Symptom Clusters In Patients Research Articles

Symptom Network and Clusters of the Multidimensional Symptom Experience in Patients With Atrial Fibrillation

Background The symptom network can provide a visual insight into the symptom mechanisms. However, few study authors have explored the multidimensional symptom network of patients with atrial fibrillation (AF). Objectives We aimed to identify the core symptom and symptom clusters of patients with AF by generating a symptom network. Furthermore, we wanted to identify multiple characteristics related to symptom clusters. Methods This is a cross-sectional study. A total of 384 patients with AF at Tianjin Medical University General Hospital were enrolled. The University of Toronto Atrial Fibrillation Severity Scale was used to assess AF symptoms. Network analysis was used to explore the core symptom and symptom cluster. Results Shortness of breath at rest (r s = 1.189, r c = 0.024), exercise intolerance (r s = 1.116), shortness of breath during physical activity (r s = 1.055, r c = 0.022), and fatigue at rest (r c = 0.020) have the top centrality for strength and closeness. The top 3 symptoms of bridge strength were shortness of breath at rest (r s = 0.264), dizziness (r s = 0.208), and palpitations (r s = 0.207). Atrial fibrillation symptoms could be clustered into the breathless cluster and the cardiac cluster. We have identified multiple factors such as mental health status, left ventricular ejection fraction, heart failure, sex, B-type natriuretic peptide, and chronic obstructive pulmonary disease as significant contributors within the breathless cluster, whereas sex, mental health status, and history of radiofrequency ablation were strongly associated with the cardiac cluster, holding promise in elucidating the underlying mechanisms of these symptoms. Conclusion Special attention should be given to shortness of breath at rest as its core and bridging role in patients' symptoms. Furthermore, both the breathless and cardiac clusters are common among patients. Network analysis reveals direct connections between symptoms, symptom clusters, and their influencing factors, providing a foundation for clinicians to effectively manage patients' symptoms.

Symptom clusters and network analysis in patients with gynecologic cancer undergoing chemotherapy: A cross-sectional study.

ObjectiveThis study aimed to explore the complex relationships among symptoms and symptom clusters in patients with gynecologic cancer receiving chemotherapy using symptom network analysis, and to identify core symptoms and core symptom clusters. MethodsA cross-sectional study was conducted at the Affiliated Hospital of Jiangnan University from December 2023 to June 2024, including 221 patients with gynecologic tumors. Participants completed demographic and clinical information questionnaires and the Chinese version of the MD Anderson Symptom Inventory (MDASI-C). Univariate analysis and multiple linear regression were used to screen covariates, exploratory factor analysis to determine symptom clusters, and network analysis to identify core symptoms and core symptom clusters. ResultsA total of 221 patients were included, with an average age of 58.73 years (SD = 11.50). Fatigue (n = 197, 89.1%) and lack of appetite (n = 192, 86.9%) were the most common symptoms, while fatigue (mean = 4.17, SD = 2.07) and distress (mean = 3.43, SD = 2.20) were the most severe symptoms. Several distinct symptom clusters were identified: sickness behavior, gastrointestinal, psychological, and side-effect clusters. In the constructed network, fatigue emerged as the most central symptom (rs = 1.28), while the sickness behavior cluster was identified as the most central symptom cluster (rs = 1.11). ConclusionsPatients with gynecologic cancer undergoing chemotherapy commonly experience a range of symptoms. Our findings suggest that targeted interventions focusing on the sickness behavior symptom cluster may help reduce the overall symptom burden and assist caregivers in developing more effective symptom management strategies.

