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

Symptom clusters of patients with advanced thyroid cancer: a cross-sectional study

PURPOSE

To investigate and analyze the symptom clusters of patients with advanced thyroid cancer and provide a basis for developing targeted symptom management measures.

METHODS

Patients who visited a multidisciplinary outpatient service for advanced thyroid cancer at a tertiary A hospital in Sichuan Province from April 2022 to April 2023 were selected using convenience sampling. A cross-sectional survey was conducted using the M.D. Anderson Symptom Inventory-Thyroid Cancer module (MDASI-THY). Symptom clusters were extracted by exploratory factor analysis.

RESULTS

Disturbed sleep had the highest incidence (75.7%) and severity (3.0 points), while mood distress had the highest incidence (63.5%) and severity (2.0 points) of symptom interference. Three symptom clusters were identified: mood-fatigue-sleep, digestive tract-sensation, and thyroid cancer-specific symptom clusters.

CONCLUSION

Patients with advanced thyroid cancer have multiple symptom clusters that seriously affect their daily lives. Health care professionals should conduct targeted observation and preventive treatment to reduce the burden of symptoms on patients.

Collaborative Filtering for the Imputation of Patient Reported Outcomes

This study addresses the prevalent issue of missing data in patient-reported outcome datasets, particularly focusing on head and neck cancer patient symptom ratings sourced from the MD Anderson Symptom Inventory. Given that many data mining and machine learning algorithms necessitate complete datasets, the accurate imputation of missing data as an initial step becomes crucial. In this study we propose, for the first time, the use of collaborative filtering for imputing missing head and neck cancer patient symptom ratings. Two configurations of collaborative filtering, namely patient-based and symptom-based, leverage known ratings to infer the missing ones. Additionally, this study compares the performance of collaborative filtering with alternative imputation methods such as Multiple Imputation by Chained Equations, Nearest Neighbor Imputation, and Linear interpolation. Performance is compared using Root Mean Squared Error and Mean Absolute Error metrics. Findings demonstrate that collaborative filtering is a viable and comparatively superior approach for imputing missing patient symptom data.

Co-occurrence of symptoms after radiochemotherapy in locally advanced cervix cancer patients: a cluster analysis

BACKGROUND

State of the art combined radiochemotherapy and image-guided brachytherapy for locally advanced cervical cancer (LACC) has shown improved disease control and survival as well as a significant reduction of organ related morbidity. However, LACC cancer survivors are still experiencing a spectrum of symptoms. The aim of this study was to identify co-occurring symptoms in cervix cancer survivors by using patient-reported outcome and physician assessed morbidity.

MATERIALS AND METHOD

EMBRACE I is a multicenter prospective observational study with 1416 LACC patients (2008-2015). Information on physician-assessed morbidity and patient-reported outcome was assessed at baseline and at regular follow-ups up with the CTCAE v.3 and EORTC-C30/CX24, respectively. Patients with at least 2 years of follow-up were included and data from 3 months to 2 years was used in the analysis. Factor analysis was used on both EORTC and CTCAE data with symptoms and follow-ups as observations. The extracted factors represent clusters of symptoms. Subsequently, regression models were built to investigate associations between the symptom clusters and QOL.

RESULTS

The analysis included 742 patients. Despite the differences in the definition of physician-assessed and patient-reported symptoms, similar clusters are identified by the two assessment methods. Three main organ-related clusters are recognized for urinary, gastro-intestinal and vaginal morbidity. Furthermore, a general symptoms cluster where fatigue, pain, insomnia, neuropathy, and hot flashes have large weights is found. Lastly, a cluster with nausea, vomit and lack of appetite is also identified. The general, gastrointestinal and nausea clusters show significant associations with general QOL.

CONCLUSIONS

This analysis on both PRO and physician-assessed morbidity found a cluster associated with general symptoms and organ-related symptom clusters (urinary, gastrointestinal, vaginal). This shows that LACC survivors experience a variety of co-occurring symptoms. Our analysis also shows that the cluster of general symptoms is associated with a decrease in QOL.

Self-management of patients with tracheostomy in the home setting: a scoping review

PURPOSE

The aim of this study was to create a model of patient-centered outcomes with respect to self-management tasks and skills of patients with a tracheostomy in their home setting.

METHODS

A scoping review using four search engines was undertaken (Medline, CINAHL, PsycINFO, Cochrane Library) to identify studies relevant to this issue and published since 2000. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statements for Scoping Reviews (PRISMA-ScR), the Joanna Briggs Institute (JBI) approach of conducting and reporting a scoping review, and the Participants, Concept, Context (PCC) scheme were employed. The following elements of the framework synthesis study data were screened, and presented based on the self-management model of Lorig and Holman.

RESULTS

34 publications from 17 countries met the criteria for study inclusion: 24 quantitative, 8 qualitative and 2 mixed methods designs. Regarding the dimensions of self-management, 28 articles reported on "managing the therapeutic regimen", 27 articles discussed "managing role and behavior changes", and 16 articles explored "managing emotions". A model of self-management of patients with tracheostomy was developed, which placed the patient in the center, since it is this individual who is completing the tasks and carrying out his or her skill sets.

