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.

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.

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.

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.

Nonpharmacological Interventions for the Fatigue-Pain-Sleep Disturbance Symptom Cluster in Lung Cancer Patients: Best Evidence Summary.

OBJECTIVES: This study aimed to summarize the most effective evidence on nonpharmacological interventions for the fatigue-pain-sleep disturbance symptom cluster in lung cancer patients and to provide evidence-based management methods for clinical team and lung cancer patients. METHODS: Guided by the "6S" pyramid model, we retrieved evidence on fatigue, pain, and sleep disturbance management from relevant websites and databases, and unpublished gray literature was also searched. The time frame of the search ranged from database establishment to September 30, 2023. Two researchers independently evaluated the literature quality using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) for guidelines, and the Assessment of Multiple Systematic Reviews II (AMSTAR II) for systematic reviews. Two people independently extracted and summarized the evidence according to the first principle of high-quality evidence and newly published evidence. The included evidence was graded by the JBI Evidence Pre-Grading System. RESULTS: A total of 52,238 articles were retrieved, of which 60 articles, including 18 guidelines, 18 JBI best practice recommendations, one Up To Date clinical practice, and 23 systematic reviews, were included. Overall, 49 pieces of evidence from six dimensions-screening, assessment, management, education, referral, and follow-up-were summarized. Forty-three pieces of evidence were level 1, three pieces of evidence were level 4, and three pieces of evidence were level 5. CONCLUSIONS: The best 49 pieces of evidence on nonpharmacological interventions for the fatigue-pain-sleep disturbance symptom cluster in lung cancer patients were summarized in this study, and these nonpharmacological interventions are scientific and comprehensive. IMPLICATIONS FOR NURSING PRACTICE: This study can provide guidance for clinical team to improve the fatigue-pain-sleep disturbance symptom cluster management. These evidence items can be implemented by clinical team to reduce the symptom burden and improve the self-management ability of symptoms in lung cancer patients.

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.

Symptom network and quality of life of breast cancer patients receiving multimodal cancer treatment: Cross-sectional study.

PURPOSE: Breast cancer patients experience symptoms and side effects from multimodal treatments, which often include menopausal symptoms resulting from cytotoxic chemotherapy or estrogen suppression therapy. This study aimed to explore the symptom network and clusters and its relationship to quality of life (QoL) in breast cancer patients who receive multimodal cancer treatment and experience treatment-related menopausal symptoms. METHODS: A correlational study was conducted. Breast cancer patients receiving multimodal cancer treatment and experiencing treatment-related menopausal symptoms were included while they were receiving radiation therapy (N = 250). Symptoms, functions and QoL were assessed using the EORTC QLQ-C30 and BR45. Network analysis, principal component analysis, exploratory factor analysis, and multiple linear regression analysis were conducted. RESULTS: Fatigue was the most central symptom in the symptom-only network as well as in the network consisting of symptoms and QoL. Fatigue, systemic therapy side effects, appetite loss, and cognitive symptoms demonstrated significant associations with QoL. The cancer and treatment related symptom cluster consisted of fatigue, cognitive symptoms, emotional symptoms and systemic therapy side effects. Breast cancer therapy-specific symptoms, such as arm symptoms, skin mucosis symptoms, and breast symptoms, formed a cluster with pain. CONCLUSION: Fatigue was the most central symptom in breast cancer patients receiving multimodal cancer treatment and experiencing menopausal symptoms. Evaluation of fatigue and providing interventions to manage fatigue would contribute to improvement of QoL of breast cancer patients receiving multimodal cancer treatments. Future network analysis and symptom cluster studies should specify the population of interest and the treatment phase using comprehensive symptom evaluation tools.

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.

Risk factors for self-reported high symptom cluster burdens in patients with breast cancer undergoing chemotherapy in China: A cross-sectional study.

