Evaluation of a psychoneurological symptom cluster in patients with breast or digestive cancer: a longitudinal observational study.

BACKGROUND: A psychoneurological symptom cluster composed of cancer-related fatigue, emotional distress, sleep difficulties, and pain is very common among patients with cancer. Cognitive difficulties are also frequently associated with this cluster. Network analyses allow for an in-depth understanding of the relationships between symptoms in a cluster. This paper details the study protocol of a longitudinal assessment of the psychoneurological symptom cluster in two distinct cohorts: breast cancer and digestive cancer survivors, using network analyses. METHODS: Over two years, the symptoms involved in the psychoneurological symptom cluster, along with other common symptoms (e.g., digestive symptoms, financial difficulties) and variables (i.e., self-compassion, coping strategies) will be assessed in two cohorts: breast cancer survivors (N = 240) and digestive cancer survivors (N = 240). Online questionnaires will be completed at baseline, then 6, 12 and 24 months later. Network analyses will be used to assess the configuration of the symptom cluster at each measurement time and in each cohort. Comparison of networks between two measurement times or between the two cohorts will also be done with network comparison tests. DISCUSSION: This study will enable a better understanding of the relationships between common symptoms endured by patients with cancer. The results will be employed to develop more cost-effective interventions which, ultimately, will significantly improve the quality of life of patients with breast or digestive cancer. TRIAL REGISTRATION: ClinicalTrials.gov (NCT05867966). Registered on the 27th of April 2023. url: https://classic. CLINICALTRIALS: gov/ct2/show/NCT05867966 .

The change of symptom clusters in gastric cancer patients during the perioperative period: a longitudinal study.

AIM AND OBJECTIVES: The purpose of this study was to describe the number, type and trajectory of symptom clusters during the perioperative period in patients with gastric cancer at four different time points. The study also aimed to identify the changes and consistency of these symptom clusters over time. DESIGN: This was a longitudinal study. METHODS: This study was conducted in a tertiary cancer hospital with 205 patients with gastric cancer. The M.D. Anderson Symptom Inventory Gastrointestinal Cancer Module was used to assess the incidence and severity of symptom clusters. Exploratory factor analysis was used to extract symptom clusters. RESULTS: The study identified four symptom clusters in patients with gastric cancer during the perioperative period: gastrointestinal symptom cluster, physical symptom cluster, psychological symptom cluster, and sleep disturbance symptom cluster. These clusters were observed across two to four time points. CONCLUSION: The findings of this study provide scientific evidence for medical staff and researchers to better understand the symptoms of patients with gastrointestinal cancer during the perioperative period. These findings can help develop individualized interventions for managing symptoms. RELEVANCE TO CLINICAL PRACTICE: Gastric cancer patients suffered from various symptom clusters, which lasted from one day before surgery to one month after surgery. They should be given careful consideration by clinical staff.

Self-report of symptom cluster experiences in cancer patient-caregiver dyads.

PURPOSE: Symptom clusters have important health implications in the context of cancer, but the symptom cluster experiences of cancer caregivers and patient-caregiver dyads are not well studied. To date, most studies report statistically derived symptom clusters among patients and fail to consider the caregivers' experience. This study aimed to assess and characterize self-reported symptom cluster experiences in cancer patient-caregiver dyads. METHODS: We recruited 30 patient-caregiver dyads from the outpatient oncology clinics at a Comprehensive Cancer Center in the Midwestern U.S. Participants completed web-based surveys reporting their symptom clusters at weekly intervals over 8 weeks of cancer treatment. RESULTS: Among 48 eligible dyads, 30 (63%) agreed to participate, 29 provided data, and ≥ 80% (24 patients, 26 caregivers) completed the study. Twenty-eight patients (97%) and twenty-two caregivers (76%) reported experiencing symptoms in clusters. There was substantial variability in the symptoms reported, perceived causality, and directional relationships among symptoms, however both patients' and caregivers' frequently described symptom clusters with psychoneurologic components (co-occurring pain, fatigue, sleep disturbance, anxiety, depression, lack of appetite and/or cognitive disturbance). Symptom clusters were perceived to have a moderate impact on patients' daily lives and a mild-to-moderate impact on caregivers' daily lives. CONCLUSION: Dyad members experienced and successfully self-reported symptom clusters, with psychoneurologic symptom clusters prevalent among both patients and their caregivers. Self-report of symptom cluster experiences provides unique insight relevant to clinical management. Findings provide foundational support for development and testing of dyad-based interventions to mitigate symptom clusters and their negative impact on daily life among cancer-patient caregiver dyads.

