Cancer Symptom Clusters: Clinical and Research Methodology

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.

Non-invasive surrogate markers of pulmonary hypertension are associated with poor survival in patients with cancer

BACKGROUND

Cancer is one of the leading causes of death worldwide, and cardiopulmonary comorbidities may further adversely affect cancer prognosis. We recently described lung cancer-associated pulmonary hypertension (PH) as a new form of PH and comorbidity of lung cancer. While patients with lung cancer with PH had significantly reduced overall survival compared with patients without PH, the prevalence and impact of PH in other cancers remain unclear.

METHODS

In this retrospective, observational cohort study, we analysed the prevalence and impact of PH on clinical outcomes in 1184 patients with solid tumours other than lung cancer, that is, colorectal, head and neck, urological, breast or central nervous system tumours, using surrogate markers for PH determined by CT.

RESULTS

PH prevalence in this cohort was 10.98%. A Cox proportional hazard model revealed a significant reduction in the median survival time of patients with cancer with PH (837 vs 2074 days; p<0.001). However, there was no correlation between pulmonary metastases and PH. A subgroup analysis showed that PH was linked to decreased lung and cardiac function. Additionally, PH was associated with systemic arterial hypertension (p<0.001) and coronary artery disease (p=0.014), but not emphysema.

CONCLUSIONS

In this study, fewer patients with cancer had surrogate parameters for PH compared with previously published results among patients with lung cancer. Consequently, the prevalence of PH in other cancers might be lower compared with lung cancer; however, PH still has a negative impact on prognosis. Furthermore, our data does not provide evidence that lung metastases cause PH. Thus, our results support the idea that lung cancer-associated PH represents a new category of PH. Our results also highlight the importance of further studies in the field of cardio-oncology.

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.

Latent profile analysis for assessing symptom clusters in women with breast cancer

PURPOSE

To identify symptom clusters among breast cancer survivors and investigate differences in health-related quality of life (HRQoL) and distress based on these discerned symptom clusters using latent profile analysis.

METHODS

We enrolled 655 adult breast cancer survivors aged 19 years and older, registered with the Cancer Survivor Integrated Supportive Center from May 2020 to July 2022. The study measured five symptoms-pain, fatigue, insomnia, anxiety, and depression-using a Visual Analogue Scale ranging from 0 to 10 points. Distress was measured using the National Comprehensive Cancer Network Distress Thermometer, with scores ranging from 0 to 10 points. HRQoL was determined using the EuroQol-5 Dimension questionnaire. Data analysis was conducted using the Jamovi and Mplus 8.8 software programs.

RESULTS

The Cluster with Few Symptoms (46.8%) was the most common, whereas the Psychological Cluster with a very high degree of depression and anxiety accounted for 20.0%, and the Moderate symptom cluster with symptoms of 3 or more points accounted for 14.4%. Distress scores were relatively high in the Psychological Cluster and the Pain-Fatigue-Insomnia Cluster, and were lowest in the Cluster with Few Symptoms (F = 103.92, p < 0.001). HRQoL scores were highest in the Cluster with Few Symptoms and lowest in the Pain-Fatigue-Insomnia Cluster (F = 177.62, p < 0.001).

CONCLUSIONS

Approximately half of breast cancer survivors who had completed the major treatment experienced persistent high symptoms such as depression and anxiety or pain, fatigue, and insomnia.

IMPLICATIONS FOR CANCER SURVIVORS

These findings provide foundational data for developing tailored intervention strategies and programs based on symptom experiences.

Symptom cluster among cancer survivors from a nationally representative survey: a network analysis

PURPOSE

To identify the symptom cluster among cancer survivors and examine their subgroup differences via network analysis based on nationally representative data.

METHODS

This cross-sectional study included 2966 survivors participating in the 2020 National Health Interview Survey (NHIS). Participants self-reported the presence of 14 symptoms capturing four clusters (physical, somatic, sleep, and psychologic problems). Network analysis models were used to reveal the relationships between symptoms and those interactions. Network comparison tests were applied to compare subgroups.

