Symptom cluster trajectories and sentinel symptoms during the first cycle of chemotherapy in patients with lung cancer

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.

Symptom clusters, fear of disease progression, and quality of life in postoperative gastric cancer patients: a cross-sectional study

BACKGROUND

Gastric cancer is a common tumor globally. Surgery is the preferred treatment for gastric cancer. Yet, little is known about its symptom clusters, fear of disease progression, and quality of life (QoL). This study aims to investigate the severity of symptom clusters, fear of disease progression, and quality of life of postoperative gastric cancer patients; to analyze the correlation between symptom clusters, fear of disease progression, and quality of life of postoperative gastric cancer patients; and to provide theoretical bases for the development of an intervention plan to enhance the quality of life of postoperative gastric cancer patients.

METHODS

A convenience sampling method was used to select 158 postoperative gastric cancer patients from a tertiary hospital in Xiamen City from January 2023 to April 2023 for the study. Data were collected using the General Information Evaluation Form, M.D. Anderson Symptom Inventory-Gastrointestinal Cancer Module (MDASI-GI), Fear of Progression Questionnaire-Short Form (FoP-Q-SF), and Functional Assessment of Cancer Therapy-General (FACT-G). Data were analyzed with EpiData 3.1 and SPSS 26.0. Symptom clusters were extracted via exploratory factor analysis. Differences in QoL based on patient characteristics were analyzed using t tests or one-way analysis of variance (ANOVA). Pearson correlation and multiple linear regression analyses were used to explore relationships among symptom clusters, fear of disease progression, and QoL.

RESULTS

The overall quality of life score in the FACT-G scale was (52.32 ± 10.58), of which the social/family status score was (16.47 ± 3.62), the physical status score was (14.24 ± 5.66), the functional status was (11.35 ± 4.48), and the emotional status score was (10.25 ± 3.53). The fear of disease progression score of postoperative gastric cancer patients was (37.37 ± 6.37), of which the physical health dimension score was (21.58 ± 4.01), and the social/family dimension score was (15.74 ± 4.07). Two symptom clusters were identified: physical/emotional sickness and gastrointestinal symptom cluster. The results of Pearson correlation analysis showed that symptom cluster severity was negatively correlated with quality of life (r =  - 0.508, P < 0.01); symptom cluster severity was significantly positively correlated with fear of disease progression (r = 0.260, P < 0.01); and fear of disease progression was significantly negatively correlated with quality of life (r =  - 0.194, P < 0.05). Multiple linear regression analyses showed that the physical/emotional sickness symptom cluster, physical health fears, and physical state of postoperative gastric cancer patients were the affecting factors of quality of life (P < 0.001).

CONCLUSION

Two symptom clusters were identified in postoperative gastric cancer patients in mainland China. Fear of disease progression was at a medium-high level, and QoL was at a medium level. Common symptoms included fatigue, pain, and worry. The physical state, physical health, and the physical/emotional sickness symptom cluster affect the quality of life of postoperative gastric cancer patients. Targeted clinical interventions are necessary to improve QoL in postoperative gastric cancer patients.

Identification of the Core Nutrition Impact Symptoms Cluster in Patients with Lung Cancer During Chemotherapy: A Symptom Network Analysis

OBJECTIVES

Lung cancer patients undergoing chemotherapy are present in multiple Nutrition Impact Symptoms (NIS). There have been no studies utilizing symptom networks to identify core NIS in lung cancer patients undergoing chemotherapy, it is necessary to identify core symptoms for effective and precise symptom management. We aimed to construct a symptom network of NIS in lung cancer patients receiving chemotherapy, and explore the core Nutrition Impact Symptoms cluster.

METHODS

A cross-sectional survey was conducted among 315 patients with lung cancer. The Patient-Generated Subjective Global Assessment-Short Form was used to assess the prevalence and severity of NIS. We constructed a symptom network and identified centrality indexes using R packages.

RESULTS

Fatigue emerged as the most prevalent and severe symptom, affecting 87% of participants, with an intensity of 3.0 ± 1.3. The network density was measured at 0.5. Strength centrality showed a stability coefficient of 0.7, with fatigue (Rs = 0.73), lack of appetite (Rs = 1.02), and nausea (Rs = 0.70) ranking as the top three symptoms. For betweenness centrality, the stability coefficient was 0.3, highlighting fatigue (Rb = 12), lack of appetite (Rb = 34), and emotional change (Rb = 18) as the primary symptoms.