CONCLUSION

This scoping review represents the first comprehensive overview and modeling of the complex self-management tasks and skills required of patients with tracheostomy in their home setting. The theoretical model can serve as a cornerstone for empirical intervention studies to better support this patient-centered outcome for this population in the future.

Associations of inflammation with neuropsychological symptom cluster in patients with Head and neck cancer: A longitudinal study

Purpose

Head and neck cancer (HNC) patients may experience multiple co-occurring neuropsychological symptoms (NPS) cluster, including fatigue, depression, pain, sleep disturbance, and cognitive impairment. While inflammation has been attributed as a key mechanism for some of these symptoms, its association with the NPS as a cluster of symptoms is unknown. Thus, the aim of this study was to examine the association between peripheral inflammation and NPS cluster among HNC patients over cancer treatment (radiotherapy with or without chemotherapy).

Methods

HNC patients were recruited and followed at pre-treatment, end of treatment, three months and one-year post-treatment. Plasma inflammatory markers, including C-reactive protein (CRP), tumor necrosis factor-alpha (TNFA), soluble tumor necrosis factor receptor-2 (sTNFR2), interleukin-1 beta (IL1-β), interleukin-6 (IL-6), interleukin-10 (IL-10), monocyte chemotactic protein-1 (MCP-1), and interleukin-1 receptor antagonist (IL-1RA) and patient-reported NPS cluster were collected at the 4 time points. Associations between inflammatory markers and the NPS cluster were analyzed using linear mixed-effects models and generalized estimating equations (GEE) models controlling covariates.

Results

147 HNC patients were eligible for analysis. 56% of the patients received chemoradiotherapy as treatment. The highest NPS cluster score was reported at the end of treatment, which gradually decreased over time. An increase in inflammatory markers including CRP, sTNFR2, IL-6 and IL-1RA was associated with higher continuous NPS cluster scores (p<0.001, p = 0.003, p<0.001, p<0.001; respectively). GEE further confirmed that patients with at least two moderate symptoms had elevated sTNFR2, IL-6, and IL-1RA (p = 0.017, p = 0.038, p = 0.008; respectively). Notably, this positive association between NPS cluster and inflammatory markers was still significant at one-year post-treatment for CRP (p = 0.001), sTNFR2 (p = 0.006), and IL-1RA (p = 0.043).

Conclusions

Most HNC patients experienced NPS clusters over time, especially immediately after the end of treatment. Elevated inflammation, as represented by inflammatory markers, was strongly associated with worse NPS cluster over time; this trend was also notable at one-year post-treatment. Our findings suggest that peripheral inflammation plays a pivotal role in the NPS cluster over cancer treatment, including long-term follow-ups. Interventions on reducing peripheral inflammation may contribute to alleviating the NPS cluster in cancer patients.

Symptom Cluster Experiences of Patients Operated for Oral Cancer: A Mixed Methods Study

OBJECTIVE

This convergent mixed methods study aimed to obtain a comprehensive understanding of symptom cluster experiences in patients with oral cancer. Survey and phenomenological interviews were conducted in parallel to identify distinct patient subgroups based on symptom cluster experiences along with their predictors and explore experiences of living with symptom clusters, respectively.

DATA SOURCES

A convenience sample of 300 patients with oral cancer who had completed surgery provided the quantitative data, and a maximum variation purposive subsample of 20 participants, drawn from the survey sample, provided the qualitative data. Agglomerative hierarchical cluster analysis was used to identify subgroups, multivariate analyses were done to identify predictors, and thematic analysis was used for patient narratives.

CONCLUSION

Almost 94% of the survey participants had two or more co-occurring symptoms. The four most severe and prevalent symptoms were dysphagia, problems with teeth or gums, speech difficulty, and dry mouth. A distinct subgroup consisting of 61% of patients reported severe dysphagia and teeth problems, which was associated with age, oral cancer stage and site. Interviews revealed the causes and the context influencing the perception and response to these symptoms. Thus, the quantitative data provided information on severity and patient subgroups based on symptom cluster experiences, while the qualitative data validated these conclusions and additionally provided in-depth details and meaningful insight on perceived causes and contextual influences of their experiences. This comprehensive picture of symptom cluster experiences can aid in the development of patient-centered interventions for people with oral cancer.

IMPLICATIONS FOR NURSING PRACTICE

An interdisciplinary approach to targeting concurrent symptoms incorporating psychological and physical interventions is necessary. Older patients treated for Stage IV cancers and for buccal mucosa tumors are at high-risk of having severe dysphagia postoperatively, and these patients should be targeted for dysphagia interventions. The contextual factors play an important role in developing patient-centered interventions.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A network analysis of self-reported psychoneurological symptoms in patients with head and neck cancer undergoing intensity-modulated radiotherapy

BACKGROUND

Patients with head and neck cancer experience psychoneurological symptoms (PNS) (i.e., depression, fatigue, sleep disturbance, pain, and cognitive dysfunction) during intensity-modulated radiotherapy (IMRT) that decrease their functional status, quality of life, and survival rates. The purpose of this study was to examine and visualize the relationships among PNS within networks over time and evaluate for demographic and clinical characteristics associated with symptom networks.