RESULTS

The core symptoms of the symptom cluster were fatigue (Bet = 33, Clo = 0.0067, Str = 0.9397), pain (Bet = 11, Clo = 0.0060, Str = 0.9226), wake up well rested (Bet = 25, Clo = 0.0057, Str = 0.8491), and anxiety (Bet = 5, Clo = 0.0043, Str = 0.9697) among cancer survivors. The core symptoms, network structure, and global strength were invariant between time since diagnoses (< 2 years vs. ≥ 2 years) or between numbers of cancers (1 vs. ≥ 2), yet varied between the comorbidity group and non-comorbidity group (≥ 1 vs. 0).

CONCLUSIONS

Fatigue would be a potential target for alleviating other symptoms through a negative feedback loop of other related symptoms of cancer survivors. In particular, cancer survivors with other chronic diseases should be the focus of attention and strengthen targeted intervention.

Chemotherapy-related symptom networks in distinct subgroups of Chinese patients with gastric cancer

Objective

This study aims to identify distinct subgroups among gastric cancer patients undergoing chemotherapy (CTX), delineate associated symptom networks, and ascertain the clinical and sociodemographic variables contributing to diverse symptom patterns.

Methods

Conducted in eastern China, our investigation involved gastric cancer patients receiving CTX. We gathered data using the M.D. Anderson Symptom Inventory Gastrointestinal Cancer Module along with clinical and sociodemographic variables. Subgroups were discerned based on symptom severity through latent profile analysis, and subsequent comparisons were made regarding the symptom networks in different subgroups.

Results

The analysis encompassed 677 eligible gastric cancer patients, revealing three profiles: "Profile 1: low class" (n = 354, 52.3%), "Profile 2: moderate class" (n = 222, 32.8%), and "Profile 3: all high class" (n = 101, 14.9%). Nausea-vomiting exhibited robust associations in the symptom networks of all subgroups, whereas sadness-distress, and taste change-lack of appetite were notably linked with Profile 1 and Profile 2. Distress emerged as a core symptom in Profile 1, lack of appetite dominated the symptom network in Profile 2, and fatigue attained the highest strength in Profile 3. Distinct symptom profiles were influenced by variables such as education level, CTX combined with surgical or herbal treatment, psychological resilience, and social support.

Conclusions

Patients within different subgroups manifest individualized patterns of symptom profiles. Analyzing demographics, disease characteristics, and psychosocial information among diverse subgroups facilitates healthcare providers in devising more personalized and targeted symptom management strategies, thereby alleviating the symptom burden on patients.

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.

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.

Patient-Reported Outcomes Measurement Information System Pediatric Symptom Profiles of Children With Cancer in China: A Latent Profile Analysis

BACKGROUND

Unpleasant symptoms are common in children with cancer. However, research identifying subgroups of children with cancer who experience similar levels of self-reported symptoms in China is limited.

OBJECTIVES

This study aimed to classify the symptom profiles of children with cancer and detect the possible predictors of the profiles and their effect on children's quality of life (QoL).

METHODS

A total of 272 children aged 8 to 17 years completed the Chinese version of the Pediatric Patient-Reported Outcomes Measurement Information System short form measures, the Pediatric QOL Inventory general core and cancer modules. Latent profile analysis was used to identify symptom profiles, and ordinal logistic regression and analysis of variance were used to examine predictors of symptom profile membership and profile differences on QoL.

RESULTS

The best fit was a 3-profile model: low, moderate, and severe symptom distress. Children who had been inpatients in the past 7 days and were currently under treatment are more likely to have severe symptoms. Participants in the low symptom distress profile reported significantly greater QoL than those in the other profiles.

CONCLUSIONS

Children with cancer are heterogeneous in their experience of symptoms. Children's characteristics, such as inpatient history and treatment status, are predictors of profiles; different symptom profiles are associated with QoL.

IMPLICATIONS FOR PRACTICE

This study identified distinct groups of patients who predictably experience higher symptoms and their predictors, which could help to place children within a profile and perhaps allow nurses to provide targeted supportive care to match children's specific symptom profile.

Symptom Clusters in Survivorship and Their Impact on Ability to Work among Cancer Survivors

BACKGROUND

Cancer survivors often experience a range of symptoms after treatment which can impact their quality of life. Symptoms may cluster or co-occur. We aimed to investigate how symptoms and symptom clusters impact the ability to work among cancer survivors.