Study of symptom clusters in brain tumor patients 2 weeks after craniotomy.

BACKGROUND: This study aimed to identify potential symptom clusters among primary brain tumor patients using factor analysis. Understanding these clusters enables better-targeted interventions post-craniotomy. METHODS: A total of 211 participants visiting Department of Neurosurgery at Shanghai Tenth People's Hospital for proposed surgical treatment between January 2021 and March 2022 were enrolled. Two weeks after craniotomy, the patients' symptoms were measured using MDASI-BT (M.D. Anderson Symptom Inventory Brain Tumor Module), and factor analysis was performed to identify symptom clusters. RESULTS: A total of three symptom clusters, i.e., symptom cluster 1, symptom cluster 2, and symptom cluster 3, were identified. Among them, symptom cluster 1 represented the fatigue-related symptom cluster, including fatigue, lethargy, dry mouth, pain, and sleep disturbance (Cronbach's α = 0.742); symptom cluster 2 represented the gut-brain axis symptom cluster, including loss of appetite, weakness in one side of the body, and change in bowel habits (Cronbach's α = 0.532); and symptom cluster 3 represented the self-image symptom cluster, including change in appearance, sadness, and distress (Cronbach's α = 0.547). CONCLUSION: This study identified three potential symptom clusters among primary brain tumor patients. Understanding these clusters could well contribute to earlier interventions and improved quality of care.

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.

Symptom clusters and network analysis of patients with intermediate and advanced liver cancer treated with targeted immunotherapy.

BACKGROUND: This study aims to identify symptom clusters in patients with intermediate and advanced liver cancer receiving targeted immunotherapy, focusing on core and bridge symptoms to establish a foundation for precise symptom management. METHODS: This study used a cross-sectional survey and utilized convenience sampling from May 2023 to January 2024 at a third-class hospital in Shanghai, China. The severity of symptoms in liver cancer patients during treatment was evaluated using the Memorial Symptom Assessment Scale. Network analysis was employed to depict the interrelation of symptom clusters and identify core and bridge symptoms. RESULTS: The symptoms were classified by severity into five clusters: oral, gastrointestinal, fatigue-related, body image, and pain-sleep. Within the symptom network, the core symptoms were pain, "I don't look like myself," and nausea, while the critical bridge symptoms included pain, itching, and feeling bloated. The strongest connections were observed between nausea and vomiting, followed by taste changes and dry mouth, as well as weight loss and "I don't look like myself." CONCLUSION: In patients receiving targeted immunotherapy for intermediate and advanced liver cancer, multiple symptoms can emerge simultaneously, forming interconnected clusters. By identifying and intervening in core and bridge symptoms, personalized management strategies can be developed to relieve other symptoms and disrupt connections between symptom clusters, thereby enhancing symptom management efficacy. This study has significant clinical and research implications, offering new insights to improve patients' quality of life and treatment outcomes.

Symptom clusters and impact on quality of life in lung cancer patients undergoing chemotherapy.

PURPOSE: To identify symptom clusters (SCs) in lung cancer patients undergoing chemotherapy and explore their impact on health-related quality of life (HRQoL). METHODS: Patients were invited to complete the Chinese version of the M.D. Anderson Symptom Inventory with the Lung Cancer Module and the Quality of Life Questionnaire-core 30. Network analysis was employed to identify SCs. The associations between SCs and each function of HRQoL were examined using the Pearson correlation matrix. Multiple linear regression was applied to analyze the influencing factors of each function of HRQoL. RESULTS: A total of 623 lung cancer patients who were receiving chemotherapy were recruited. The global health status of lung cancer patients was 59.71 ± 21.09, and 89.73% of patients developed symptoms. Three SCs (Somato-psychological SC, Respiratory SC, and Gastrointestinal SC) were identified, and Somato-psychological SC and Gastrointestinal SC were identified as influencing factors for HRQoL in lung cancer patients. CONCLUSION: Most lung cancer patients who undergo chemotherapy experience a range of symptoms, which can be categorized into three SCs. The Somato-psychological SC and Gastrointestinal SC negatively impacted patients' HRQoL. Health care providers should prioritize monitoring these SCs to identify high-risk patients early and implement targeted preventive and intervention measures for each SC, aiming to alleviate symptom burden and enhance HRQoL.

