Defining the Symptom Cluster: How Far Have We Come?

Symptom Clusters in Children With Leukemia Receiving Chemotherapy: A Scoping Review

BACKGROUND

Leukemia represents the most prevalent childhood malignancy. Understanding the symptom clusters (SCs) associated with leukemia may help develop an effective care plan for affected children.

OBJECTIVES

The aims of this study were to summarize the methods of identifying SCs; ascertain the types, attributes, and changing patterns of SCs during different chemotherapy phases; and provide a point of reference for the subsequent improvement of symptom management in pediatric leukemia.

METHODS

The methodological framework employed was the Joanna Briggs Institute Scoping Review Guide. A comprehensive search was conducted across various databases, including PubMed, EMBASE, CINAHL, Web of Science, MEDLINE, Scopus, and China National Knowledge Infrastructure from inception until July 15, 2023.

RESULTS

A total of 14 articles were included in this review, 6 in English and 8 in Chinese. The Memorial Symptom Assessment Scale 10-18 is the most commonly used instrument, whereas factor analysis is the most common statistical method for SC identification. The SCs were classified into 12 categories. The most severe SCs varied across different phases. Specifically, the emotional cluster dominated the prechemotherapy phase, the gastrointestinal cluster surfaced during postinduction therapy, and the consolidation and maintenance therapy phases revealed the self-image disorder cluster.

CONCLUSION

Various consistent and dynamic SCs manifest among pediatric patients with leukemia undergoing chemotherapy.

IMPLICATIONS FOR PRACTICE

Future research endeavors should formulate clear criteria to determine the stability and consistency of SCs, validate SC composition and characteristics, and devise precise symptom management protocols based on SC characteristics in the distinct chemotherapy phases.

Symptom Clusters and Their Impact on Spiritual Well-Being Among Women with Breast Cancer

Purpose

To explore symptom experience and symptom clusters among Jordanian women with breast cancer and investigate whether these clusters predict patients' spiritual well-being.

Patients and Methods

A sample of 142 Jordanian women with breast cancer were asked to complete the Memorial Symptom Assessment Scale (MSAS), Functional Assessment of Chronic Illness Therapy- Spiritual Well-being (FACIT-Sp) scale, and socio-demographic questionnaire. Exploratory factor analysis was used to group symptoms into clusters, and multiple linear regression was used to explore the symptom clusters that predict spiritual well-being.

Results

The most prevalent symptoms among women with breast cancer were fatigue, anxiety, tension, and pain. All these symptoms have a prevalence greater than 50%. Three clusters were found: treatment-related symptom cluster consisting of eight symptoms, gastrointestinal symptom cluster consisting of seven symptoms, and psychological symptom cluster consisting of five symptoms. The psychological symptom cluster was the only cluster predicting the women's spiritual well-being (t (141) = -3.049; p < 0.01).

Conclusion

Women with breast cancer experience several concurrent symptoms and symptom clusters. Screening for psychological symptom clusters and their treatment improves patients' spiritual well-being. The majority of women with breast cancer did not receive any complementary therapies and hardly any spiritual or psychological support, which should be provided in the future to support their spiritual well-being.

Identification of symptom clusters and sentinel symptoms during the first cycle of chemotherapy in patients with lung cancer

PURPOSE

To identify symptom clusters (SCs) in patients with lung cancer who are undergoing initial chemotherapy and to identify the sentinel symptoms of each SC.

METHODS

A convenience sampling method was used to recruit patients with lung cancer who were undergoing their initial chemotherapy treatment. Patient information was collected using the General Demographic Questionnaire, MD Anderson Symptom Inventory (including the lung cancer module) and a schedule documenting the initial occurrence of symptoms. The Walktrap algorithm was employed to identify SCs, while sentinel symptoms within each SC were identified using the Apriori algorithm in conjunction with the initial occurrence time of symptoms.

RESULTS

A total of 169 patients with lung cancer participated in this study, and four SCs were identified: the psychological SC (difficulty remembering, sadness, dry mouth, numbness or tingling, and distress), somatic SC (pain, fatigue, sleep disturbance, and drowsiness), respiratory SC (coughing, expectoration, chest tightness, and shortness of breath), and digestive SC (nausea, poor appetite, constipation, vomiting, and weight loss). Sadness, fatigue, and coughing were identified as sentinel symptoms of the psychological, somatic, and respiratory SCs, respectively. However, no sentinel symptom was identified for the digestive SC.

CONCLUSION

Patients with lung cancer who are undergoing chemotherapy encounter a spectrum of symptoms, often presenting as SCs. The sentinel symptom of each SC emerges earlier than the other symptoms and is characterized by its sensitivity, significance, and driving force. It serves as a vital indicator of the SC and assumes a sentry role. Targeting sentinel symptoms might be a promising strategy for determining the optimal timing of interventions and for mitigating or decelerating the progression of the other symptoms within the SC.

Trends and predictors of Quality of Life in lung cancer survivors

INTRODUCTION

Health-related quality of life (HR-QoL) is often impaired in lung cancer survivors. To inform personalized survivorship care, we identified associations between HR-QoL scores and patient-, tumor-, and treatment-factors over time.

MATERIALS AND METHODS

We evaluated HR-QoL scores provided at diagnosis, 6 months, 1 year, and 2 years from the Yale Lung Cancer Biorepository. HR-QoL was measured via the Functional Assessment of Cancer Therapy - Lung (FACT-L) instrument and available for a subset of patients (n = 513). Analyses were stratified by early-stage (I-II; n = 355) non-small cell lung cancer (NSCLC), advanced stage NSCLC (III-IV; n = 158), and small cell lung cancer (SCLC, n = 21). We used mixed effects modeling and multivariable analysis with covariate adjustment to examine changes in FACT-L from diagnosis to follow-up. Sensitivity analysis was performed including patients with early-stage disease and complete FACT-L scores at both baseline and year 2 (n = 91).

RESULTS

The average FACT-L scores at diagnosis in early-stage NSCLC, advanced stage NSCLC, and SCLC were 121.0 (standard deviation (SD) 11.4), 109.2 (18.7), and 98.7 (20.2) respectively. At all timepoints, HR-QoL was higher in patients with early-stage NSCLC (vs advanced-stage disease). In patients with early- and advanced-stage NSCLC, HR-QoL was higher at years 1 and 2 than at diagnosis, though the changes did not meet clinical significance. At NSCLC diagnosis, higher HR-QoL was associated with older age, better performance status, participating in physical activity, adenocarcinoma histology, and (in advanced stage NSCLC) anticipated treatment with chemotherapy. At NSCLC follow-up, HR-QoL was higher in patients with higher BMI and better performance status.

DISCUSSION

In patients with newly diagnosed NSCLC, HR-QoL scores are impacted by patient factors, tumor factors, and treatment factors. HR-QoL is higher in patients with early-stage disease. In patients surviving 2 years, HR-QoL was higher at follow-up, though the change did not meet clinical significance. To optimize HR-QoL, lung cancer survivorship teams should prioritize comorbidity management, physical activity, healthy weight maintenance, and treatment-related side effects.

Exploring symptom clusters in mild cognitive impairment and dementia with the NIH Toolbox

OBJECTIVE

Symptom clustering research provides a unique opportunity for understanding complex medical conditions. The objective of this study was to apply a variable-centered analytic approach to understand how symptoms may cluster together, within and across domains of functioning in mild cognitive impairment (MCI) and dementia, to better understand these conditions and potential etiological, prevention, and intervention considerations.

METHOD

Cognitive, motor, sensory, emotional, and social measures from the NIH Toolbox were analyzed using exploratory factor analysis (EFA) from a dataset of 165 individuals with a research diagnosis of either amnestic MCI or dementia of the Alzheimer's type.