CONCLUSIONS

This study identified a core symptom cluster consisting of fatigue, lack of appetite, and emotional change. These findings provide valuable insights for developing targeted symptom management strategies and interventions for this patient population in the future.

IMPLICATIONS FOR NURSING PRACTICE

Nurses need to comprehensively consider the interaction of multidimensional symptoms to provide lung chemotherapy cancer with targeted symptom management strategies and intervention guidance to reduce the burden of symptoms and improve quality of life.

Exploration of symptom cluster patterns and their trajectory in esophageal cancer surgery patients

PURPOSE

To investigate symptom burden and symptom cluster trajectories in patients undergoing surgery for esophageal cancer.

METHODS

A convenience sample of 210 patients who underwent thoracoscopic surgery for esophageal cancer was included from July to December 2023. The symptoms of the patients were evaluated at the following time points: preoperatively (T0), 1-3 days postoperatively (T1), 7 days postoperatively (T2), 1 month postoperatively (T3), and 3 months postoperatively (T4). This was done via the Chinese version of the MD Anderson Symptom Scale and the Supplementary Questionnaire for Perioperative Esophageal Cancer Symptoms. Exploratory factor analysis was used to identify symptom clusters, and latent class growth modeling was used to analyze the trajectories of each different symptom cluster.

RESULTS

Exploratory factor analysis revealed the presence of four symptom clusters: mood-related symptom clusters (worst at T1, T2, and T4), gastrointestinal symptom clusters (worst at T0), fatigue-related symptom clusters (worst at T3), and surgery-related symptom clusters, with cumulative variance contribution rates of 64.34%, 62.29%, 68.23%, 70.29%, and 63.82%, respectively. The latent category growth model identified the existence of 2-3 distinct trajectories in each symptom cluster.

CONCLUSION

This study identified 4 distinct symptom clusters in patients undergoing esophageal cancer surgery. The mood-related and gastrointestinal symptom clusters exhibited worsening and recurrence within 7 days post-surgery, necessitating particular attention. A subset of patients in the fatigue-related symptom cluster showed a tendency for continued exacerbation, emphasizing the need for long-term monitoring. Furthermore, symptom management strategies can be prioritized based on the severity of the symptom clusters.

Effectiveness of non-pharmacological interventions in managing symptom clusters among lung cancer patients: a systematic review

BACKGROUND

Non-pharmacological interventions, as complements to pharmacological treatments, are widely employed for managing symptom clusters in patients with lung cancer. Although numerous systematic reviews and meta-analyses have explored the effects of these interventions, most studies have centred on the broader cancer population and specific symptom clusters. This review aims to consolidate existing non-pharmacological interventions and assess their effectiveness in managing symptom clusters among lung cancer patients.

METHODS

A comprehensive literature search, encompassing eight databases from inception to October 1, 2024, was conducted. Two independent reviewers carried out the study selection, quality assessment, and data extraction. Methodological quality was evaluated using the Cochrane Risk-of-Bias 2 tool and the Risk of Bias in Non-randomized Studies of Interventions. The findings were synthesized narratively based on intervention type and supplemented by meta-analysis using RevMan 5.4 software. The study protocol was registered with PROSPERO (CRD42023467406).

RESULTS

This systematic review comprised 15 relevant studies involving 1,692 patients, published between 2011 and 2024. The analysis revealed the effectiveness of psychological, educational, and complementary or alternative medicine interventions in alleviating the severity of most symptom clusters. However, the efficacy of exercise-based and multimodal interventions remained inconclusive. The meta-analysis demonstrated a positive impact of non-pharmacological interventions on depression compared with the control conditions (SMD = -0.30, 95% CI [-0.46, -0.15], p < 0.01, I2 = 6%). Additionally, the educational intervention subgroup showed low heterogeneity and effectively improved fatigue (SMD = -0.50, 95% CI [-0.68, -0.33], p < 0.01, I2 = 0%).