Patients' and Clinicians' Perceptions of the Clinical Utility of Predictive Risk Models for Chemotherapy-Related Symptom Management: Qualitative Exploration Using Focus Groups and Interviews.

BACKGROUND: Interest in the application of predictive risk models (PRMs) in health care to identify people most likely to experience disease and treatment-related complications is increasing. In cancer care, these techniques are focused primarily on the prediction of survival or life-threatening toxicities (eg, febrile neutropenia). Fewer studies focus on the use of PRMs for symptoms or supportive care needs. The application of PRMs to chemotherapy-related symptoms (CRS) would enable earlier identification and initiation of prompt, personalized, and tailored interventions. While some PRMs exist for CRS, few were translated into clinical practice, and human factors associated with their use were not reported. OBJECTIVE: We aim to explore patients' and clinicians' perspectives of the utility and real-world application of PRMs to improve the management of CRS. METHODS: Focus groups (N=10) and interviews (N=5) were conducted with patients (N=28) and clinicians (N=26) across 5 European countries. Interactions were audio-recorded, transcribed verbatim, and analyzed thematically. RESULTS: Both clinicians and patients recognized the value of having individualized risk predictions for CRS and appreciated how this type of information would facilitate the provision of tailored preventative treatments or supportive care interactions. However, cautious and skeptical attitudes toward the use of PRMs in clinical care were noted by both groups, particularly in relationship to the uncertainty regarding how the information would be generated. Visualization and presentation of PRM information in a usable and useful format for both patients and clinicians was identified as a challenge to their successful implementation in clinical care. CONCLUSIONS: Findings from this study provide information on clinicians' and patients' perspectives on the clinical use of PRMs for the management of CRS. These international perspectives are important because they provide insight into the risks and benefits of using PRMs to evaluate CRS. In addition, they highlight the need to find ways to more effectively present and use this information in clinical practice. Further research that explores the best ways to incorporate this type of information while maintaining the human side of care is warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT02356081; https://clinicaltrials.gov/study/NCT02356081.

Exploring symptom clusters in Chinese patients with peritoneal dialysis: a network analysis.

BACKGROUND: In recent years, the research on symptom management in peritoneal dialysis (PD) patients has shifted from a single symptom to symptom clusters and network analysis. This study collected and evaluated unpleasant symptoms in PD patients and explored groups of symptoms that may affect PD patients with a view to higher symptom management. METHODS: The symptoms of PD patients were measured using the modified Dialysis Symptom Index. The symptom network and node characteristics were assessed by network analysis, and symptom clusters were explored by factor analysis. RESULTS: In this study of 602 PD patients (mean age 47.8 ± 16.8 years, 47.34% male), most had less than 2 years of dialysis experience. Five symptom clusters were obtained from factor analysis, which were body symptom cluster, gastrointestinal symptom cluster, mood symptom cluster, sexual disorder symptom cluster, and skin-sleep symptom cluster. Itching and decreased interest in sex may be sentinel symptoms, and being tired or lack of energy and feeling anxious are core symptoms in PD patients. CONCLUSIONS: This study emphasizes the importance of recognizing symptom clusters in PD patients for better symptom management. Five clusters were identified, with key symptoms including itching, decreased interest in sex, fatigue, and anxiety. Early intervention focused on these symptom clusters in PD patients holds promise for alleviating the burden of symptoms.

Symptom clusters and sentinel symptoms in breast cancer survivors based on self-reported outcomes:A cross-sectional survey.