RESULTS

The six-factor EFA solution described here primarily replicated the intended structure of the NIH Toolbox with a few deviations, notably sensory and motor scores loading onto factors with measures of cognition, emotional, and social health. These findings suggest the presence of cross-domain symptom clusters in these populations. In particular, negative affect, stress, loneliness, and pain formed one unique symptom cluster that bridged the NIH Toolbox domains of physical, social, and emotional health. Olfaction and dexterity formed a second unique cluster with measures of executive functioning, working memory, episodic memory, and processing speed. A third novel cluster was detected for mobility, strength, and vision, which was considered to reflect a physical functioning factor. Somewhat unexpectedly, the hearing test included did not load strongly onto any factor.

CONCLUSION

This research presents a preliminary effort to detect symptom clusters in amnestic MCI and dementia using an existing dataset of outcome measures from the NIH Toolbox.

Symptom Clusters in Patients With Advanced Cancer: A Prospective Longitudinal Cohort Study to Examine Their Stability and Prognostic Significance

This study's purpose was to assess symptom cluster (SC) stability during disease progression and determine their strength of association with survival in patients with advanced cancer . Consecutively eligible patients with advanced cancer not receiving cancer-specific treatment and referred to a Tertiary Palliative Care Clinic were enrolled in a prospective cohort study. At first consultation (D0) and in subsequent consultations at day 15 (D15) and day 30 (D30), patients rated 9 symptoms through the Edmonton Symptom Assessment System scale (0-10) and 10 others using a Likert scale (1-5). Principal components factor analysis with varimax rotation was used to determine SCs at each consultation. Of 318 patients with advanced cancer, 301 met eligibility criteria with a median age of 69 years (range 37-94). Three SCs were identified: neuro-psycho-metabolic (NPM), gastrointestinal, and sleep impairment, with some variations in their constitution over time. Exploratory factor analysis accounted for 40% of variance of observed variables in all SCs. Shorter median survival was observed continuously for NPM cluster (D0 23 vs. 58 days, P < .001; D15 41 vs. 104 days, P=.004; D30 46 vs. 114 days, P = .002), although the presence of 2 or more SCs on D0 and D15 also had prognostic significance (D0: 21 vs. 45 days, P = .005; D30: 50 vs. 96 days, P = .040). In a multivariable model, NPM cluster (D0 hazard ratio estimate: HR 1.64; 95%CI, 1.17-2.31; P = .005; D15 HR: 2.51; 95%CI, 1.25-5.05; P = .009; D30 HR: 3.9; 95%CI, 1.54-9.86; P = .004) and hospitalization (D0 HR: 2.27; 95%CI, 1.47-3.51; P < .001; D15 HR: 2.43; 95%CI, 1.18-5.01; P = .016; D30 HR: 3.41; 95%CI, 1.35-8.62; P = .009) were independently and significantly associated with worse survival. Three clinically relevant SCs were identified, and their constitution had small variations, maintaining a stable set of nuclear symptoms through disease progression. Presence of the NPM cluster and hospitalization maintained their prognostic value over time.

Symptom Clusters in Adults with Post-COVID-19: A Cross-Sectional Survey

More than 100 symptoms have been reported for post-coronavirus disease 2019 (COVID-19) and this study aimed to organize self-reported symptoms by identifying symptom clusters. We used a cross-sectional survey with a convenience sample of 491 adults who reported experiencing prolonged symptoms of COVID. A list of 25 symptoms of post-COVID-19 was used to measure the symptoms, and exploratory factor analysis was undertaken to identify symptom clusters for people with symptoms lasting 5 to 8 weeks and 9 weeks or longer. Six symptom clusters were identified for each of the two groups, and five clusters were similar across both groups: respiratory, general viral, smell/taste, cognitive cardiac, and mental health. The >9-week group reported symptoms primarily from two factors: respiratory-muscular and mental health. Post-COVID-19 symptom clusters differ across timeframes. Symptom clusters were useful in establishing coherent patterns of multiple complex symptoms.

The association of circadian parameters and the clustering of fatigue, depression, and sleep problems in breast cancer survivors: a latent class analysis

PURPOSE

Circadian rhythms control a wide range of physiological processes and may be associated with fatigue, depression, and sleep problems. We aimed to identify subgroups of breast cancer survivors based on symptoms of fatigue, insomnia, and depression; and assess whether circadian parameters (i.e., chronotype, amplitude, and stability) were associated with these subgroups over time.

METHODS

Among breast cancer survivors, usual circadian parameters were assessed at 3-4 months after diagnosis (T0), and symptoms of fatigue, depression, and insomnia were assessed after 2-3 years (T1, N = 265) and 6-8 years (T2, N = 169). We applied latent class analysis to classify survivors in unobserved groups ("classes") based on symptoms at T1. The impact of each of the circadian parameters on class allocation was assessed using multinomial logistic regression analysis, and changes in class allocation from T1 to T2 using latent transition models.

RESULTS

We identified 3 latent classes of symptom burden: low (38%), moderate (41%), and high (21%). Survivors with a late chronotype ("evening types") or low circadian amplitude ("languid types") were more likely to have moderate or high symptom burden compared to "morning types" and "vigorous types," respectively. The majority of survivors with moderate (59%) or high (64%) symptom burden at T1 had persistent symptom burden at T2.

IMPLICATIONS FOR CANCER SURVIVORS

A late chronotype and lower circadian amplitude after breast cancer diagnosis were associated with greater symptoms of fatigue, depression, and insomnia at follow-up. These circadian parameters may potentially be novel targets in interventions aimed at alleviating symptom burden among breast cancer survivors.

Identifying care problem clusters and core care problems of older adults with dementia for caregivers: a network analysis

Background

A shift in research interest from separate care problem to care problem clusters among caregivers of people living with dementia may contribute to a better understanding of dementia care. However, the care problems network among caregivers of people living with dementia are still unknown. This study aimed to identify care problem clusters and core care problems, and explore demographic variables associated with these care problem clusters among caregivers of people living with dementia.

Methods

Participants were recruited through memory clinics and WeChat groups. The principal component analysis was applied to identify care problem clusters. The network analysis was conducted to describe the relationships among care problems and clusters. Multiple linear models were used to explore the associated factors for the occurrence of the overall care problems and top three central care problem clusters.

Results

A total of 1,012 carer-patient pairs were included in the analysis. Nine care problem clusters were identified. In the entire care problem network, "deterioration in activities of daily living" was the most core care problem cluster across the three centrality indices, followed by "verbal and nonverbal aggression" and "loss of activities of daily living." Variables including marital status, years of dementia diagnosis, number of dementia medication type, and caregiver's educational attainment were associated with the prevalence of these three care problem clusters.

Conclusion

Our study suggests that there is a need to evaluate care problem clusters for the improvement of care problem management among people living with dementia. It is particularly important to include assessment and treatment of core care problem as an essential component of the dementia care.

Symptom burden survey and symptom clusters in patients with cervical cancer: a cross-sectional survey

PURPOSE

The purpose of this study is to determine the incidence and severity of symptoms of patients with cervical cancer within 6 months after radiotherapy and chemotherapy, form a symptom burden report, evaluate the distribution characteristics of symptoms, identify symptom clusters, and provide a basis for clinical doctors and nurses to improve the symptom management of patients with cervical cancer after radiotherapy and chemotherapy.

METHODS

The patients with cervical cancer within 6 months after radiotherapy and chemotherapy were recruited to investigate their symptom burden. Exploratory factor analysis was used to identify symptom clusters.

RESULTS

A total of 250 patients participated in the study. The study found that the most common symptom among the 40 symptoms was fatigue, and the most serious symptom was nocturia. Based on the occurrence rate and severity of symptoms, nine symptom clusters were identified, including psycho-emotion-related symptom cluster, pain-disturbed sleep-related symptom cluster, menopausal symptom cluster, tinnitus-dizziness-related symptom cluster, urinary-related symptom cluster, dry mouth-bitter taste-related symptom cluster, intestinal-related symptom cluster, memory loss-numbness-related symptom cluster, and emaciation-related symptom cluster. The three most serious symptom clusters are pain-disturbed sleep-related symptom cluster, urinary-related symptom cluster, and memory loss-numbness-related symptom cluster.