METHODS

A total of 172 patients (mean age, 59.8 ± 9.9 years; 73.8%, male; 79.4%, White) completed symptom questionnaires four times, namely, before IMRT (T1), 1 month (T2), 3 months (T3), and 12 months (T4) post IMRT. Network analysis was used to examine the symptom-symptom relationships among PNS. Centrality indices, including strength, closeness, and betweenness, were used to describe the degrees of symptom network interconnections. Network comparison test was used to assess the differences between two symptom networks.

RESULTS

Depression was associated with the other four symptoms, and fatigue was associated with the other three symptoms across the four assessments. Based on the centrality indices, depression (rstrength  = 1.3-1.4, rcloseness  = 0.06-0.08, rbetweeness  = 4-10) was the core symptom in all symptom networks, followed by fatigue. Female gender, higher levels of stress, and no alcohol use were associated with stronger symptom networks in network global strength before IMRT.

CONCLUSION

Network analysis provides a novel approach to gain insights into the relationships among self-reported PNS and identify the core symptoms and associated characteristics. Clinicians may use this information to develop symptom management interventions that target core symptoms and interconnections within a network.

LAY SUMMARY

This study describes the symptom-symptom relationships for five common symptoms in patients with head and neck cancer receiving radiotherapy. Depression and fatigue appeared to be two core symptoms that were connected with sleep disturbance, pain, and cognitive dysfunction within a network. Several characteristics (i.e., female, higher stress, no alcohol use) were associated with stronger symptom networks.

Symptomatic Features and Factors Associated With Do-Not-Resuscitate Consent in Advanced Cancer Patients Admitted to Palliative Care Ward

This study aimed to conduct a retrospective cross-sectional study to investigate the prevalence of symptoms and symptom clusters on sociodemographic and disease characteristics, as well as factors associated with Do-Not-Resuscitate (DNR) consent. Advanced cancer patients were enrolled between 2018 and 2020 with available data. Demographic and clinical data were obtained for analysis from Hospital Information System (HIS) in China. Symptom clusters were extracted by hierarchical cluster analysis. Chi-square test and multiple logistic regression were conducted to investigate the prevalence characteristics of symptoms and influencing factors of DNR consent, respectively. 798 advanced cancer patients were enrolled. The most prevalent symptoms were pain (93%), anorexia (36.5%), and sleep disorders (34.2%). High heart rate was associated with poor performance status and more symptoms. Three clusters were extracted: fatigue-related, respiratory-circulatory system, and digestive system symptom clusters. The incidence of symptoms was statistically significant in age, gender, education level, residence, BMI, performance status, distress score, ADL, and primary pain level. The DNR signature rate was 15.5%. Female, distant metastasis, in-ward rescue, and appearance of dyspnea were independent influencing factors of DNR signature.Chinese hospitalized cancer patients had more symptoms burden that were influenced by various demographic characteristics, especially pain and fatigue-related symptoms. Concerning the trajectory of vital signs is important among advanced cancer patients. The DNR signature rate was lower and our finding indicating an urgency to accurately assess the prognosis and give more palliative care education to enhance DNR rates and early signing in Chinese context.

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

OBJECTIVE

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

DATA SOURCES

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

CONCLUSION

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

IMPLICATIONS FOR NURSING PRACTICE

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

Symptom Clusters and Quality of Life in Cervical Cancer Patients Receiving Concurrent Chemoradiotherapy: The Mediating Role of Illness Perceptions

OBJECTIVES

Although studies shows that symptom clusters and illness perceptions are negatively associated with quality of life (QoL), it is unclear how these variables of cervical cancer patients who receive concurrent chemoradiotherapy (CCRT) relate to each other. This study aimed to identify the symptom clusters in cervical cancer patients who receive CCRT and evaluate the mediating effect of illness perceptions on the relationship between symptom clusters and QoL.

METHODS

A cross-sectional survey was conducted on 286 cervical cancer patients receiving CCRT from October 2019 to October 2020. M.D. Anderson Symptom Inventory, Brief Illness Perception Questionnaire, and Functional Assessment Cancer Therapy-Cervix were applied to investigate the symptom clusters, illness perceptions and QoL of the participants, respectively. Exploratory factor analysis was conducted to identify symptom clusters. The relationships among symptom clusters, illness perceptions, and QoL were analyzed with the structural equation modeling.

RESULTS

A total of four symptom clusters were identified, including psychological status symptom cluster, therapy side-effect symptom cluster, sickness symptom cluster, and gastrointestinal symptom cluster (χ² = 1,552.282, Df = 78, P < 0.001). Symptom clusters, illness perceptions, and QoL were significantly correlated. Symptom clusters had significant direct (β = -0.38, P < 0.001) and indirect effects (β = -0.21, P < 0.001) on QoL.

CONCLUSION

Illness perceptions played a significant mediating role between symptom clusters and QoL in cervical cancer patients receiving CCRT. Strategies like prompting effective symptom management for the purposes of alleviating illness perceptions may contribute to improving their QoL.