Feasibility of a nurse-initiated brief cognitive behavioral strategy intervention program for symptom clusters experienced by patients with advanced non-small cell lung cancer

BackgroundA nurse-initiated brief cognitive behavioral Strategy (CBS) intervention program has shown alleviation effects of single symptoms. However, the feasibility of the brief CBS for symptoms included in the Pain and Fatigue symptom clusters in patients with advanced nonsmall cell lung cancer (NSCLC) has not been evaluated. ObjectiveTo evaluate the feasibility of application of the nurse-initiated brief CBS intervention program focusing on pain and fatigue symptoms among the Pain and Fatigue/anorexia symptom clusters experienced by patients with advanced NSCLC. MethodsIn this one-group pretest-posttest design, participants were 15 outpatients with NSCLC undergoing medical treatment (UMIN 000026996). After expressing consent to the study participation, the participants completed a baseline questionnaire and were given a booklet explaining brief cognitive behavioral therapies (relaxation, problem-solving strategies for symptom relief), exercise therapy, and tools. We provided follow-up calls five times and evaluated the retention and changes in symptom severities till the 10th week after the intervention. ResultsOf 15 participants, 10 (66.7%) completed the program. For pain relief strategies, 87% chose deep breathing for relaxation, and 80% fatigue relief with exercises. The median symptom severities (at the baseline and Wk10) showed downward tendencies: pain (2.00, 1.00), sadness (1.00, 0.00), and anxiety (1.00, 0.50). Implications for practiceWe need a randomized controlled trial to further test the effectiveness of the intervention in alleviating symptom and improving QOL of this population. ConclusionsThe nurse-initiated brief CBS intervention program is clinically practical in this population. Nurses may provide useful support for patient symptom management by brief CBS.

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

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. 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. 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." 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.

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

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. This was a longitudinal study. 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. 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. 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. 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.

Abstract PO1-11-06: Evaluating Symptom Clusters in Patients with Breast Cancer Experiencing Aromatase Inhibitor-Associated Musculoskeletal Symptoms

Abstract Background: Although treatment with an aromatase inhibitor (AI) for 5-10 years decreases 10-year breast cancer mortality by about 40%, up to 25% of patients will stop treatment early because of treatment-related, intolerable joint and muscular pain and stiffness, called aromatase inhibitor-associated musculoskeletal symptoms (AIMSS). We previously identified that nociplastic pain, or chronic pain in the absence of tissue damage or inflammation, is associated with increased likelihood of developing AIMSS. Other studies have found that symptom clusters, such as the SPPADE symptoms (sleep disturbance, pain, physical function impairment, anxiety, depression, and low energy/fatigue) are prevalent and co-occur in patients with cancer. Here we examine the prevalence of SPPADE symptoms for patients experiencing AIMSS and willing to enroll on a clinical trial examining use of cannabidiol (CBD) to treat their symptoms. Methods: Patients with stage 0-3 hormone receptor-positive breast cancer experiencing AIMSS (defined as worst joint pain ≥4/10 during prior 7 days that developed or worsened since starting AI therapy) were eligible for enrollment in this single arm, single center phase 2 open label clinical trial (NCT04754399). Enrolled patients completed validated questionnaires at baseline and then received CBD (Epidiolex) for 15 weeks. Patient-reported outcomes (PRO) data was collected serially, including the following questionnaires which addressed SPPADE symptoms: Brief Pain Inventory (BPI) to assess pain, PROMIS Profile 29+2 v2.1 to assess multiple symptoms, and Fibromyalgia Survey (FMS) to assess nociplastic pain. Results: 39 patients enrolled on this clinical trial. The median age at enrollment was 57 (range 37-59) and 21% of patients were over age 70. The majority of patients were white (92%) and average BMI was 31 (SD 6.6). Anastrozole was the most used aromatase inhibitor (74%), followed by exemestane (18%), and letrozole (8%). 5 patients (13%) required concomitant GnRHa therapy. Baseline PRO data was obtained from 37 patients. BPI average pain score over the week prior to enrollment was 5.1 (SD 1.5) and worst pain score was 7.2 (SD 1.3). Pain interference reported on the BPI was 4.1 (SD 2.1). Compared to the general population, enrolled patients reported better physical function (T-score 60.2, SE 3.7), less depression (T-score 45.5, SE 4.7) and fatigue (T-score 46.7, SE 5.1), and similar levels of anxiety (T-score 51, SE 7.1) and sleep disturbance (T-score 49.5, SE 5.9) on the PROMIS Profile. On the FMS, 62% of patients had evidence of nociplastic pain, with average score 13.3 (SD 5.7). The median number of sites of pain in the body reported by patients was 8 (range 1-16). Conclusions: While patients enrolling on an AIMSS clinical trial reported a high degree of daily pain that regularly interferes with their activities, for most patients these symptoms did not appear to have a negative impact on mood, affect, or other symptoms that typically cluster with pain. Though it is difficult to extrapolate results from a small population, the unexpected absence of co-occurring symptoms in this population raises additional questions about the interplay of AIMSS and other symptoms commonly reported in interventional AIMSS studies. Follow-up PRO data will be obtained in this clinical trial, allowing us to examine the impact of CBD use on pain, pain interference, and other patient-reported symptoms, as well as to explore which patients are more likely to obtain benefit from CBD treatment. Funding support provided by Conquer Cancer, the ASCO Foundation and the Rising Tide Foundation for Clinical Cancer Research. Citation Format: Fleege Nicole, N. Lynn Henry. Evaluating Symptom Clusters in Patients with Breast Cancer Experiencing Aromatase Inhibitor-Associated Musculoskeletal Symptoms [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-11-06.