CONCLUSION

The symptoms of patients with cervical cancer within 6 months after radiotherapy and chemotherapy are complex, and nine symptom clusters can be identified according to the incidence and severity of symptoms. We can find the potential biological mechanism of each symptom cluster through the discussion of previous mechanism research and clinical research. The number of symptom clusters and the number of symptoms within the symptom cluster are closely related to the symptom evaluation scale selected for the study. Therefore, the symptom cluster study urgently needs a targeted symptom evaluation scale that can comprehensively reflect the patient's condition.

Cancer-related Fatigue in Lung Cancer: A Research Agenda: An Official American Thoracic Society Research Statement

Background: Fatigue is the most common symptom among cancer survivors. Cancer-related fatigue (CRF) may occur at any point in the cancer care continuum. Multiple factors contribute to CRF development and severity, including cancer type, treatments, presence of other symptoms, comorbidities, and medication side effects. Clinically, increasing physical activity, enhancing sleep quality, and recognizing sleep disorders are integral to managing CRF. Unfortunately, CRF is infrequently recognized, evaluated, or treated in lung cancer survivors despite more frequent and severe symptoms than in other cancers. Therefore, increased awareness and understanding of CRF are needed to improve health-related quality of life in lung cancer survivors. Objectives: 1) To identify and prioritize knowledge and research gaps and 2) to develop and prioritize research questions to evaluate mechanistic, diagnostic, and therapeutic approaches to CRF among lung cancer survivors. Methods: We convened a multidisciplinary panel to review the available literature on CRF, focusing on the impacts of physical activity, rehabilitation, and sleep disturbances in lung cancer. We used a three-round modified Delphi process to prioritize research questions. Results: This statement identifies knowledge gaps in the 1) detection and diagnostic evaluation of CRF in lung cancer survivors; 2) timing, goals, and implementation of physical activity and rehabilitation; and 3) evaluation and treatment of sleep disturbances and disorders to reduce CRF. Finally, we present the panel's initial 32 research questions and seven final prioritized questions. Conclusions: This statement offers a prioritized research agenda to 1) advance clinical and research efforts and 2) increase awareness of CRF in lung cancer survivors.

Relationships Between Colorectal Cancer Survivors' Positive Psychology, Symptoms, and Quality of Life

This cross-sectional study examined colorectal cancer (CRC) survivors' symptom and symptom cluster characteristics (occurrence, frequency, and severity), positive psychology (benefit-finding and post-traumatic growth), and quality of life (QoL), and determined whether positive psychology moderates symptoms and QoL relationship during acute cancer survivorship, time from diagnosis to treatment completion. A total of 117 CRC survivors completed demographics, symptoms, QoL, and positive psychology questionnaires. Descriptive statistics, multiple linear regression, and moderation analyses were performed. Participants reported high QoL (94%, M = 5.15) and moderate-high positive psychology (75%, M = 3.21). Nineteen symptoms and five symptom clusters were inversely related to QoL (p < .05). Positive psychology (M = ~≥3.24) moderated the relationship of QoL (p < .05) with symptoms occurrence (n = 10), symptom severity (n = 1), and with the generalized symptom cluster (weakness, fatigue, dizziness, drowsy, sleep disturbances, and pain). Positive psychology aids in symptom management and improves QoL. Nurses are poised to identify, prevent, promote, and advocate self-management skills to improve health-related outcomes.

Symptom clusters and impact on quality of life in esophageal cancer patients

BACKGROUND

Esophageal cancer patients can experience co-occurring, related symptoms labeled symptom clusters. This study aimed to identify symptom clusters and explore which SCs independently affect the quality of life (QoL) among esophageal cancer patients.

METHODS

This cross-sectional study was performed in Shenyang, China, from February 2021 to February 2022. Finally, 118 esophageal cancer patients effectively completed the survey. Questionnaires' information included the Functional Assessment of Cancer Therapy-General (FACT-G), the MD Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI), the Multidimensions Scale of Perceived Social Support, and demographic and clinical characteristics. Exploratory factor analysis with principal axis factoring was used to identify symptom clusters, and multiple regression analysis was employed to analyze the influencing factors of QoL.

RESULTS

The mean score of FACT-G was 69.88 (SD = 17.85) among 118 esophageal cancer patients. Four symptom clusters were identified: psychological-somatic, dysphagia, fatigue-pain, and gastrointestinal symptom clusters. Results of regression analysis indicated a significant impact on QoL for chemotherapy (β = 0.140, P < 0.045), psychological-somatic symptom cluster (β = - 0.329, P = 0.013), and social support (β = 0.409, P < 0.001) after adjusting demographic and clinical characteristics. The linear combination explained 47.8% of the variance in QoL.

CONCLUSIONS

There is a critical need to emphasize the importance of psychological-somatic symptoms clusters management programs and increasing social support to improve QoL in esophageal cancer patients.

Topology and redescriptions detect multiple alternative biological pathways from clinical phenotypes

Biological pathways play a crucial role in the properties of diseases and are important in drug discovery. Identifying the logical relationships among distinctive phenotypic clusters could reveal possible connections to the underlying pathways. However, this process is challenging since clinical phenotypes are often available through unstructured electronic health records. Moreover, in the absence of a standardized questionnaire, there could be bias among physicians toward selecting certain medical terms. In this article, we develop an efficient pipeline to address these challenges and help practitioners to reveal the pathways associated with the disease. We use topological data analysis and redescriptions and propose a pipeline of four phases: (1) pre-processing the clinical notes to extract the salient concepts, (2) constructing a feature space of the patients to characterize the extracted concepts, (3) leveraging the topological properties to distill the available knowledge and visualize the extracted features, and finally, (4) investigating the bias in the clinical notes of the selected features and identify possible pathways. Our experiments on a publicly available dataset of COVID-19 clinical notes testify that our pipeline can indeed extract meaningful pathways.

Advances in Conceptual and Methodological Issues in Symptom Cluster Research: A 20-Year Perspective

Two conceptual approaches are used to evaluate symptom clusters: "clustering" symptoms (ie, variable-centered analytic approach) and "clustering" patients (ie, person-centered analytic approach). However, these methods are not used consistently and conceptual clarity is needed. Given the emergence of novel methods to evaluate symptom clusters, a review of the conceptual basis for older and newer analytic methods is warranted. Therefore, this article will review the conceptual basis for symptom cluster research; compare and contrast the conceptual basis for using variable-centered versus patient-centered analytic approaches in symptom cluster research; review their strengths and weaknesses; and compare their applications in symptom cluster research.

Symptom phenotypes in Pulmonary Arterial Hypertension: The PAH “Symptome”

Women with pulmonary arterial hypertension (PAH) experience multiple symptoms, including dyspnea, fatigue, and sleep disturbance, that impair their health‐related quality of life (HRQOL). However, we know little about phenotypic subgroups of patients with PAH with similar, concurrent, multiple symptoms. The objectives of this study were to define the “symptome” by symptom cluster phenotypes and compare characteristics such as biomarkers, cardiac structure and function (echocardiography), functional capacity (6‐min walk distance), and HRQOL between the groups. This cross‐sectional study included 60 women with PAH. Subjects completed an assessment battery: Pulmonary Arterial Hypertension Symptom Scale, Pittsburgh Sleep Quality Index, Multidimensional Dyspnea Profile, Patient‐Reported Outcomes Measurement Information System (PROMIS®) Physical Function, PROMIS® Sleep‐Related Impairment, and the emPHasis‐10. Subjects also underwent transthoracic echocardiography, phlebotomy, 6‐min walk distance, and actigraphy. The three symptoms of dyspnea, fatigue, and sleep disturbance were used to define the symptom clusters. Other PAH symptoms, plasma and serum biomarkers, cardiac structure and function (echocardiography), exercise capacity (6‐min walk distance), sleep (actigraphy), and HRQOL were compared across phenotypes. The mean age was 50 ± 18 years, 51% were non‐Hispanic white, 32% were non‐Hispanic Black and 40% had idiopathic PAH. Cluster analysis identified Mild (n = 28, 47%), Moderate (n = 20, 33%), and Severe Symptom Cluster Phenotypes (n = 12, 20%). There were no differences for age, race, or PAH etiology between the phenotypes. WHO functional class (p < 0.001), norepinephrine levels (p = 0.029), right atrial pressure (p = 0.001), physical function (p < 0.001), sleep onset latency (p = 0.040), and HRQOL (p < 0.001) all differed significantly across phenotypes. We identified three distinctive symptom cluster phenotypes (Mild, Moderate, and Severe) for women with PAH that also differed by PAH‐related symptoms, physical function, right atrial pressure, norepinephrine levels, and HRQOL. These phenotypes could suggest targeted interventions to improve symptoms and HRQOL in those most severely affected.