AIM: To investigate symptom clusters and sentinel symptoms in breast cancer survivors based on self-reported outcomes, explore the impact of sentinel symptoms on patients' quality of life and psychological distress, provide a basis for implementing accurate symptom management. DESIGN: A cross-sectional survey. METHODS: The study was conducted from September 2021 to December 2022. We recruited 281 patients who were re-examined in an outpatient department of a tertiary hospital in Hebei Province. The European Organization for the Research and Treatment of Cancer (EORTC) Quality-of-Life Questionnaire - Core30 (QLQ-C30), the EORTC Quality-of-Life Questionnaire Breast Cancer - 23 (QLQ-BR23), the Hospital Anxiety and Depression Scale (HADS) were used to conduct the survey. Symptom clusters were explored using principal component analysis, sentinel symptoms were explored using the Apriori algorithm. Correlation analysis was used to explore the relationship between sentinel symptoms and quality of life, correlation with psychological distress. This paper adhered to the STROBE guidelines. RESULTS: Breast cancer survivors have a wide range of self-reported symptoms in the form of four symptom clusters: a fatigue symptom cluster, a gastrointestinal symptom cluster, a sickness symptom cluster and a surgical trauma-related symptom cluster. Three sentinel symptoms were explored: pain, alopecia and limited function of the upper limbs. Except for sexual function, all of the sentinel symptoms were negatively correlated with patients' quality of life and positively correlated with psychological distress (p < .05). CONCLUSIONS: Breast cancer survivors have a variety of symptoms in the form of four symptom clusters. Pain, alopecia and limited function of the upper limbs are the sentinel symptoms, which affect patients' quality of life and psychological distress.

Subsyndromes and symptom clusters: Multilevel factor analysis of behavioral and psychological symptoms of dementia with intensive longitudinal data.

INTRODUCTION: Behavioral and psychological symptoms in dementia (BPSD) are dynamic phenomena with a high amount of intraindividual variability. We applied a multilevel framework to identify subsyndromes (between-person factors) that represent clinically relevant profiles of BPSD and identify symptom clusters (within-person factors) that represent contextually driven daily symptom experiences. METHODS: This study used an intensive longitudinal design in which 68 co-residing family caregivers to persons living with dementia were recruited to proxy report on their care recipient's daily symptom experiences of 23 different BPSD for eight consecutive days (n = 443 diaries). A multilevel exploratory/confirmatory factor analysis was used to account for nested data and separate within-person variances from between-level factor estimates. RESULTS: Exploratory factor analysis identified a 4-between 3-within factor structure based on fit statistics and clinical interpretability. DISCUSSION: This study offers major methodological and conceptual advancements for management of BPSD within Alzheimer's disease and related dementias by introducing two related but distinct concepts of subsyndromes and symptom clusters. HIGHLIGHTS: Because behavioral and psychological symptoms of dementia (BPSD) are dynamic temporal phenomenon, this introduces measurement error into aggregate group-level estimates when trying to create subsyndromes. We propose a multilevel analysis to provide a more valid and reliable estimation by separating out variance due to within-person daily fluctuations. Using a multilevel exploratory factor analysis with intensive longitudinal data, we identified distinct and meaningful groups of BPSD. The four factors at the between-person level represented subsyndromes that are based on how BPSD co-occurred among persons with Alzheimer's disease (AD). These subsyndromes are clinically relevant because they share features of established clinical phenomena and may have similar neurobiological etiologies. We also found three within-person factors representing distinct symptom clusters. They are based on how BPSD clustered together on a given day for an individual with AD and related dementias. These clusters may have shared environmental triggers.

Symptom clusters and predominant symptoms in lymphoma survivorship: a cross-sectional study using trend analysis.