Background and Aims: Further exploration is needed to recognize symptom clusters and categorize subgroups with distinct cluster patterns and associated risks, focusing on symptoms that are highly self-reported by patients with breast cancer undergoing chemotherapy. This study aimed to identify subgroups and risk factors for self-reported high symptom cluster burden among patients with breast cancer undergoing chemotherapy. Methods: A total of 647 participants who met the inclusion criteria were included in the study, with data collected on demographics, disease information, self-reported symptoms, and psychosocial factors. Latent class analysis was utilized to identify the subgroup, while logistic regression was used to pinpoint predictive risk factors. Results: Latent class analysis revealed three subgroups: the "high burden of all symptoms group" (n = 107, 16.54%), the "high burden of psychological symptoms group" (n = 103, 15.92%), and the "low burden of all symptoms group" (n = 437, 67.54%). Patients in the high burden of all symptom group and high burden of psychological symptom group exhibited significantly worse function outcomes (p < 0.001). Predictive risk factors for the "high burden of all symptom group" included older age, lower self-efficacy, worse body image, and a higher financial burden. Similarly, patients with high burden of psychological symptom were more likely to have low self-efficacy, poor body image, and a high financial burden. Conclusion: The study demonstrated the importance of giving more attention to patients with breast cancer who are at risk of developing into membership of high symptom cluster burden group.

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.

Symptom clusters and unplanned hospital readmission in Chinese patients with acute myocardial infarction on admission.

Backgroud: Acute myocardial infarction (AMI) has a high morbidity rate, high mortality rate, high readmission rate, high health care costs, and a high symptomatic, psychological, and economic burden on patients. Patients with AMI usually present with multiple symptoms simultaneously, which are manifested as symptom clusters. Symptom clusters have a profound impact on the quality of survival and clinical outcomes of AMI patients. Objective: The purpose of this study was to analyze unplanned hospital readmissions among cluster groups within a 1-year follow-up period, as well as to identify clusters of acute symptoms and the characteristics associated with them that appeared in patients with AMI. Methods: Between October 2021 and October 2022, 261 AMI patients in China were individually questioned for symptoms using a structured questionnaire. Mplus 8.3 software was used to conduct latent class analysis in order to find symptom clusters. Univariate analysis is used to examine characteristics associated with each cluster, and multinomial logistic regression is used to analyze a cluster membership as an independent predictor of hospital readmission after 1-year. Results: Three unique clusters were found among the 11 acute symptoms: the typical chest symptom cluster (64.4%), the multiple symptom cluster (29.5%), and the atypical symptom cluster (6.1%). The cluster of atypical symptoms was more likely to have anemia and the worse values of Killip class compared with other clusters. The results of multiple logistic regression indicated that, in comparison to the typical chest cluster, the atypical symptom cluster substantially predicted a greater probability of 1-year hospital readmission (odd ratio 8.303, 95% confidence interval 2.550-27.031, P < 0.001). Conclusion: Out of the 11 acute symptoms, we have found three clusters: the typical chest symptom, multiple symptom, and atypical symptom clusters. Compared to patients in the other two clusters, those in the atypical symptom cluster-which included anemia and a large percentage of Killip class patients-had worse clinical indicators at hospital readmission during the duration of the 1-year follow-up. Both anemia and high Killip classification suggest that the patient's clinical presentation is poor and therefore the prognosis is worse. Intensive treatment should be considered for anemia and high level of Killip class patients with atypical presentation. Clinicians should focus on patients with atypical symptom clusters, enhance early recognition of symptoms, and develop targeted symptom management strategies to alleviate their discomfort in order to improve symptomatic outcomes.

Identification of distinct symptom profiles in prostate cancer patients with cancer-related cognitive impairment undergoing androgen deprivation therapy: A latent class analysis.