Efficacy of acupuncture for a cough-related symptom cluster in patients with lung cancer: A randomized controlled trial

PurposeThis study was designed to evaluate the effect of acupuncture on cough, expectoration, and shortness of breath in lung cancer patients. MethodsBetween December 2021 and June 2022, a total of 130 lung cancer patients were recruited, and they were split into control and intervention groups at random. Routine nursing was provided to the control group, whereas routine nursing with acupuncture using LU7 (Lie Que), LU9 (Tai Yuan), BL13 (Fei Shu), and BL20 (Pi Shu) was administered to the intervention group for 7 days. The severity of cough, expectoration, and shortness of breath was assessed 1 day before and after the interventions using the lung cancer-specific module of the MDASI. A two-way ANOVA was performed for group comparisons. ResultsCompared with the control group, the symptoms of cough in the intervention group were significantly improved (F = 5.095, MD = −0.32, 95% CI, −0.59 to 0.04, P = 0.025), while expectoration (F = 0.626, MD = −0.11, 95% CI, −0.38 to 0.16, P = 0.430) and shortness of breath (F = 0.165, MD = −0.05, 95% CI, −0.27 to 0.18, P = 0.685) had no significant change. Cough also identified an obvious interaction effect (P = 0.014), and the post-intervention simple main effect test demonstrated a tangible difference between the two groups (MD = −0.66, 95% CI, −0.99 to 0.33, P < 0.001) post-intervention. ConclusionsAcupuncture using LU7, LU9, BL13, and BL20 can relieve the cough of lung cancer patients, but not relieve expectoration and shortness of breath.

Illness Perceptions as a Predictor of Symptom Cluster Trajectories in Patients With Inflammatory Bowel Disease: A Latent Growth Mixture Model.

The aims of this study were to (a) identify the trajectory of symptom clusters in patients with inflammatory bowel disease up to 28 weeks after initiation of infliximab therapy and (b) examine the illness perceptions associated with symptom cluster trajectories. This was a prospective study where participants completed the symptom cluster scale at baseline, 14 weeks, and 28 weeks. A latent growth mixture modeling was used to identify trajectories of symptom clusters that were predicted, using baseline covariates (Brief Illness Perception Questionnaire). A total of 206 patients were included and identified as three latent classes: moderate symptom cluster-stable decline group (C1), high symptom cluster-rapid decline group (C2), and stable symptom cluster-stable trend group (C3). C1 was predicted by cognitive illness perceptions (odds ratio [95% confidence interval]: 1.134 [1.071, 1.200], p < .001). C2 was also predicted by cognitive and emotional illness perceptions (odds ratio [95% confidence interval]: 1.169 [1.095, 1.248], p < .001; odds ratio [95% confidence interval]: 1.174 [1.038, 1.328], p = .011). Patients with inflammatory bowel disease, initiating infliximab therapy, had different symptom cluster trajectories. Illness perceptions were associated with symptom cluster classes, which underline the complexity of symptoms. Paying attention to these factors and providing necessary knowledge and psychological supporting care after infliximab therapy would effectively improve patients' symptom burden.