Distinguishing symptom patterns in adults newly diagnosed with cancer: a latent class analysis

CONTEXT

Socio-demographic differences, including place of residence, socio-economic status, ethnicity, and gender, have been associated with various inequities in cancer care outcomes.

OBJECTIVES

The aims were to distinguish subgroups of patients with different symptom patterns at the time of the initial oncology visit and determine which clinical and socio-demographic variables are associated the different symptom patterns.

METHOD

Responses to the Edmonton Symptom Assessment Scale- revised and clinical and socio-demographic variables were obtained via the Ontario Cancer Registry and linked health data files. Latent class analyses were conducted to identify and compare the subgroups.

RESULTS

The cohort (n = 216,110) with a mean age of 64.5 years consisted of 54.1% women. The analyses identified six latent classes (proportions ranging from 0.09 to 0.31) with distinct symptom patterns, including: 1) many severe symptoms, 2) many less severe symptoms, 3) predominantly mild symptoms, 4) severe psychosocial symptoms, 5) severe somatic symptoms, 6) few symptoms. The subgroups were associated not only with clinical differences (diagnoses and functional status), but also with various socio-demographic (age, sex) and community characteristics (neighborhood income, proportion of foreign born, rurality).

CONCLUSION

The results indicated that there were substantial differences in symptom patterns at the time of the initial oncology visit, which were associated with both clinical diagnoses and socio-demographic differences. These results point to the importance of taking the social situation of patients into account, and not just diagnosis, to better understand differences in symptom patterns of people living with cancer.

Symptom cluster: management and advanced practices in oncology nursing

OBJECTIVE

To present the definition of "symptom cluster" in cancer patients and to reflect on the theory, assessment, outcomes, and interventions for symptom management, based on the perspective of advanced practices in oncology nursing.

METHOD

Theoretical-reflective study that presents and discusses possibilities for managing "symptom clusters" through advanced practices in oncology nursing.

RESULTS

The term "symptom cluster" can be defined as a set of two or more related symptoms. The theoretical concepts and models that can help in its understanding are: Theory of Unpleasant Symptoms, Theory of Symptom Management, concept of self-efficacy and Theory of symptom self-management. Advanced practice nurses have the skills to manage "symptom clusters," optimizing outcomes and positively influencing the quality of life of cancer patients.

CONCLUSION

Advanced practice nurses have the essential characteristics to design, to implement and to evaluate intervention protocols aimed at the management of "symptom clusters" in cancer patients.

Nutrition Impact Symptom Clusters in a Cohort of Indigenous Australian Hemodialysis Patients: New Insights Into the Management of Malnutrition?

OBJECTIVE

The objective of this study is to describe nutrition impact symptom clusters present in a large sample of indigenous hemodialysis patients.

DESIGN AND METHODS

This study is a cross-sectional secondary analysis of data from a service audit conducted in 2016. All participants were hemodialysis patients from 2 satellite hemodialysis units in Central Australia. All participants completed a Patient-Generated Subjective Global Assessment. Exploratory factor analysis was performed to identify nutrition impact symptom clusters.

RESULTS

A total of 249 patients were included, representing 16% of all indigenous dialysis patients in Australia. Malnutrition was present in 29% of the sample. Five distinct nutrition impact symptom clusters were identified, accounting for 51.942% of the variance in symptoms. The 5 clusters extracted were the following: sore mouth (swallow problems, sore mouth, pain); nausea and vomiting (nausea, vomiting, taste changes); abnormal bowels (diarrhea, constipation, depression); anorexia (no appetite, early satiety); and dry mouth (dry mouth, dental problems).

CONCLUSIONS

Malnourished patients experienced a significantly greater symptom burden in this study. This analysis extends the small evidence base about the nutrition impact symptom burden of indigenous hemodialysis patients. Understanding symptom clusters and how symptoms are connected may be useful for triaging care and managing malnutrition.

Symptom clusters and quality of life in ambulatory patients with multiple myeloma

PURPOSE

The aim of this study was to investigate symptom clusters and associated clinical factors in ambulatory multiple myeloma patients undergoing medication therapy. We also aimed to determine the correlations between symptom clusters and patient quality of life.

METHODS

A total of 174 multiple myeloma patients hospitalized in the haematology day unit were included in this study. A cross-sectional survey was conducted to examine symptoms and quality of life. Symptoms were assessed by the Chinese version of the Condensed Memorial Symptom Assessment Scale. Quality of life was measured with the Functional Assessment of Cancer Therapy-General. Principal component analysis was used to identify symptom clusters. Independent-samples t tests and chi-square tests were used for comparisons between groups. Spearman's rank correlation analysis was used to identify correlations.

RESULTS

We identified three symptom clusters in multiple myeloma patients: psychological; pain, dry mouth, and difficulty sleeping; and fatigue symptom cluster. For each symptom cluster, the patients could be categorized into a severe-symptom group or a mild-symptom group based on the distress of symptoms. The patients in each group exhibited differential demographic and clinical features. Symptom cluster distress was adversely correlated with patients' quality of life.

CONCLUSIONS

Ambulatory multiple myeloma patients undergoing anticancer medication therapy experience multiple symptoms, which can be categorized into three symptom clusters. For each symptom cluster, level of distress was associated with patients' demographic and clinical characteristics. The presence and level of distress of these symptom clusters have adverse impacts on patients' quality of life.

Symptom clusters in patients receiving chemotherapy: A systematic review

BACKGROUND AND PURPOSE

Since 2001, symptom cluster research has grown considerably. However, because multiple methodological considerations remain, ongoing synthesis of the literature is needed to identify gaps in this area of symptom science. This systematic review evaluated the progress in symptom clusters research in adults receiving primary or adjuvant chemotherapy since 2016.

METHODS

Eligible studies were published in English between 1 January 2017 and 17 May 2021; evaluated for and identified symptom clusters 'de novo;' and included only adults being treated with primary or adjuvant chemotherapy. Studies were excluded if patients had advanced cancer or were receiving palliative chemotherapy; symptoms were measured after treatment; symptom clusters were pre-specified or a patient-centred analytic approach was used. For each study, symptom instrument(s); statistical methods and symptom dimension(s) used to create the clusters; whether symptoms were allowed to load on more than one factor; method used to assess for stability of symptom clusters and associations with secondary outcomes and biomarkers were extracted.

RESULTS

Twenty-three studies were included. Memorial Symptom Assessment Scale was the most common instrument and exploratory factor analysis was the most common statistical method used to identify symptom clusters. Psychological, gastrointestinal, and nutritional clusters were the most commonly identified clusters. Only the psychological cluster remained relatively stable over time. Only five studies evaluated for secondary outcomes.

DISCUSSION

While symptom cluster research has evolved, clear criteria to evaluate the stability of symptom clusters and standardised nomenclature for naming clusters are needed. Additional research is needed to evaluate the biological mechanism(s) for symptom clusters.

PROSPERO REGISTRATION NUMBER

CRD42021240216.