METHODS

We used symptom severity data and ability to work data routinely collected from cancer survivors attending a survivorship clinic after primary treatment with curative intent. We defined symptom clusters using single linkage and a threshold on the rescaled distances of <10. We then conducted a logistic regression to examine how symptoms and symptom clusters were related to the ability to work.

RESULTS

We analysed data from 561 cancer survivors, mean age 58 years and 1.5 years post diagnosis, with mixed diagnoses including breast (40.5%), colorectal (32.3%), and haematological cancers (15.3%). Limitations to work ability were reported by 34.9% of participants. Survivors experiencing pain, emotional, and cognitive symptom clusters were 14-17% more likely to report limitations in their ability to work. Older survivors and those with a higher stage disease were more likely to report limitations in their ability to work.

CONCLUSION

A better understanding and management of symptom severity and symptom clusters may help the sizable proportion of cancer survivors experiencing symptoms to participate in work after treatment.

Evaluation of the Effect of Self-Efficacy on Symptoms in Gastrointestinal Cancer Patients

Objective: The incidence of gastrointestinal cancer is increasing day by day and is among the highest 10 cancer types in the world. This study was conducted to evaluate the effects of self-efficacy of patients with gastrointestinal system cancer on symptom clusters. Methods: This cross-sectional study was conducted with 105 patients treated for gastrointestinal system cancer in a hospital located in the south of Turkey. In the study, patients over 18 years of age without hearing or speech impairment were included. To determine symptom clusters, Latent Profile Analysis and comparison of self-efficacy scale items by symptom clusters were performed with Chi-square, ANOVA, and Kruskal Wallis test. Results: The mean age of the patients was 58.83 ± 13.1 years; of the patients, 37.1% had colon ca, 21.9% had rectum ca. The patients had higher mean scores of fatigue, pain, feeling distressed, feeling sad, dry mouth, sleep disturbance, loss of appetite and nausea in the last week. The patients had higher mean scores of fatigue, pain, feeling distressed, feeling sad, dry mouth, sleep disturbance, loss of appetite and nausea in the last week. Three symptom clusters were determined by latent profile analysis; high, moderate, mild. It was determined that the level of self-efficacy was high in the symptom cluster which is low symptom severity and number of symptoms (p < .05). Conclusion: The number and the severity of symptoms are lower in patients with high self-efficacy perceptions.

Virologic Nonsuppression Among Patients With HIV Newly Diagnosed With Cancer at Uganda Cancer Institute: A Cross-Sectional Study

PURPOSE

AIDS-related mortality declined markedly since the introduction of antiretroviral therapy (ART); however, cancer mortality in Africa was higher than its incidence in 2020. People living with HIV (PLWHIV) are at an increased risk of malignancy and death from malignancy compared with the general population. In Uganda, AIDS-defining malignancies (ADMs), including cervical cancer, Kaposi sarcoma, and non-Hodgkin lymphoma, are among the commonest malignancies. Virologic nonsuppression has been identified as an important predictor of mortality among PLWHIV diagnosed with cancer. This study aimed to determine the prevalence and to identify factors associated with virologic nonsuppression among PLWHIV newly diagnosed with cancer.

METHODS

This was a cross-sectional study that was carried out between December 2018 and April 2019 at the Uganda Cancer Institute. PLWHIV who had been on ART for at least 6 months and were newly diagnosed with cancer were enrolled.

RESULTS

A total of 167 participants were enrolled. Cervical cancer was the commonest ADM (n = 45; 50.6%) of all ADMs, while esophageal and breast cancers were the commonest non-ADMs, accounting for 17.5% (n = 14) each of all non-ADMs. The prevalence of virologic nonsuppression was 15%. Having Kaposi sarcoma (odds ratio [OR], 8.15; P = .003), being poorly adherent to ART (OR, 4.1; P = .045), and being on second-line ART (OR, 5.68; P = .011) were associated with virologic nonsuppression.