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

ObjectiveThis 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. MethodsSymptom 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. ResultsThe 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. ConclusionsThis 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 registrationChiCTR2300070944 (Chinese Clinical Trial Register).

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

BackgroundA 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.MethodsOver 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.DiscussionThis 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 registrationClinicalTrials.gov (NCT05867966). Registered on the 27th of April 2023. url: https://classic.clinicaltrials.gov/ct2/show/NCT05867966.

Symptom clusters and characteristics of cervical cancer patients receiving concurrent chemoradiotherapy: A cross-sectional study

BackgroundCervical cancer patients have a high symptom burden during concurrent chemoradiotherapy (CCRT) and urgently need precise symptom management strategies. Nonetheless, the symptom profile and influencing factors are unclear. MethodsA total of 234 patients with cervical cancer who underwent CCRT in a tertiary care hospital clinical oncology center in Guangxi Zhuang Autonomous Region from March 2022 to March 2023 were included in the study. The general information questionnaire, M.D. Anderson symptom inventory, Fatigue Scale-14, Pittsburgh Sleep Quality Index, and grip strength test were used for the investigation. Symptom clusters were extracted by exploratory factor analysis, and latent profile analysis was performed using Mplus 8.0 software. Multinomial logistic regression was used to explore the factors influencing the potential categories of symptom clusters. ResultsExploratory factor analysis extracted four symptom clusters: a fatigue-related symptom cluster, a gastrointestinal-related symptom cluster, a mood-related symptom cluster, and a physical-related symptom cluster, of which the fatigue-related symptom cluster was more severe and was divided into three potential categories: low fatigue-good muscle fitness type (25.63%), general fatigue-moderate muscle fitness type (68.37%) and high fatigue-low muscle fitness type (6%). Multinomial logistic regression analysis showed that hemoglobin levels, tumor stage, absence of complications, and unemployment were factors influencing the fatigue-related symptom cluster in patients undergoing CCRT for cervical cancer. ConclusionsCervical cancer patients experience multiple symptom clusters during CCRT. Different characteristics appeared in different clusters. Among them, fatigue-related symptom clusters were more severe and heterogeneous. In clinical practice, we should pay attention to and use high symptom feature predictors, focusing on the core symptoms that play a dominant role, achieving early identification and management, and reducing patients' symptom burden.

Leveraging electronic patient-reported outcomes collected at six cancer centers to identify symptom clusters across the first four weeks of chemotherapy.