Objective: To identify latent classes of cognitive impairment and co-occurring symptoms (fatigue, pain, sleep disturbance, depression) as clusters in patients with prostate cancer undergoing androgen deprivation therapy and to explore the predictors among distinct latent classes. Methods: A total of 228 patients with prostate cancer were recruited in this cross-sectional study. The assessment instrument included the Perceived Cognitive Impairment Scale, the Fatigue Severity Scale, the Athens Insomnia Scale, the Brief Pain Inventory, the Patient Health Questionnaire-9, the UCLA Loneliness Scale, the International Physical Activity Questionnaire - Short Form, the Charlson comorbidity index, and General Information questionnaire. The identification of different patient subgroups was done by the latent class analysis. Results: The study identified three distinct latent classes: all low symptoms (class 1, 32%), high depression symptoms (class 2, 37.7%), and high physical symptoms (fatigue, sleep disturbance, and pain) with high cognitive impairment (class 3, 30.3%). Patients who had higher Charlson comorbidity index (P = 0.003) scores were more likely to be classified in class 3. Patients with higher loneliness scores (P < 0.001; P < 0.001) were significantly more likely to fall into class two or three than in class 1. However, having a higher level of physical activity (P = 0.014; P < 0.001) increased the likelihood of being in class 1. Conclusions: This study exhibited the inter-individual variability of symptom experience in prostate cancer patients with cognitive impairment undergoing androgen deprivation therapy. The result suggests that more emphasis should be placed on screening for fatigue, sleep disturbance, and pain, and future interventions should focus on loneliness and physical activity.

Nonpharmacological Interventions for Managing Symptom Clusters in Adults: A Systematic Review.

Objectives: The complex effects of multiple co-occurring symptoms are a major cause of reduced quality of life; thus, it is necessary to identify symptom clusters experienced by patients and explore interventions. This study aimed to provide an overview of non-pharmacological interventions based on symptom clusters in adults to identify effective intervention strategies and methods. Methods. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. For the search databases, PubMed, Embase, Cochrane Library, CINAHL, RISS, KISS, and KISTI were used. It includes English and Korean experimental studies published up to May 2023. The literature quality was evaluated using the Joanna Briggs Institute Quality Assessment Tool. Results. Of the 18 studies selected, 15 were randomized controlled trials and three were quasi-experimental studies, all of which were conducted on patients with cancer. The symptom clusters-based interventions in the literature are classified as movement-based, relaxation-based, integrated, and miscellaneous interventions. Integrated interventions, which were effective in all studies, might prove to be very effective for managing symptom clusters. Movement-based intervention studies, which include dance, Qigong, and Tai Chi, might be very effective in improving health-related quality of life (HRQoL). Conclusions. This review demonstrates that non-pharmacological interventions reduce the occurrence and severity of symptom clusters, thereby improving HRQoL. Further studies are required to evaluate the effects of these interventions in patients with various chronic conditions other than cancer.

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.

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.

Effects of yoga interventions on the fatigue-pain-sleep disturbance symptom cluster in breast cancer patients: A systematic review.

OBJECTIVE: This systematic review aimed to evaluate the effectiveness of yoga intervention on the fatigue-pain-sleep disturbance symptom cluster in breast cancer patients. METHODS: Ten electronic databases (Medline, Embase, PubMed, Cochrane Central Register of Controlled Trials, CINAHL, Web of Science, Scopus, British Nursing Index, China National Knowledge Infrastructure, and Wan Fang database) were searched to identify randomized controlled trials from inception to October 2023. Two independent reviewers evaluated study eligibility, extracted data, and assessed the risk of bias using the Cochrane Risk of Bias tool. The findings were synthesized narratively. This systematic review has been registered (PROSPERO ID: CRD42023391269). RESULTS: A total of 1389 studies were identified, and 18 studies were included in this systematic review. Two studies reported significant alleviation of fatigue-pain-sleep disturbance symptoms, and two studies indicated a significant reduction in fatigue-sleep disturbance symptoms compared to the control group. Commonly employed yoga contents included breathing exercise and posture practice. The effective intervention components encompassed the combination of in-person sessions and home-based sessions delivery mode, with intervention sessions lasting 50-120 min each and dosages ranging from once per week to twice daily, spanning 6-16 weeks. CONCLUSIONS: Yoga intervention can be beneficial in alleviating the fatigue-pain-sleep disturbance symptom cluster in breast cancer patients. Future research should be tailored to design yoga interventions addressing different treatment stages and preferences of breast cancer patients.