CONCLUSION

The prevalence of virologic nonsuppression is high among patients with HIV newly diagnosed with cancer. These findings emphasize the need for strengthening of adherence strategies, optimizing ART regimens, and prioritization of viral load testing among PLWHIV with newly diagnosed malignancy.

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

PURPOSE

To investigate symptom severity, symptom cluster trajectories and sentinel symptoms during chemotherapy cycle 1 in patients with lung cancer.

METHODS

Patients with lung cancer were recruited to complete the MD Anderson Symptom Inventory (MDASI) and First Appearance of Symptoms Time Sheet daily during the first week of chemotherapy cycle 1. Latent class growth analysis was performed to examine symptom cluster trajectories. The Apriori algorithm combined with the time of the first appearance of symptoms after chemotherapy was used to determine the sentinel symptoms of each symptom cluster.

RESULTS

A total of 175 lung cancer patients participated in the study. Five symptom clusters were identified: class 1 (difficulty remembering-numbness-hemoptysis-weight loss), class 2 (cough-expectoration-chest tightness-shortness of breath), class 3 (nausea-sleep disturbance-drowsiness-constipation), class 4 (pain-distress-dry mouth-sadness-vomiting), class 5 (fatigue-lack of appetite). Sentinel symptoms were found to be cough (class 2) and fatigue (class 5), while none were found for other symptom clusters.

CONCLUSION

The trajectories of five symptom clusters were observed during the first week of chemotherapy cycle 1 and the sentinel symptoms of each cluster were explored. The study has important significance for the effective management of symptoms and the quality of nursing care for patients. At the same time, alleviating sentinel symptoms may reduce the severity of the whole symptom cluster, reducing medical resources and improving quality of life for lung cancer patients.

Experience of living with symptom clusters in postoperative pancreatic cancer patients

OBJECTIVE

The purpose of this study was to describe symptom clusters (SCs), and symptom experiences in early postoperative patients with pancreatic cancer who are recovering at home.

METHODS

From October 2021 and April 2022,15 patients following pancreatic cancer surgery were recruited from a tertiary hospital in Jiangsu Province by maximum variation sampling. Semi-structured interviews were performed to collect data and thematic analysis was conducted to analyze the data.

RESULTS

Three themes were extracted from the data. The first theme "difference in symptom perception and cognition" illustrated factors such as patient knowledge, expected recovery status, and risk perception could influence patient symptom experience. Most patients actually reported fewer and less severe symptoms than previous studies. The second theme "the results of symptom cluster" demonstrated anorexia-distress SC, bowel-digestive related SC and sleep disturbance related SC, and anorexia-distress SC should be considered as the priority SC given its multidimensional significance for patients. The last theme described the patient's positive attitudes, behaviours and barriers to coping with symptoms, namely "symptom self-management experience".

CONCLUSION

There are differences in the perception and interpretation of SCs in postoperative pancreatic cancer patients. Understanding the meaning of individual differences in the experience of symptoms can assist patients in the management of SCs. Medical staff should combine patient self-management strategies and evidence-based data to provide appropriate support at different stages to improve patient symptom management and quality of life.

The Role of Symptom Clusters in Triage of COVID-19 Patients

BACKGROUND AND OBJECTIVE

COVID-19 manifests with a broad range of symptoms. This study investigates whether clusters of respiratory, gastrointestinal, or neurological symptoms can be used to diagnose COVID-19.

METHODS

We surveyed symptoms of 483 subjects who had completed COVID-19 laboratory tests in the last 30 days. The survey collected data on demographic characteristics, self-reported symptoms for different types of infections within 14 days of onset of illness, and self-reported COVID-19 test results. Robust LASSO regression was used to create 3 nested models. In all 3 models, the response variable was the COVID-19 test result. In the first model, referred to as the "main effect model," the independent variables were demographic characteristics, history of chronic symptoms, and current symptoms. The second model, referred to as the "hierarchical clustering model," added clusters of variables to the list of independent variables. These clusters were established through hierarchical clustering. The third model, referred to as the "interaction-terms model," also added clusters of variables to the list of independent variables; this time clusters were established through pairwise and triple-way interaction terms. Models were constructed on a randomly selected 80% of the data and accuracy was cross-validated on the remaining 20% of the data. The process was bootstrapped 30 times. Accuracy of the 3 models was measured using the average of the cross-validated area under the receiver operating characteristic curves (AUROCs).