PURPOSE: This study explored symptom clusters (SCs) and predominant symptoms in lymphoma survivorships at least 1 month after treatment. METHODS: A cross-sectional trend study design was adopted. Inclusion criteria were participants who were over the age of 20, diagnosed with lymphoma, and 1 month after treatment concluded. The symptoms were assessed by the Functional Assessment of Cancer Therapy Scale-Lymphoma Subscale. Data were analyzed using descriptive statistics, latent profile analysis (LPA), and comparisons of means and frequencies of each symptom in each SC. RESULTS: A total of 234 lymphoma survivors completed this study. Three SCs were identified at < 2 and > 5 years and two SCs at 2-5 years. Worrying about getting new symptoms and infections emerged as predominant symptoms across all SCs over time. This study provides insights into the symptom experiences of survivors of lymphoma and highlights the significant role of worry-related symptoms in their survivorship. CONCLUSION: Through the use of LPA and a trend study design, we identified distinct SCs in lymphoma survivors, providing valuable insights into their longitudinal symptom experiences. The findings emphasize the complexity of symptomatology in lymphoma survivorship and underscore the importance of employing advanced statistical methods to explore and understand these clusters comprehensively, informing targeted interventions and improved care strategies.

Symptom clusters among breast cancer patients in relation to chemotherapy cycles: a longitudinal study.

PURPOSE: The aim of this study was to identify symptom clusters in breast cancer patients undergoing adjuvant chemotherapy. METHODS: A prospective longitudinal study was conducted. And a sample of 620 breast cancer patients receiving adjuvant chemotherapy was recruited using convenience sampling from May 20, 2020, to March 31, 2021. Data were collected eight times: the first chemotherapy cycle (T1) to the eighth cycle of chemotherapy (T8). Exploratory factor analysis was used to explore the composition of symptom clusters. RESULTS: Symptoms with an incidence of less than 20% were deleted and the remaining symptoms were included in the factor analysis. Three common factors were extracted in T1, including gastrointestinal symptom cluster, emotional and psychological symptom cluster, and menopausal symptom cluster. Five common factors were extracted from T2 to T7, including gastrointestinal symptom cluster, emotional and psychological symptom cluster, neurological symptom cluster, menopausal symptom cluster, and self-image disorder symptom cluster. Four common factors were extracted at T8, including gastrointestinal symptom cluster, emotional and psychological symptom cluster, neurological symptom cluster, and menopausal symptom cluster. CONCLUSION: Breast cancer patients undergoing adjuvant chemotherapy experience multiple symptoms and different symptom clusters in different chemotherapy cycles. It is a benefit for health care providers to better understand and care for breast cancer patients. It will also help such women to manage concurrent symptoms ahead to promote their quality of life.

Associations of the gut microbiome with psychoneurological symptom cluster in women with gynecologic cancers: a longitudinal study.

PURPOSE: The present study aimed to evaluate the associations between the gut microbiome and psychoneurological symptoms (PNS) cluster in women with gynecologic cancers over time. METHODS: In this secondary data analysis, 19 women with cervical and endometrial cancers treated with radiotherapy were followed at pre-treatment, 6-8 weeks, and 6 months post-treatment. To measure symptoms, Functional Assessment of Cancer Therapy-General (FACT-G) and Patient Health Questionnaire-9 (PHQ-9) were used. An average Z score of at least three out of five symptoms was computed as the PNS cluster total score. Rectal swabs were also collected at the same time points and sequenced using 16S rRNA V4 regions. The Kruskal-Wallis and permutational multivariable analysis of variance tests were used to compare α- and ß-diversity between patients with high and low PNS cluster. The linear discriminant analysis effect size (LEfSe) tested taxa differences between study groups. Also, the linear mixed-effect model was used to evaluate the association of the gut microbiome and the PNS cluster over cancer treatment. RESULTS: The patients' mean age was 58 years, 47% Black, 52% single/divorced, and 66% had college or above education. Among the participants, 63% had endometrial cancer with stage I disease. There was a different taxonomy profile between patients with high and low PNS. Patients with high PNS had a lower α-diversity than those with low PNS (Shannon, p = 0.03, evenness, p = 0.03). The mixed effects model results showed that low α-diversity and abundance of Fusicatenibacter and Ruminococcus were associated with high PNS cluster over cancer treatment. CONCLUSION: The association between the gut microbiome and PNS cluster suggest that the gut microbiota plays a role in developing the PNS cluster. Future larger studies are required to shed light on the gut microbiota role in symptom development in gynecologic cancer patients.

Identification of distinct symptom profiles in patients with gynecologic cancers using a pre-specified symptom cluster.

