgery (P = .007). Carriers of the minor allele for a single nucleotide polymorphism in IL13 (rs1295686) were more likely to report breast pain prior to surgery (P = .019). Findings suggest that breast pain occurs in over a quarter of women who are about to undergo breast cancer surgery. Based on phenotypic and genotypic characteristics found, inflammatory mechanisms contribute to preoperative breast pain.

PERSPECTIVE

In women with breast cancer, preoperative pain may be associated with increases in inflammatory responses associated with an increased number of biopsies. In addition, differences in cytokine genes may contribute to this preoperative breast pain.

Symptom cluster analyses based on symptom occurrence and severity ratings among pediatric oncology patients during myelosuppressive chemotherapy

BACKGROUND

Symptom cluster research is an emerging field in symptom management. The ability to identify symptom clusters that are specific to pediatric oncology patients may lead to improved understanding of symptoms' underlying mechanisms among patients of all ages.

OBJECTIVE

The purpose of this study, in a sample of children and adolescents with cancer who underwent a cycle of myelosuppressive chemotherapy, was to compare the number and types of symptom clusters identified using patients' ratings of symptom occurrence and symptom severity.

METHODS

Children and adolescents with cancer (10-18 years of age; N = 131) completed the Memorial Symptom Assessment Scale 10-18 on the day they started a cycle of myelosuppressive chemotherapy, using a 1-week recall of experiences. Symptom data based on occurrence and severity ratings were examined using exploratory factor analysis. The defined measurement model suggested by the best exploratory factor analysis model was then examined with a latent variable analysis.

RESULTS

Three clusters were identified when symptom occurrence ratings were evaluated, which were classified as a chemotherapy sequela cluster, mood disturbance cluster, and a neuropsychological discomfort cluster. Analysis of symptom severity ratings yielded similar cluster configurations.

CONCLUSIONS

Cluster configurations remained relatively stable between symptom occurrence and severity ratings. The evaluation of patients at a common point in the chemotherapy cycle may have contributed to these findings.

IMPLICATIONS FOR PRACTICE

Additional uniformity in symptom clusters investigations is needed to allow appropriate comparisons among studies. The dissemination of symptom cluster research methodology through publication and presentation may promote uniformity in this field.

Symptom clusters: myth or reality?

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.

Effects of pain, fatigue, insomnia, and mood disturbance on functional status and quality of life of elderly patients with cancer

BACKGROUND

Most elderly patients with cancer suffer from a multitude of intense physical and psychological symptoms regardless of the stage of disease. The current paper describes the prevalence of pain, fatigue, insomnia, and mood disturbance, alone and in combination in elderly cancer patients, as well as the inter-correlations among these four symptoms, and the relationship of the symptom cluster to functional status and quality of life (QoL) during cancer therapy.

PATIENTS AND METHODS

This cross-sectional study used secondary data from a convenience sample of 120 patients, 65 years of age and older, with colorectal, lung, head/neck, breast, gynecological, prostate or esophageal cancer receiving chemotherapy or radiotherapy. Measuring instruments included the Karnofsky Performance Scale (KPS), the respective items from the Chinese version of the Symptom Distress Scale (SDS-C), and the Functional Assessment of Cancer Therapy-General (FACT-G [C]). The influence of the symptom cluster on patients' functional status and QoL was determined by hierarchical multiple regression.

RESULTS

Twenty percent and 29.2% of patients reported co-occurrence of any two and any three symptoms of pain, fatigue, insomnia, and mood disturbance, respectively. About one-third of patients (31.2%) reported co-occurrence of all of the four symptoms. The inter-correlations among pain, fatigue, insomnia, and mood disturbance were mild to moderate (r=0.29-0.43, p<0.01). In terms of functional status, the KPS showed a moderate negative correlation with the four symptoms (r=-0.29 to -0.55, p<0.01). Correlations between the FACT-G (C) subscale/total scores and symptom cluster showed moderate negative correlations (r=-0.23 to -0.55, p<0.01). About 8.7-52.9% of variance in functional status and QoL is explained by the symptom cluster of pain, fatigue, insomnia, and mood disturbance in elderly cancer patients receiving cancer therapy after adjustment for gender, age, co-morbidity, stage of disease, and treatment modality.

CONCLUSIONS

Our results suggest that pain, fatigue, insomnia, and mood disturbance are highly prevalent in elderly patients who undergone cancer therapy. These four symptoms may occur in a cluster and may negatively influence elderly patients' functional status and QoL during cancer therapy.