366 Background: Symptom clusters are groups of two or more related concurrent symptoms. Interventions that target symptom clusters may be more efficient than those which address individual symptoms, yet few studies have identified symptom clusters using patient-reported outcomes collected in routine practice. The purpose of this study was to identify symptom clusters de novo using data reported in eSyM, an electronic health record-integrated cancer symptom management program deployed across six large and diverse health systems. Methods: Adults starting chemotherapy to treat thoracic, gastrointestinal, and gynecologic cancers used eSyM to report symptoms twice weekly for up to six months. We analyzed patient-reported symptom data from cycle 1, day 2 (T0), one week (T1), and two (T2), three (T3), and four (T4) weeks later. Patients reported attributes (i.e., frequency, severity, and interference) of 12 symptoms using items derived from the PRO-CTCAE. We calculated a composite grade (0, 1, 2, or 3) for each symptom and conducted an exploratory factor analysis using polychoric correlations and unweighted least squares estimation to identify symptom clusters at each time point. We considered rotated factor loadings ≥|0.30| meaningful and assessed the Eigenvalues, structure, and clinical relevance of two- through four-factor (i.e., cluster) models. Finally, we labeled each cluster according to its predominant symptoms using labels adopted from prior studies of symptom clusters in patients undergoing chemotherapy. Results: Our analytic sample at each time point included 730 (T0), 1605 (T1), 1571 (T2), 1617 (T3), and 1456 (T4) symptom reports. Of the two-, three-, and four-factor models, the two-factor model had the least cross-loading and was the most clinically relevant across time points. The two-factor model accounted for 100% of the total variance in symptoms. In this model, a gastrointestinal symptom cluster was comprised of vomiting, nausea, decreased appetite, trouble drinking, and diarrhea at all time points, while a psychoneurological symptom cluster was comprised of fatigue, pain, anxiety, shortness of breath, and constipation at all time points. Rash was present in the psychoneurological cluster at T0 but was not present in any cluster at T1-T4. Conclusions: Patients experience gastrointestinal and psychoneurological symptom clusters in the first four weeks of chemotherapy. Our findings suggest it is feasible to use routinely collected data to identify symptom clusters using composite PRO-CTCAE grades. Future research will investigate the prevalence of symptom clusters, clinical and demographic characteristics of patients at high risk for severe symptoms, and how to better manage symptom clusters.

Identification of Core Symptom Cluster in Patients With Digestive Cancer: A Network Analysis.

A lack of identified core symptom clusters in digestive cancer patients hinders achieving precision symptom intervention. There are few studies on identifying digestive cancer symptom clusters based on network analysis. The aims of this study were to construct the symptom network of digestive cancer patients and identify the core symptom cluster. A cross-sectional study was conducted among 202 digestive cancer patients. The Chinese version of the MD Anderson Symptom Inventory for gastrointestinal cancer scale was used to assess the symptoms by convenience sampling. R software was used to construct a symptom network and identify core symptom clusters. Edge weight and centrality difference tests were used to test the accuracy of core symptom cluster identification. The most common symptoms were distress, poor appetite, and sadness. The most serious symptoms were poor appetite, disturbed sleep, and fatigue. The core symptom cluster of the psychoemotional symptom group was distress, sadness, and numbness. The centrality index showed that the top 3 in strength were distress (Rs = 1.11), fatigue (Rs = 1.09), and sadness (Rs = 1.04). The edge weight difference test showed that the psychoemotional symptom group had high stability. The psychoemotional symptoms of digestive cancer patients should be given priority for intervention. Network analysis must be extended to the symptom research of cancer patients as soon as possible to provide a scientific basis for symptom management. Nurses must perform comprehensive psychological and emotional assessments, initiate referrals for psychoemotional symptom management and psychological services, and administer pharmacologic and nonpharmacologic interventions to improve appetite loss in digestive cancer patients.

Program of algorithm for pharmacological treatment of major depressive disorder in China: Benefits or not?

BackgroundThis research was designed to investigate Algorithm Guided Treatment (AGT) and clinical traits for the prediction of antidepressant treatment outcomes in Chinese patients with major depressive disorder (MDD). MethodsThis study included 581 patients who had reached treatment response and 406 patients remained non-responded observed after three months of treatment. Sociodemographic factors, clinical traits, and psychiatric rating scales for evaluating therapeutic responses between the two groups were compared. Logistic regression analysis was adopted to determine the risk factors of unresponsive to antidepressant (URA) in MDD. Kaplan-Meier survival analysis was utilized to compare the therapeutic response between AGT and treatment as usual (TAU). ResultsCompared to the MDD responsive to antidepressant (RA) group, the URA group had significantly lower rates of the following clinical traits: married status, anxious distress, moderate to severe depressive symptoms, and higher rates of comorbidity (p-value < 0.05). Logistic Regression Analysis showed that eight clinical traits from psychiatric rating scales, such as anxious characteristics, were correlated positively with URA, while the other eight symptoms, such as autonomic symptoms, were negatively correlated. Time to symptomatic remission was longer in TAU without statistically significant (p-value = 0.11) by log-rank testing. ConclusionsThe factors may affect the therapeutic responses and compliance of patients, increasing the non-response risk for antidepressants. Therapeutic responses might be improved by increasing the clarification and elucidation of different symptom clusters of patients. Benefits on treatment response to AGT were not found in our study, indicating a one-size-fits-all approach may not work.Trial Registration: We registered as a clinical trial at the International Clinical Trials Registry Platform (No. NCT01764867) and obtained ethical approval 2012-42 from SMHC.