PURPOSE: Pain, fatigue, sleep disturbance, and depression are four of the most common symptoms in patients with gynecologic cancer. The purposes were to identify subgroups of patients with distinct co-occurring pain, fatigue, sleep disturbance, and depression profiles (i.e., pre-specified symptom cluster) in a sample of patients with gynecologic cancer receiving chemotherapy and assess for differences in demographic and clinical characteristics, as well as the severity of other common symptoms and QOL outcomes among these subgroups. METHODS: Patients completed symptom questionnaires prior to their second or third cycle of chemotherapy. Latent profile analysis was used to identify subgroups of patients using the pre-specified symptom cluster. Parametric and nonparametric tests were used to evaluate for differences between the subgroups. RESULTS: In the sample of 233 patients, two distinct latent classes were identified (i.e., low (64.8%) and high (35.2%)) indicating lower and higher levels of symptom burden. Patients in high class were younger, had child care responsibilities, were unemployed, and had a lower annual income. In addition, these women had a higher body mass index, a higher comorbidity burden, and a lower functional status. Patients in the high class reported higher levels of anxiety, as well as lower levels of energy and cognitive function and poorer quality of life scores. CONCLUSIONS: This study identified a number of modifiable and non-modifiable risk factors associated with membership in the high class. Clinicians can use this information to refer patients to dieticians and physical therapists for tailored interventions.

The connections of physical and psychosocial symptoms among patients with terminal illnesses: A network analysis.

BACKGROUND: Patients with terminal illnesses have different symptoms. The goal of palliative care is to alleviate the suffering induced by these symptoms. Available research on symptoms has focused on their prevalence or identification of clusters. Little is known about the central symptoms contributing to the maintenance of the whole system of symptoms or the mechanism of influence between symptoms, particularly between physical and psychosocial symptoms. AIM: The study used network analysis to explore symptom clusters among patients with terminal illnesses and identify the central symptoms, the bridge symptoms, and pathways between physical and psychosocial symptoms. DESIGN AND SETTING/PARTICIPANTS: This is a retrospective cohort study using baseline symptom assessment of 677 adults with terminal illnesses receiving care from the Integrated Community End-of-Life Care Support Teams. RESULTS: Three symptom clusters were identified: physical, psychological, and practical clusters. "Weakness or lack of energy" was identified as the crucial symptom affecting the changes of other symptoms, followed by depression and anxiety. Three connections between the psychological and physical symptoms were identified: anxiety-pain, depression-constipation, and perceived family anxiety-poor appetite pathways. Pathways of practical concern-peace and practical concern-depression were indicated between practical and psychological symptoms. CONCLUSIONS: This study is the first of its kind to investigate the connections and mechanism of influence between symptoms among patients with terminal illnesses. It offers clear pathways for intervention with the most influential symptoms of weakness, anxiety, and depression.

Exploration of symptom clusters during hemodialysis and symptom network analysis of older maintenance hemodialysis patients: a cross-sectional study.

BACKGROUND: Symptom networks can provide empirical evidence for the development of personalized and precise symptom management strategies. However, few studies have established networks of symptoms experienced by older patients on maintenance hemodialysis. Our goal was to examine the type of symptom clusters of older maintenance hemodialysis patients during dialysis and construct a symptom network to understand the symptom characteristics of this population. METHODS: The modified Dialysis Symptom Index was used for a cross-sectional survey. Network analysis was used to analyze the symptom network and node characteristics, and factor analysis was used to examine symptom clusters. RESULTS: A total of 167 participants were included in this study. The participants included 111 men and 56 women with a mean age of 70.05 ± 7.40. The symptom burdens with the highest scores were dry skin, dry mouth, itching, and trouble staying asleep. Five symptom clusters were obtained from exploratory factor analysis, of which the clusters with the most severe symptom burdens were the gastrointestinal discomfort symptom cluster, sleep disorder symptom cluster, skin discomfort symptom cluster, and mood symptom cluster. Based on centrality markers, it could be seen that feeling nervous and trouble staying asleep had the highest strength, and feeling nervous and feeling irritable had the highest closeness and betweenness. CONCLUSIONS: Hemodialysis patients have a severe symptom burden and multiple symptom clusters. Dry skin, itching, and dry mouth are sentinel symptoms in the network model; feeling nervous and trouble staying asleep are core symptoms of patients; feeling nervous and feeling irritable are bridge symptoms in this symptom network model. Clinical staff can formulate precise and efficient symptom management protocols for patients by using the synergistic effects of symptoms in the symptom clusters based on sentinel symptoms, core symptoms, and bridge symptoms.