CONCLUSIONS

Psychological and educational interventions have proven effective in managing symptom clusters in lung cancer patients. However, further research is needed to explore the effects of exercise, multimodal approaches, and complementary or alternative medicine. To enhance symptom management, future research could focus on core symptom clusters.

Exploring Central and Bridge Symptoms in Patients with Lung Cancer: A Network Analysis

OBJECTIVES

This study aimed to identify symptom clusters in lung cancer patients undergoing chemotherapy and the central and bridge symptoms within each symptom cluster.

METHODS

In this cross-sectional study, 1,255 patients with lung cancer were recruited through convenience sampling at Nanfang Hospital. Patient symptom burden was assessed using the M.D. Anderson Symptom Inventory (MDASI) and the Lung Cancer module of the MDASI (MDASI-LC). Symptom clusters were identified using the Walktrap algorithm, and central and bridge symptoms in the symptom clusters were identified by network analysis.

RESULTS

The patients included 818 (65.18%) males and 437 (34.82%) females with a mean age of 56.56 ± 11.78 years. Four symptom clusters were identified: fatigue, gastrointestinal, psychoneurological and respiratory. Their central symptoms were fatigue, vomiting, distress and hemoptysis, respectively, and their bridge symptoms were pain, vomiting, dry mouth and shortness of breath.

CONCLUSIONS

Lung cancer symptoms show certain strong correlations with each other, resulting in symptom clusters. Central symptoms may influence other symptoms within a symptom cluster, and bridge symptoms might impact the density of the symptom network. This study identified central and bridge symptoms in lung cancer patients undergoing chemotherapy. Targeting these symptoms with interventions for symptom clusters could make symptom management more precise and effective.

IMPLICATIONS FOR NURSING PRACTICE

In clinical settings, the burden of symptom clusters may be reduced by intervening against the central symptoms of these symptom clusters. Alternatively, if the objective is to diminish the connections between different symptom clusters and holistically alleviate the overall burden, interventions focused on bridge symptoms may be employed.

Sentinel and networked symptoms in patients with breast cancer undergoing chemotherapy

PURPOSE

It was designed to identify the symptom clusters and sentinel symptoms among patients with breast cancer receiving chemotherapy at the community level, and to explore core and bridge symptoms at the global level.

METHODS

A cross-sectional survey was conducted using the MD Anderson Symptom Inventory. Patients with breast cancer receiving chemotherapy, recruited from the "Be Resilient to Breast Cancer" project between January 2023 and December 2023, were included in the study. Symptom clusters and their sentinel symptoms were identified using exploratory factor analysis and Apriori algorithm. Core and bridge symptoms were identified using network analysis.

RESULTS

A total of 468 patients with breast cancer participated in the current study. At the community level, three symptom clusters and their corresponding sentinel symptoms were identified: a gastrointestinal symptom cluster (with nausea as the sentinel symptom), a psycho-sleep-related symptom cluster (with distress as the sentinel symptom), and a neurocognition symptom cluster (with dry mouth as the sentinel symptom). At the global level, fatigue emerged as the core symptom, while disturbed sleep and lack of appetite as bridge symptoms.

CONCLUSION

Addressing nausea, distress, and dry mouth are imperative for alleviating specific symptom clusters at the community level. Furthermore, targeting fatigue, disturbed sleep, and lack of appetite are crucial to break the interactions among diverse symptoms at the global level.

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

PURPOSE

This study was designed to evaluate the effect of acupuncture on cough, expectoration, and shortness of breath in lung cancer patients.

METHODS

Between 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.

RESULTS

Compared 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.

CONCLUSIONS

Acupuncture using LU7, LU9, BL13, and BL20 can relieve the cough of lung cancer patients, but not relieve expectoration and shortness of breath.

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.

Identifying symptom clusters and temporal interconnections in patients with lung tumors after CT-guided microwave ablation: A network analysis

PURPOSE

To explore symptom clusters and interrelationships using a network analysis approach among symptoms in patients with lung tumors who underwent computed tomography (CT)-guided microwave ablation (MWA).

METHODS

A longitudinal study was conducted, and 196 lung tumor patients undergoing MWA were recruited and were measured at 24 h, 48 h, and 72 h after MWA. The Chinese version of the MD Anderson Symptom Inventory and the Revised Lung Cancer Module were used to evaluate symptoms. Network analyses were performed to explore the symptom clusters and interrelationships among symptoms.