Cluster de sintomas: manejo e práticas avançadas em enfermagem oncológica

RESUMO Objetivo: Apresentar a definição de “cluster de sintomas” em pacientes com câncer e refletir sobre modelos teóricos, avaliação, desfechos e intervenções para manejo de sintomas, na perspectiva das práticas avançadas em enfermagem oncológica. Método: Estudo teórico-reflexivo que apresenta e discute possibilidades de manejo de “clusters de sintomas” por meio das práticas avançadas em enfermagem oncológica. Resultados: O termo “cluster de sintomas” pode ser definido como um conjunto de dois ou mais sintomas relacionados entre si. Os conceitos e modelos teóricos que podem ajudar na sua compreensão são: Teoria dos Sintomas Desagradáveis, Teoria do Manejo de Sintomas, conceito de autoeficácia e teoria do autocontrole dos sintomas. Os enfermeiros de prática avançada têm habilidades para realizar o manejo dos “clusters de sintomas”, otimizando os desfechos e influenciando positivamente a qualidade de vida de pacientes com câncer. Conclusão: Os enfermeiros de prática avançada reúnem as características essenciais para elaborar, implementar e avaliar protocolos de intervenções direcionadas ao manejo de “clusters de sintomas” em pacientes com câncer.

Symptom Clusters, Physical Activity, and Quality of Life: A Latent Class Analysis of Children During Maintenance Therapy for Leukemia

BACKGROUND

Children undergoing treatment for acute lymphocytic leukemia (ALL) report co-occurring symptoms of fatigue, sleep disturbances, and depression as a symptom cluster. Physical activity (PA) may influence symptom severity and quality of life (QOL).

OBJECTIVES

This study examined changes in symptoms and QOL during ALL maintenance in children categorized by symptom cluster and explored the influence of PA and symptoms on QOL.

METHODS

Self-report of fatigue, sleep disturbance, and depression; QOL; and PA were measured at the beginning and end of maintenance in 42 children aged 3 to 18 years with ALL. Children were categorized into symptom cluster groups based on measurements at the beginning of maintenance.

RESULTS

Two latent classes of symptom clusters (low and high) were identified with significant differences between groups in symptoms at both the beginning and end maintenance (P < .01). Each group's symptom levels did not change during maintenance. Quality-of-life was different between groups at both time points (P < .01) and did not improve. Children with low symptoms and high PA at the beginning of maintenance had better QOL as treatment ended compared with the physically active high-symptom group and the inactive high-symptom group (P < .01).

CONCLUSIONS

Children with higher symptoms did not experience an improvement with time. Symptom and PA levels may influence QOL at the end of treatment.

IMPLICATIONS FOR PRACTICE

Maintenance therapy is a long time (1.5 years) in a child's life. Symptom assessment is needed early in maintenance; interventions are needed for children with high levels.

Symptom Clusters in Head and Neck Cancer: A Systematic Review and Conceptual Model

OBJECTIVE

The two approaches to symptom-cluster research include grouping symptoms and grouping patients. The objective of this systematic review was to examine the conceptual approaches and methodologies used in symptom-cluster research in patients with head and neck cancer.

DATA SOURCES

Articles were retrieved from electronic databases (CINAHL, MEDLINE via Ovid, APA PsycINFO, Scopus, Embase, and Cochrane Central Register of Controlled Trials-CENTRAL), five grey literature portals, and Google Scholar. Seventeen studies met the eligibility criteria. Eight studies grouped symptoms to identify symptom clusters, of which two used qualitative methods. The number of symptom clusters ranged from two to five, and the number of symptoms in a cluster ranged from 2 to 11. Nine studies grouped patients based on their experiences with multiple symptoms. Cluster analysis and factor analysis were most commonly used. Despite variable names and composition of symptom clusters, synthesis revealed three prominent symptom clusters: general, head and neck cancer-specific, and gastrointestinal. Being female and quality of life were significantly associated with high symptom group or cluster severity. Biological mechanisms were sparsely examined.

CONCLUSION

Symptom cluster research in head and neck cancer is emerging. Consensus on nomenclature of a symptom cluster will facilitate deduction of core clinically relevant symptom clusters in head and neck cancer. Further research is required on understanding patients' subjective experiences, identifying predictors and outcomes, and underlying mechanisms for symptom clusters.

IMPLICATIONS FOR NURSING PRACTICE

Identification of clinically relevant symptom clusters would enable targeted symptom assessment and management strategies, thus improving treatment efficiencies and patient outcomes.

Guideline-Recommended Symptom Management Strategies That Cross Over Two or More Cancer Symptoms

PROBLEM IDENTIFICATION

Patients with cancer experience multiple symptoms, but current practice is driven by guidelines that address single symptoms. Identifying symptom management strategies recommended across two or more symptoms could relieve multiple symptoms and reduce patient burden.

LITERATURE SEARCH

The Oncology Nursing Society, National Comprehensive Cancer Network, and American Society of Clinical Oncology websites were searched to identify management guidelines for 15 symptoms.

DATA EVALUATION

The authors extracted symptom management strategies and recommendations. Recommendations were synthesized by symptom across the guidelines, and recommended strategies were compared across symptoms.

SYNTHESIS

Among 32 guidelines reviewed, a total of 88 symptom management strategies (41 pharmacologic, 47 nonpharmacologic) were recommended across two or more symptoms.

IMPLICATIONS FOR PRACTICE

Findings support the potential for coordinated selection of symptom management strategies that cross over multiple symptoms in a patient. Investigators should test these symptom management strategies in the context of co-occurring symptoms and develop guidelines that address multiple symptoms.

Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry: A network analysis

Background

Research into the clustering of symptoms may improve the understanding of the underlying mechanisms that affect survivors' symptom burden. This study applied network analyses in a balanced sample of cancer survivors to 1) explore the clustering of symptoms and 2) assess differences in symptom clustering between cancer types, treatment regimens, and short‐term and long‐term survivors.

Methods

This study used cross‐sectional survey data, collected between 2008 and 2018, from the population‐based Patient Reported Outcomes Following Initial Treatment and Long Term Evaluation of Survivorship registry, which included survivors of 7 cancer types (colorectal cancer, breast cancer, ovarian cancer, thyroid cancer, chronic lymphocytic leukemia, Hodgkin lymphoma, and non‐Hodgkin lymphoma). Regularized partial correlation network analysis was used to explore and visualize the associations between self‐reported symptoms (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire) and the centrality of these symptoms in the network (ie, how strongly a symptom was connected to other symptoms) for the total sample and for subgroups separately.

Results

In the total sample (n = 1330), fatigue was the most central symptom in the network with moderate direct relationships with emotional symptoms, cognitive symptoms, appetite loss, dyspnea, and pain. These relationships persisted after adjustments for sociodemographic and clinical characteristics. Connections between fatigue and emotional symptoms, appetite loss, dyspnea, and pain were consistently found across all cancer types (190 for each), treatment regimens, and short‐term and long‐term survivors.

Conclusions

In a heterogenous sample of cancer survivors, fatigue was consistently the most central symptom in all networks. Although longitudinal data are needed to build a case for the causal nature of these symptoms, cancer survivorship rehabilitation programs could focus on fatigue to reduce the overall symptom burden.

In a sample of 1330 survivors, fatigue is found to be the most central symptom (ie, the symptom most strongly connected to other symptoms) in the network with moderate direct relationships with emotional symptoms, cognitive symptoms, appetite loss, dyspnea, and pain. Connections between fatigue and emotional symptoms, appetite loss, dyspnea, and pain were consistently found across all cancer types (colorectal cancer, breast cancer, ovarian cancer, thyroid cancer, chronic lymphocytic leukemia, Hodgkin lymphoma, and non‐Hodgkin lymphoma, n = 190 for each group), treatment regimens, and short‐term and long‐term survivors.