Symptom and problem clusters in German specialist palliative home care - a factor analysis of non-oncological and oncological patients' symptom burden.

BACKGROUND: Specialist palliative home care (SPHC) aims to maintain and improve patients' quality of life in the community setting. Symptom burden may differ between oncological and non-oncological patients. However, little is known about diagnosis-related differences of SPHC patients. This study aims to describe the prevalence of physical symptom burden and psychosocial problems of adult patients in SPHC, and to evaluate diagnosis-related symptom clusters. METHODS: Secondary analysis of data from a prospective, cross-sectional, multi-centre study on complexity of patients, registered at the German Register for Clinical Studies (DRKS trial registration number: DRKS00020517, 12/10/2020). Descriptive statistics on physical symptom burden and psychosocial problems at the beginning of care episodes. Exploratory and confirmatory factor analyses to identify symptom and problem clusters. RESULTS: Seven hundred seventy-eight episodes from nine SPHC teams were included, average age was 75 years, mean duration of episode 18.6 days (SD 19.4). 212/778 (27.2%) had a non-oncological diagnosis. Main burden in non-oncological episodes was due to poor mobility (194/211; 91.9%) with significant diagnosis-related differences (χ² = 8.145, df = 1, p = .004; oncological: 472/562; 84.0%), and due to weakness (522/565; 92.4%) in oncological episodes. Two symptom clusters (psychosocial and physical) for non-oncological and three clusters (psychosocial, physical and communicational/practical) for oncological groups were identified. More patients in the non-oncological group compared to the oncological group showed at least one symptom cluster (83/212; 39.2% vs. 172/566; 30.4%). CONCLUSION: Patients with non-oncological diseases had shorter episode durations and were more affected by symptom clusters, whereas patients with oncological diseases showed an additional communicational/practical cluster. Our findings indicate the high relevance of care planning as an important part of SPHC to facilitate anticipatory symptom control in both groups.

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.

Multiple myeloma patients undergoing chemotherapy: Which symptom clusters impact quality of life?

AIMS AND OBJECTIVES: To identify symptom clusters and examine their association with health-related quality of life. BACKGROUND: Multiple myeloma patients undergoing chemotherapy suffer from disease symptoms and adverse effects during the course of the disease. However, single symptom management has little effect, and symptom management for these patients remains challenging. Symptom clusters open a new perspective and provide important clues for symptom management. DESIGN: A cross-sectional study. METHOD: Participants were invited to complete the Chinese version of the Memorial Symptom Assessment Scale and Quality of Life Questionnaire-core 30. Appropriate indicators were used for descriptive statistics. Principal component analysis was used to identify symptom clusters. Associations between symptom clusters and quality of life were examined with Pearson correlation coefficients, Pearson correlation matrix and multiple linear regression. This study was reported following the STROBE checklist. RESULTS: A total of 177 participants were recruited from seven hospitals in this study. We identified self-image disorder, psychological, gastrointestinal, neurological, somatic and pain symptom clusters in multiple myeloma patients with chemotherapy. Approximately 97.65% of patients suffer from multiple symptom clusters. The pain, psychological and gastrointestinal symptom clusters have negatively influence on health-related quality of life. The strongest association was found with the pain symptom cluster. CONCLUSION: Most of multiple myeloma patients suffer from multiple symptom clusters. When improving the multiple myeloma patients' health-related quality of life, the clinical staff should prioritise relieving the pain symptom cluster. RELEVANCE TO CLINICAL PRACTICE: When multiple myeloma patients undergoing chemotherapy suffer from multiple symptom clusters, nurses should prioritise relieving the pain symptom cluster to improve their health-related quality of life. When drawing up and providing interventions, nurses should focus on the correlation among symptoms rather than single symptom. By relieving one symptom in a given cluster, other symptoms within the same symptom cluster may also be relieved.