RESULTS

Four stable symptom communities were identified within the networks. Distress, weight loss, and chest tightness were the central symptoms. Distress, and weight loss were also the most key bridge symptoms, followed by cough. Three symptom networks were temporally stable in terms of symptom centrality, global connectivity, and network structure.

CONCLUSION

Our findings identified the central symptoms, bridge symptoms, and the stability of symptom networks of patients with lung tumors after MWA. These network results will have important implications for future targeted symptom management intervention development. Future research should focus on developing precise interventions for targeting central symptoms and bridge symptoms to promote patients' health.

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).

Predictors of sleep quality components in patients undergoing transarterial chemoembolisation: a cross-sectional study

PURPOSE

Patients undergoing transarterial chemoembolisation experience postembolisation symptoms and interferences affecting sleep quality, which require intervention. The study aimed to identify the predictors of sleep quality components in patients undergoing transarterial chemoembolisation.

METHODS

This study included two groups of participants: 50 patients undergoing transarterial chemoembolisation and 45 nurses caring for them. Data were collected from September to November 2022 using a structured questionnaire, and analysed using descriptive statistics, the t-test, analysis of variance, Spearman's rank correlation, and multiple regression analysis using the SPSS 27.0 program (IBM Corp., Armonk, NY, USA).

RESULTS

The mean sleep quality score was 40.28±14.10. Heat sensation (t=-2.08, p=.043) and fatigue (t=-4.47, p<.001) predicted sleep fragmentation in 38.6% of the patients. Abdominal pain (t=-2.54, p=.014), vomiting (t=-2.21, p=.032), and the expected fatigue by the nurses (t=2.68, p=.014) predicted sleep length in 41.7% of patients. Abdominal pain (t=-2.05, p=.046) explained 42.9% of sleep depth.

CONCLUSION

Based on the predictors of sleep quality components obtained in this study, strategies to improve sleep quality tailored to patients undergoing transarterial chemoembolisation should be developed. This study highlighted the need to bridge the gap between patients' and nurses' expected fatigue and its contribution to sleep fragmentation and sleep length. It also highlighted the importance of noncontact temperature measurement, controlling vomiting, and pain relief for improving sleep length in patients undergoing transarterial chemoembolisation.

Symptom clusters and their impact on quality of life among Chinese patients with lung cancer: A cross-sectional study

PURPOSE

To investigate the symptom clusters of Chinese patients with lung cancer, and explore their impact on quality of life (QoL) and each of its functioning.

METHOD

A cross-sectional study was conducted between October 2022 and April 2023 among 219 lung cancer patients at a general hospital in Sichuan Province. Data were collected using a general information questionnaire, the MD Anderson Symptom Inventory, and the EORTC QLQ-C30. R within the RStudio platform was used to conduct descriptive statistics, exploratory factor analysis and multiple regression analysis.

RESULTS

Psychoneurological, respiratory, gastrointestinal and fatigue-related symptom clusters were identified, each of which was significantly negatively correlated with overall QoL, global health status/QoL and each functioning. The respiratory (β = -0.60, P = 0.02) and fatigue-related symptom cluster (β = -0.86, P = 0.02) were predictors of global health status/QoL; the fatigue-related symptom cluster predicted physical (β = -1.68, P < 0.01), role (β = -1.63, P < 0.01) and cognitive functioning (β = -1.45, P < 0.01); the psychoneurological symptom cluster was a predictor of patients' emotional functioning (β = -1.26, P < 0.01); and the psychoneurological (β = -0.81, P < 0.01) and gastrointestinal symptom cluster (β = -0.60, P = 0.05) predicted social functioning.

CONCLUSIONS

Respiratory and fatigue-related symptom clusters were strong predictors of global health status/QoL; fatigue-related, psychoneurological and gastrointestinal symptom clusters had a negative impact on patients' functioning. Nurse practitioners should pay more attention to monitoring respiratory and fatigue-related symptom clusters to identify high-risk populations in time, and tailored interventions based on symptom clusters are needed to synergistically reduce the symptom burden, thereby improving patients' QoL.