Development and Validation of the Stroke Symptom Cluster Scale Among Korean Stroke Survivors: Mixed-Methods Design

PURPOSE

This study aimed to develop and validate the Stroke Symptom Cluster Scale for Korean Adults (SSCS-K) for stroke survivors.

DESIGN

An exploratory sequential study with a mixed-methods design was performed.

METHODS

In the development stage, a qualitative study with in-depth interviews was conducted with 27 stroke patients. The validation stage involved analyzing the psychometric properties from 288 stroke patients.

FINDINGS

The SSCS-K comprising 65 items in six dimensions (mobility, cognition, sensory, mood, communication, and swallowing difficulty) demonstrated acceptable internal consistency (Cronbach's α = .92-.94). Confirmatory factor analyses with a six-factor solution showed that it explained 62% of the variance in stroke symptoms. The concurrent validity was confirmed with the Stroke-Specific Quality of Life Scale (r = .38-.83, p < .001).

CONCLUSION

The SSCS-K has strong psychometric properties as a measure to assess clustered symptoms in stroke survivors during their long-term rehabilitation.

CLINICAL RELEVANCE

Rehabilitation nurses may consider the SSCS-K as a useful tool for assessing symptoms of stroke survivors.

Maternal Mental Health Symptoms and Clusters Predict Toddler Sleep in Low-Income Homes

The authors examined the association of maternal mental health symptoms and symptom clusters with the sleeping behaviors of toddlers living in low-income homes. The sample is comprised of 174 racially diverse mother and toddler (15-19 months old) dyads who were participating in a longitudinal birth cohort study. Dyads were initially recruited from Women, Infant, and Children clinics in a Midwestern county of the United States. Maternal mental health symptoms were measured with self-reports of depression (Center for Epidemiological Studies-Depression), parenting stress (Parenting Stress Index Very Short Form), and parenting self-efficacy. Toddler sleeping behaviors were measured with an adaptation of the Tayside Children's Sleep Questionnaire that assessed toddler difficulties in initiating or maintaining sleep (DIMS). Maternal mental health symptom clusters were identified with latent profile analysis and toddler DIMS were regressed on maternal mental health symptoms. We found that 1 SD worse maternal depression, parenting stress, or parenting self-efficacy predicted 0.18-0.24 SD worse toddler DIMS (p < .05). Moreover, we found that the cluster of adverse maternal mental health symptoms predicted nearly 0.75 SD worse toddler DIMS as compared with the cluster of good maternal mental health symptoms (p < .05). These findings provide insight into how maternal mental health symptom clusters may be important in understanding sleep behaviors in early toddlerhood, a sensitive period of sleep development, and underscore the need to support mothers with co-occurring adverse mental health symptoms, as their children may be at higher risk for DIMS.

Symptom clusters and quality of life in persons with multiple sclerosis across the lifespan

PURPOSE

To describe symptom clusters based on severity of co-occurring symptoms among adults with multiple sclerosis (MS) by age groups and to further examine symptom clusters as a correlate of quality of life (QOL) by age groups.

METHODS

This cross-sectional study enrolled persons with MS between 20 and 79 years of age who completed measures of fatigue, depression, anxiety, sleep quality, and QOL using the 36-Item Short Form Health Survey. Bivariate correlation and partial correlation analyses examined associations among symptoms, QOL, and MS characteristics. K-means cluster analyses determined symptom clusters among the full sample and pre-determined age groups (i.e., 20-39, 40-59, and 60-79). One-way ANOVAs examined differences in QOL among clusters for the overall sample and by age groups.

RESULTS

Among the overall sample of 205 participants, symptoms were significantly correlated with QOL and three distinct clusters were identified and differentiated by the magnitude of symptom experience (i.e., mild, moderate, and severe). Results were consistent among young and middle-aged adults; however, among older adults two severe sleep problem clusters were identified that were distinguished by moderate versus severe fatigue, depression, and anxiety. ANOVAs among the overall sample indicated that the three symptom clusters varied significantly for both physical component scores, F(2, 202) = 12.03, p < .001, η2 = .10, and mental component scores, F(2, 202) = 137.92, p < .001, η2 = .58; severe symptom cluster was associated with worse QOL. Patterns in the age subgroup ANOVAs were consistent.

CONCLUSIONS

Given the strong association between severity of symptom clusters and QOL, approaches for targeting co-occurring symptoms are critically needed.

Symptom Clusters Predictive of Quality of Life Among Jordanian Women with Breast Cancer

OBJECTIVES

This study was conducted to explore symptom clusters among women with breast cancer in Jordan.

DATA SOURCES

A cross-sectional survey of 516 women with breast cancer who were recruited from three hospitals.

CONCLUSION

This study demonstrated that women with breast cancer experienced several symptoms at the same time. These symptoms tend to cluster in five main groups, and patients experiencing the psychological, nausea and vomiting, and pain clusters are expected to have a lower mean score of quality of life.

IMPLICATIONS FOR NURSING PRACTICE

Nurses need to assess and manage symptoms as clusters to improve the quality of life of women with breast cancer. Symptoms clusters should guide symptoms management practice and be given a priority equal to the active treatment of cancer. Symptoms management and cancer treatment should be started simultaneously.

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.

Symptom Profiles of Latina Breast Cancer Survivors: A Latent Class Analysis

BACKGROUND

Symptom research among Latinas with breast cancer is limited-especially as it relates to multiple co-occurring symptoms.

OBJECTIVE

The aim of the study was to identify subgroups (latent classes) of Latinas who have distinct symptom profiles while receiving radiation, chemotherapy, and/or hormonal therapy for breast cancer.

METHODS

This secondary analysis included intake data from three randomized trials of supportive care psychosocial interventions for Latinas treated for breast cancer (n = 290). Prevalence of 12 symptoms-measured using the General Symptom Distress Scale-was entered into the latent class analysis to identify classes of women with different symptom profiles.

RESULTS

Most of the participants had Stage II or III disease, and 81% reported receiving chemotherapy. On average, women reported 4.2 (standard deviation [SD] = 3) symptoms with an overall symptom distress score of 6.4 (SD = 2.5) on a 1-10 scale, with 10 being most distressing. Latent class analysis resulted in three classes that were labeled based on symptoms with the highest prevalence. Class 1 (n = 192) was "Disrupted Sleep and Tired," Class 2 (n = 74) was "Tired," and Class 3 (n = 24) was "Pain, Disrupted Sleep, and Tired." Depression, anxiety, and difficulty concentrating had moderate prevalence in each of the three classes.

DISCUSSION

Beyond the core six symptoms (depression, anxiety, fatigue, pain, disrupted sleep, difficulty concentration), the classes differed in the prevalence of other burdensome symptoms (e.g., nausea, vomiting, constipation), which provide implications for treatment. Thus, it is important to assess for the full range of symptoms so that supportive care interventions can be tailored for the distinct symptom profiles of Latinas with breast cancer.

Symptom clusters in head and neck cancer patients with endotracheal tube: Which symptom clusters are independently associated with health-related quality of life?

PURPOSE

The point of view of symptom clusters (SCs) may develop an efficient symptom management strategy to enhance health-related quality of life (HRQoL) in head and neck (HNC) patients with endotracheal tube (ETT). The study aims to investigate the possible SCs in HNC patients with ETT and determine whether there was an independent relationship between one or more SCs and HRQoL.

METHODS

A cross-sectional study design was adopted, and 203 HNC patients with ETT were recruited. They took measurements of General Information Questionnaire, MD Anderson Symptom Inventory-Head & Neck, and Twelve-Item Short-Form Health Survey (SF-12). Spearman correlations, partial correlations, and hierarchical cluster analysis were performed to determine latent number of SCs, and covariance analyses were used to determine independent associations between SCs and SF-12. This study followed STROBE Statement.

RESULTS

Pain SCs (pain, distressed, short of breath, and sadness), fatigue SCs (fatigue/weakness, restless, and sleepy), digestive SCs (appetite loss, constipation, and nausea), HNC-specific SCs (dry mouth and mucus), and tracheostomy-related SCs (difficulty swallowing and difficulty with voice and speech) were found. After adjusting covariant variables, this study found independent relationships of pain SCs and fatigue SCs with physical component summary of SF-12, and between fatigue SCs and mental component summary of SF-12.