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.

Effects of nonpharmacological interventions on symptom clusters in breast cancer survivors: A systematic review of randomized controlled trials.

Objective: To summarize nonpharmacological interventions and assess their effects on symptom clusters and quality of life (QoL) in breast cancer (BC) survivors. Methods: Seven English and three Chinese electronic databases and three clinical trial registries were searched from January 2001 to August 2023. A narrative approach was applied to summarize the data. The primary outcome was symptom clusters measured by any patient-reported questionnaires, and the secondary outcomes were QoL and intervention-related adverse events. Results: Six published articles, one thesis, and one ongoing trial involving 625 BC survivors were included. The fatigue-sleep disturbance-depression symptom cluster was the most frequently reported symptom cluster among BC survivors. The nonpharmacological interventions were potentially positive on symptom clusters and QoL among the BC survivors. However, some of the included studies exhibited methodological concerns (e.g., inadequate blinding and allocation concealment). The intervention protocols in only two studies were developed following a solid evidence-based approach. Adverse events related to the targeted interventions were reported in six included studies, with none performing a causality analysis. Conclusions: The nonpharmacological interventions could be promising strategies for alleviating symptom clusters in BC survivors. Future studies should adopt rigorously designed, randomized controlled trials to generate robust evidence. Systematic review registration: INPLASY202380028.

Identifying central symptom clusters and correlates in patients with lung cancer post-chemotherapy: A network analysis.

Objective: This study aims to investigate the network structures of symptoms and symptom clusters in patients with lung cancer post-chemotherapy, with a focus on identifying the central symptom cluster. Understanding the central cluster is crucial for targeted and effective symptom management. Methods: Symptom occurrence and severity were assessed using the Memorial Symptom Assessment Scale (MSAS). Principal component analysis (PCA) was employed to explore symptom clusters, while network analysis unveiled the network structure and pinpointed the central symptom cluster. Results: The study included 512 patients with lung cancer. Four distinct symptom clusters emerged: sickness behavior, psychological, lung cancer-specific, and epithelial. The sickness behavior symptom cluster was identified as the central symptom cluster. Conclusions: This research designates the sickness behavior symptom cluster as central in post-chemotherapy patients with lung cancer, offering valuable insights for clinical nurses in devising more effective symptom management strategies. Trial registration: ChiCTR2300070944 (Chinese Clinical Trial Register).

A longitudinal study of symptom cluster latent profiles in ovarian cancer patients undergoing chemotherapy.

BACKGROUND: This study aimed to identify distinct patterns within the symptom cluster of fatigue, pain, and sleep disturbance among ovarian cancer patients receiving chemotherapy, to determine the factors predicting these patterns and their impact on quality of life. METHODS: The longitudinal study collected data from 151 ovarian cancer patients at three time points: before chemotherapy (T0), after the first chemotherapy cycle (T1), and following the completion of four cycles of chemotherapy (T2). Latent profile analysis and latent transition analysis were used to identify symptom patterns and evaluate changes in symptom patterns. A bias-adjusted three-step approach was utilized to examine predictor variables and distal outcomes associated with latent class membership. RESULTS: Three symptom patterns emerged: "All Low," "Moderate" (T0)/"Low pain and high sleep disturbance" (T1 and T2), and "All High." Patients with lower educational attainment and higher levels of anxiety and depression were found to be at an elevated risk of belonging to the "All High" class. All quality-of-life domains showed significant differences among the three subgroups, following an "All Low" > "All High" pattern (p < 0.05). Membership in three classes remained relatively stable over time, with probabilities of 0.749 staying within their groups from T0 to T2. CONCLUSIONS: This study underscores the existence of a diverse and heterogeneous experience within the symptom cluster of fatigue, pain, and sleep disturbance among ovarian cancer patients. Importantly, these patterns were stable throughout chemotherapy. Recognizing and understanding these patterns can inform the development of targeted interventions to alleviate the burden of symptom clusters in this population.