A new theory to promote self-management of symptom clusters and healthcare quality in patients with decompensated cirrhosis.

Patients with decompensated cirrhosis, a symptomatic phase of cirrhosis, commonly experience multiple symptoms concurrently, referred to as symptom clusters. Effective self-management of symptoms is known to improve outcomes in various chronic diseases. However, a theory for self-management of symptom clusters in decompensated cirrhosis is lacking. In this study, we applied grounded theory research methodology to construct a new theory of self-management of symptom clusters in these patients. This qualitative study prospectively enrolled 20 patients with decompensated cirrhosis within 1 week after hospital admission. Data related to patients' experiences, needs, perspectives, and abilities related to their symptoms were collected via a semi-structured, in-depth interview and analyzed with Nvivo version 20 software. Grounded theory methodology with 3 coding steps (open, axial, and selective coding) was applied to generate a theory of self-management of symptom clusters. From the step-by-step coding process, 2 core categories or major themes were identified: patients' experiences with symptoms and coping with symptoms. The first major theme included symptom clustering, multidimensionality, recurrence, and specificity, while the second consisted of endogenous motivation, endogenous resistance, and external support needs. A new theory of self-management of symptom clusters was then constructed and delineated to enhance self-management among patients with decompensated cirrhosis. Using patient experience data, we developed a new theory of self-management of symptom clusters in patients with decompensated cirrhosis. Use of this theory has the potential to promote patient self-management and guide healthcare providers in planning optimal treatments and implementing timely interventions, ultimately improving in patient outcomes.

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.

Characterising symptom clusters in patients with atrial fibrillation undergoing catheter ablation

ObjectiveThis study aims to leverage natural language processing (NLP) and machine learning clustering analyses to (1) identify co-occurring symptoms of patients undergoing catheter ablation for atrial fibrillation (AF) and (2)...

Symptoms and symptom clusters in patients newly diagnosed with inflammatory bowel disease: results from the IBSEN III Study

BackgroundPatients with inflammatory bowel disease report multiple symptoms, but the relationships among co-occurring symptoms are poorly understood. This study aimed to examine the prevalence of symptoms and explore symptom clusters and possible associations between symptom clusters and socio-demographic and clinical variables in patients newly diagnosed with inflammatory bowel disease.MethodsThe IBSEN III study is a prospective population-based inception cohort of patients with inflammatory bowel disease. This study used patient data from the three largest hospitals in the study catchment area. The Memorial Symptom Assessment Scale was used to assess the prevalence of symptoms. Symptom clusters were identified using principal component analysis. Possible associations between socio-demographic and clinical variables and symptom cluster membership were estimated using regression analysis.ResultsOf the 573 patients (age, ≥18 years) diagnosed with inflammatory bowel disease, 350 (61.1%) completed the questionnaire (responders). Eleven symptoms were reported by >50% of the responders. The three most prevalent symptoms were bloating (84%), drowsiness (81%), and lack of energy (81%). Three symptom clusters were identified: psychological (56% of the patients), impaired energy (28%), and physical (16%) clusters. Multinomial regression analysis revealed that vitamin D deficiency was significantly associated with the impaired energy cluster (odds ratio=2.49, 95% confidence interval [1.00-6.2],p=0.05).ConclusionsWe found high symptom prevalence in patients newly diagnosed with inflammatory bowel disease. Three distinct symptom clusters were identified, and the psychological cluster includes >50% of the patients. Vitamin D deficiency is the only factor associated with cluster membership, namely the impaired energy cluster.