CONCLUSIONS

Multiple SCs were found in those HNC patients. Pain SCs and fatigue SCs were independently associated with HRQoL. In process of caring HNC patients with ETT, it is vital to focus on SCs, especially on pain SCs and fatigue SCs, which might effectively improve patients' HRQoL.

CLINICAL EVALUATION AND PATTERN OF SYMPTOMS IN COLORECTAL CANCER PATIENTS

BACKGROUND

Colorectal cancer is the third most common type of cancer in the world and the increased survival of the colorectal cancer population is very significant. Thus, it becomes relevant to study the symptoms associated with the progression of the disease and treatment, for proper clinical management.

OBJECTIVE

To describe the clinical and epidemiological profile of colorectal cancer patients and to identify the most prevalent signs and symptoms patterns.

METHODS

Cross-sectional study evaluating the prevalence of symptoms in 348 colorectal cancer patients admitted to a referral oncology hospital. We applied MSAS-BR scale and, through factor analysis with principal componente analysys, we performed the grouping of symptoms.

RESULTS

There was a predominance of men, aged 60 years or older, married, white, with high school, moderately differentiated tumor, stage III/IV disease, colon cancer and no distant metastasis. The most prevalent symptoms were weight loss (67.53%) and the least prevalent were mouth sores (2.01%). The groupings of symptoms established were "fatigue and psychic symptoms", "gastrointestinal symptoms", "self-perceptive symptoms" and "general symptoms", which described 80% of the symptoms presented.

CONCLUSION

We evidenced the importance of identifying these symptoms clusters in order to improve strategies for clinical management in patients with colorectal cancer.

Symptom clusters in hospitalized older adults: Characteristics and outcomes

Hospital care in medical patients relies mostly on objective measures with limited assessment of subjective symptoms. We subgrouped 331 hospitalized older adults with medical diagnosis (age 75.5 ± 7.1) according to the severity of multiple symptoms to explore if these subgroups differed in health-related characteristics on admission and functional outcomes one month post-discharge. Cluster analysis identified three subgroups based on experiences with five highly distressing symptoms (fatigue, dyspnea, dizziness, sleep disturbance, pain): low levels of all symptoms, high levels of all symptoms; moderate levels of four symptoms with high dyspnea. Belonging in different subgroups was accompanied by different levels of cognitive and mental, but not physical or health status. Patients in the subgroup "Moderate Levels with High Dyspnea" had significantly lower risk of decline in post-discharge instrumental activities of daily living than other subgroups. Better understanding of older hospitalized adults' symptom profiles may yield important information on health condition and recovery.

Interventions for Managing a Symptom Cluster of Pain, Fatigue, and Sleep Disturbances During Cancer Survivorship: A Systematic Review

PROBLEM IDENTIFICATION

More than 40% of cancer survivors experience a symptom cluster of pain, fatigue, and sleep disturbances, which can greatly reduce quality of life.

LITERATURE SEARCH

A literature search was performed using CINAHL®, Google ScholarTM, PubMed®, PsycINFO®, and Web of Science. Articles included randomized controlled trials of interventions aimed at managing a symptom cluster of pain, fatigue, and sleep disturbances.

DATA EVALUATION

11 studies were assessed for quality, risk of bias, cancer type, sample size, intervention type, duration, and setting. For an intervention to be considered effective, the reduction of symptom severity or distress had to be statistically significant.

SYNTHESIS

Data from the 11 studies were summarized. Four interventions were found to be effective in managing the symptom cluster, but evidence on long-term effectiveness was insufficient.

IMPLICATIONS FOR NURSING

Oncology nurses can assess the patterns and characteristics of simultaneous symptoms experienced by cancer survivors and administer interventions to relieve symptom burden and improve quality of life.

Symptom clusters in newly diagnosed glioma patients: which symptom clusters are independently associated with functioning and global health status?

Background

Symptom management in glioma patients remains challenging, as patients suffer from various concurrently occurring symptoms. This study aimed to identify symptom clusters and examine the association between these symptom clusters and patients’ functioning.

Methods

Data of the CODAGLIO project was used, including individual patient data from previously published international randomized controlled trials (RCTs) in glioma patients. Symptom prevalence and level of functioning were assessed with European Organisation for Research and Treatment of Cancer (EORTC) quality of life QLQ-C30 and QLQ-BN20 self-report questionnaires. Associations between symptoms were examined with Spearman correlation coefficients and partial correlation networks. Hierarchical cluster analyses were performed to identify symptom clusters. Multivariable regression analyses were performed to determine independent associations between the symptom clusters and functioning, adjusted for possible confounders.

Results

Included in the analysis were 4307 newly diagnosed glioma patients from 11 RCTs who completed the EORTC questionnaires before randomization. Many patients (44%) suffered from 5–10 symptoms simultaneously. Four symptom clusters were identified: a motor cluster, a fatigue cluster, a pain cluster, and a gastrointestinal/seizures/bladder control cluster. Having symptoms in the motor cluster was associated with decreased (≥10 points difference) physical, role, and social functioning (betas ranged from −11.3 to −15.9, all P < 0.001), independent of other factors. Similarly, having symptoms in the fatigue cluster was found to negatively influence role functioning (beta of −12.3, P < 0.001), independent of other factors.

Conclusions

Two symptom clusters, the fatigue and motor cluster, were frequently affected in glioma patients and were found to independently have a negative association with certain aspects of patients’ functioning as measured with a self-report questionnaire.

Association between Health Problems and Turnover Intention in Shift Work Nurses: Health Problem Clustering

Shift work nurses experience multiple health problems due to irregular shifts and heavy job demands. However, the comorbidity patterns of nurses’ health problems and the association between health problems and turnover intention have rarely been studied. This study aimed to identify and cluster shift work nurses’ health problems and to reveal the associations between health problems and turnover intention. In this cross-sectional study, we analyzed data from 500 nurses who worked at two tertiary hospitals in Seoul, South Korea. Data, including turnover intention and nine types of health issues, were collected between March 2018 and April 2019. Hierarchical clustering and multiple ordinal logistic regressions were used for the data analysis. Among the participants, 22.2% expressed turnover intention and the mean number of health problems was 4.5 (range 0–9). Using multiple ordinal logistic regressions analysis, it was shown that sleep disturbance, depression, fatigue, a gastrointestinal disorder, and leg or foot discomfort as a single health problem significantly increased turnover intention. After clustering the health problems, four clusters were identified and only the neuropsychological cluster—sleep disturbance, fatigue, and depression—significantly increased turnover intention. We propose that health problems within the neuropsychological cluster must receive close attention and be addressed simultaneously to decrease nurse’s turnover intentions.

Symptom Clusters' Content, Stability and Correlation with the Quality of Life in a Heterogeneous Group of Cancer Patients: A Large-Scale Longitudinal Study

Cancer-related symptoms can negatively affect the quality of life, hinder or delay treatment, and increase suffering. This study aimed to explore symptom clusters among Jordanian cancer patients. A longitudinal survey design was used. The sample consisted of 1280 cancer patients treated in three selected hospitals. Two-thirds of the participants were female (63.5%) with a mean age of 52.7 SD 13.8 years and 40.3% had breast cancer. Five clusters were identified, the first was the psychological cluster of eight symptoms; the second was the treatment side-effects cluster consisting of ten symptoms; the third was the nausea and vomiting cluster comprising four symptoms; the fourth was the pain cluster comprising four symptoms; and last was the fatigue cluster, with three symptoms. Cancer patients through the journey of cancer treatment have several symptoms that tend to occur in five clusters which are negatively correlated with their quality of life.

The Correlation of Symptom Clusters and Functional Performance in Adult Acute Leukemia Patients Under Chemotherapy

BACKGROUND

Adult acute leukemia (AL) patients who receive chemotherapy usually experience multiple symptoms during the treatment course. The symptom clusters (SCs) as well as subsets of concurrent symptoms in AL patients have not yet been demonstrated.

OBJECTIVE

To investigate the SCs of adult AL patients who were receiving chemotherapy and to determine their correlations with functional performance.

METHODS

A total of 132 hospitalized adult AL patients were included in this study. A cross-sectional survey aimed to examine symptoms and functional performance was conducted. The patients' symptoms were assessed using the Chinese version of the Condensed Memorial Symptom Assessment Scale, and functional performance was evaluated through activities of daily living and quality of life.

RESULTS

We identified 4 SCs in adult AL patients: psychological SC, pain-fatigue-sleep SC, dry mouth-constipation SC, and nutrition-impaired SC. The psychological SC was the most common and most distressing SC. The different SCs were each differentially correlated with patient characteristics. The distress of the psychological SC, pain-fatigue-sleep SC, and nutrition-impaired SC was adversely correlated with functional performance.

CONCLUSIONS

Adult AL patients undergoing chemotherapy experience multiple symptoms that can be further categorized into 4 SCs. The distress from some SCs is negatively associated with patients' functional performance.

IMPLICATIONS FOR PRACTICE

Symptom burden remains a major problem for adult AL patients undergoing chemotherapy. Identifying SCs of AL patients should be the basis for accurate and cost-effective interventions. Personalized SC management may improve the functional performance and healthcare quality of adult AL patients.

Facing the large variety of life-limiting conditions in children

Life-limiting conditions in children in specialized pediatric palliative care (PPC) are manifold. The "Together for Short Lives" (TfSL) association established four disease categories, which represent the most common illness trajectories. Better understanding the palliative care needs and symptoms of children within these TfSL groups will result in improved anticipation of clinical problems and tailored care. During this retrospective single-center cohort study, 198 children, adolescents, and young adults (CAYAs) were in PPC. Mean age at referral was 8.7 years (range 0.0-25.0), mean duration of care 355 days (range 1-2754). One hundred six (53.5%) CAYAs died during the study period. Sixty-five (32.8%) CAYAs were assigned to TfSL-1, 13 (6.6%) to TfSL-2, 49 (24.7%) to TfSL-3, and 71 (35.9%) to TfSL-4. Home visits were conducted on average every 9.6 days in TfSL-1, 18.9 days in TfSL-2, 31.7 days in TfSL-3, and 31.8 days in TfSL-4 (p value < 0.01).Conclusions: Intensity of palliative care significantly differed between the TfSL groups. Neurological and gastrointestinal symptoms were most prominent across all TfSL groups. Symptom cluster analysis showed distinct clusters in TfSL-1 (cluster 1, fatigue/lack of appetite/nausea/somnolence; cluster 2, dyspnea/fear/myoclonus/seizures/spasticity) and TfSL-3/4 (cluster 1, spasticity; cluster 2, all other symptoms).What is Known:• The four TfSL (together for short lives) groups represent the four most common illness trajectories of pediatric palliative care patients.• Better understanding the palliative care needs and symptoms of children within these four TfSL groups will result in improved anticipation of clinical problems and tailored care.What is New:• In our study, TfSL-1 represented the largest individual group of patients, also requiring the most intensive care (defined by the number of visits per days of care).• Symptom cluster analysis revealed distinct symptom clusters in TfSL-1 and TfSL-3/4, which can be used to anticipate clinically common challenges in these patients.

Use of Cluster Analysis to Delineate Symptom Profiles in an Ehlers-Danlos Syndrome Patient Population

CONTEXT

The Ehlers-Danlos Syndromes (EDSs) are a set of rare heritable disorders of connective tissue, characterized by defects in the structure and synthesis of extracellular matrix elements that lead to a myriad of problems including joint hypermobility and skin abnormalities. Because EDS affects multiple organ systems, defining clear boundaries and recognizing overlapping clinical features shared by disease phenotypes is challenging.

OBJECTIVES

The objective of this study was to seek evidence of phenotypic subgroups of patients with distinctive symptom profiles and describe these resulting subgroups.

METHODS

Data were extracted from a repository assembled 2001-2013 by the National Institute on Aging Intramural Research Program. Agglomerative hierarchical clustering was used to form distinct subgroups of patients with respect to the domains of pain, physical and mental fatigue, daytime sleepiness, and nighttime sleep. Domains were selected based on literature review, clinician expertise, and guidance from patient advisors.

RESULTS

One hundred seventy-five patients met all inclusion criteria. Three subgroups were identified. The Pain Dominant subgroup (39 patients) had the highest mean pain values, but lowest mean values of other symptoms. The High Symptom Burden subgroup (71 patients) had high mean values in all domains. The Mental Fatigue subgroup (65 patients) had a high mean value for mental fatigue and daytime sleepiness, but a lower mean value for pain.

CONCLUSION

The subgroups aligned with clinical observation of the heterogeneous nature of EDS, with overlapping symptoms between subtypes and a wide divergence in degree of symptoms within subtypes. This exploratory study helps characterize the various phenotypes and comorbidities of patients with EDS.

Physical Activity, the Childhood Cancer Symptom Cluster-Leukemia, and Cognitive Function: A Longitudinal Mediation Analysis

BACKGROUND

Children undergoing leukemia treatment report co-occurring symptoms of fatigue, sleep disturbances, pain, nausea, and depression as a symptom cluster. Physical activity (PA) is essential for development and may influence symptom severity. Children with leukemia are at risk of cognitive impairments from central nervous system therapies. Using a longitudinal parallel-process model, relationships among function and symptom clusters were explored.

OBJECTIVE

This study examined the longitudinal mediation effects of PA on cognition via a symptom cluster during leukemia treatment.

METHODS

Symptoms, PA, and cognitive function of 327 children aged 3 to 18 years were measured over 4 intervals during the first year of leukemia treatment. Children 7 years or older self-reported and parents reported for younger children. Parents completed cognitive function measurements for all children. The influence of the first time point and the subsequent change between all 4 time points of PA on the symptom cluster were explored. Analysis determined whether the symptom cluster mediated the effect of cognition over the treatment period.

RESULTS

Patients with a higher PA at time 1 reduced their symptom cluster severity over the measurements. However, when PA increased over the measurements, symptom cluster severity also increased. When the symptom cluster was more severe at time 1, cognitive function was lower at time 1, and cognitive function decreased over time. When symptoms became more severe over time, cognitive function declined.

CONCLUSIONS

The symptom cluster acted as a mediator between PA and cognition.

IMPLICATIONS FOR PRACTICE

Symptom management during treatment may be an additional strategy for protecting cognitive function.

Symptom-based latent classes of persons with irritable bowel syndrome

A large amount of interindividual variability exists in symptom experiences of persons with irritable bowel syndrome (IBS). Thus, consideration of multiple symptoms to identify distinct symptom subgroups may be useful in directing personalized health strategies for symptom management. We aimed to identify latent classes (i.e., subgroups) of persons with IBS who share similar patterns of symptoms using symptom-related variables (six groups of daily diary symptoms, cognitive beliefs about IBS, and IBS quality of life [QOL]); and to examine how subgroups differed in patient characteristics. Data were derived from a baseline assessment of men and women enrolled in two cognitively-focused intervention trials (N = 332). Using latent class analysis, four latent classes were identified: Class 1 (low symptoms and good QOL, n = 153), Class 2 (low symptoms and moderate QOL, n = 106), Class 3 (high symptoms with diarrhea and poor QOL, n = 38), and Class 4 (high symptoms with low diarrhea and moderate QOL, n = 35). Diarrhea, being female, less formal education, unemployment, and previous history of major depressive disorder were associated with membership in Class 3. Using these distinct symptom profiles, the next step is to explore underlying mechanisms accounting for symptom burden with the goal of designing tailored interventions to reduce that burden.