Neurotransmitter Gene Polymorphisms Are Associated with Symptom Clusters in Patients Undergoing Radiation Therapy

Purpose was to evaluate for associations between the severity of three distinct symptom clusters (ie, sickness-behavior, mood-cognitive, treatment-related) and polymorphisms for 16 genes involved in catecholaminergic, GABAergic, and serotonergic neurotransmission. Patients with breast and prostate cancer (n = 157) completed study questionnaires at the completion of radiation therapy. Memorial Symptom Assessment Scale was used to assess the severity of 32 common symptoms. Three distinct symptom clusters were identified using exploratory factor analysis. Associations between the symptom cluster severity scores and neurotransmitter gene polymorphisms were evaluated using regression analyses. Severity scores for the sickness-behavior symptom cluster were associated with polymorphisms for solute carrier family 6 (SLC6A) member 2 (SLC6A2), SLC6A3, SLC6A1, and 5-hydroxytryptamine receptor (HTR) 2A (HTR2A) genes. For the mood-cognitive symptom cluster, severity scores were associated with polymorphisms for adrenoreceptor alpha 1D, SLC6A2, SLC6A3, SLC6A1, HTR2A, and HTR3A. Severity scores for the treatment-related symptom cluster were associated with polymorphisms for SLC6A2, SLC6A3, catechol-o-methyltransferase, SLC6A1, HTR2A, SLC6A4, and tryptophan hydroxylase 2. Findings suggest that polymorphisms for several neurotransmitter genes are involved in the severity of sickness-behavior, mood-cognitive, and treatment-related symptom clusters in oncology patients at the completion of radiation therapy. Four genes with various associated polymorphisms were common across the three distinct symptom clusters (ie, SLC6A2, SLC6A3, SLC6A1, HTR2A) which suggest that these clusters have common underlying mechanisms.

A multi-modal intervention for managing the fatigue–sleep disturbance–depressed mood symptom cluster in breast cancer patients undergoing chemotherapy: A pilot study

ObjectiveTo examine the feasibility and acceptability of a multi-modal intervention for managing the cancer-related fatigue–sleep disturbance–depressed mood (F-S-D) symptom cluster in patients with breast cancer (BC) and receiving chemotherapy in Hong Kong, and the preliminary effects of such intervention on the occurrence of the F-S-D symptom cluster in these patients. MethodsThis study was a single-blind randomized controlled trial. Patients with BC scheduled for chemotherapy were recruited. Intervention participants received a weekly nurse-led multi-modal intervention lasting 7 weeks. The feasibility parameters and adverse events were assessed using logbook records. Acceptability was evaluated using a program evaluation questionnaire. F-S-D symptoms and quality of life (QOL) were measured at baseline (T0), upon intervention completion (T1), and 3 months after intervention completion (T2). Generalized estimating equation analyses were used. ResultsFifty participants were enrolled. The eligibility and enrollment rates were 11% and 87.7%, respectively. The rate of adherence to the intervention was 96%. No adverse events were reported. All participants were satisfied with the intervention, which had significant effects in terms of reducing the occurrence of the F-S-D symptom cluster at T2 (P ​= ​0.035) and improving QOL at T1 and T2 (T1: P ​= ​0.035; T2: P ​= ​0.012). ConclusionsThe multi-modal intervention is a feasible, acceptable, and safe intervention that demonstrated preliminary positive effects in managing the F-S-D symptom cluster and improving QOL in patients with BC and receiving chemotherapy in Hong Kong. This study provides key insights into F-S-D symptom cluster management in patients with BC. Trial registrationChiCTR2100047819 (Chinese Clinical Trial Register).