RESULTS

In 30 bootstrap samples, the main effect model had an AUROC of 0.78. The hierarchical clustering model had an AUROC of 0.80. The interaction-terms model had an AUROC of 0.81. Both the hierarchical cluster model and the interaction model were significantly different from the main effect model (α = .04). Patients with different races/ethnicities, genders, and ages presented with different symptom clusters.

CONCLUSIONS

Using clusters of symptoms, it is possible to more accurately diagnose COVID-19 among symptomatic patients.

Cancer-related fatigue: Identification of hallmarks to enable refined treatment approaches

OBJECTIVE

Recommendations for fatigue management are commonly given in an undifferentiated manner without further evaluation of patient's specific symptomatology. Thus, we aimed to identify hallmarks of potential fatigue subgroups which might guide more refined treatment.

METHODS

The FiX study assessed fatigue with the EORTC QLQ-FA12 in patients around 2 years after cancer diagnosis (T0) including 15 different entities. After 2 years, a follow-up survey (T1) was conducted. The analyses comprised all patients with prevalent fatigue at T0 (N = 1023). Hierarchical cluster analysis was performed using the Ward method and including the dichotomized factors emotional distress, pain, insomnia, and obesity. Emotional distress, that is, depressive symptoms and anxiety, was assessed by the PHQ-4. Pain and insomnia were based on the according symptom scores of the EORTC QLQ-C30. Analysis of covariance was conducted to investigate the association of the fatigue clusters at T0 with subsequent fatigue at T1.

RESULTS

Four hierarchical clusters were identified. The first cluster comprised patients with moderate-to-severe distress. The remaining fatigue cases were differentiated by obesity and then by pain. Fatigue cases without any of these three symptoms formed the last cluster. Physical, emotional and cognitive fatigue were highest in the distress cluster. Additionally, this cluster was associated with higher physical, emotional and cognitive fatigue at T1 compared to the other clusters.

CONCLUSIONS

Fatigue in conjunction with emotional distress had worse impact, persisted longer, and may require other treatment approaches than fatigue in patients without emotional distress. Obesity and pain may be further distinguishing hallmarks for refined fatigue management.

Palliative Care Early in the Care Continuum among Patients with Serious Respiratory Illness: An Official ATS/AAHPM/HPNA/SWHPN Policy Statement

Background: Patients with serious respiratory illness and their caregivers suffer considerable burdens, and palliative care is a fundamental right for anyone who needs it. However, the overwhelming majority of patients do not receive timely palliative care before the end of life, despite robust evidence for improved outcomes. Goals: This policy statement by the American Thoracic Society (ATS) and partnering societies advocates for improved integration of high-quality palliative care early in the care continuum for patients with serious respiratory illness and their caregivers and provides clinicians and policymakers with a framework to accomplish this. Methods: An international and interprofessional expert committee, including patients and caregivers, achieved consensus across a diverse working group representing pulmonary-critical care, palliative care, bioethics, health law and policy, geriatrics, nursing, physiotherapy, social work, pharmacy, patient advocacy, psychology, and sociology. Results: The committee developed fundamental values, principles, and policy recommendations for integrating palliative care in serious respiratory illness care across seven domains: 1) delivery models, 2) comprehensive symptom assessment and management, 3) advance care planning and goals of care discussions, 4) caregiver support, 5) health disparities, 6) mass casualty events and emergency preparedness, and 7) research priorities. The recommendations encourage timely integration of palliative care, promote innovative primary and secondary or specialist palliative care delivery models, and advocate for research and policy initiatives to improve the availability and quality of palliative care for patients and their caregivers. Conclusions: This multisociety policy statement establishes a framework for early palliative care in serious respiratory illness and provides guidance for pulmonary-critical care clinicians and policymakers for its proactive integration.

Distinguishing symptom patterns in adults newly diagnosed with cancer: a latent class analysis

CONTEXT

Socio-demographic differences, including place of residence, socio-economic status, ethnicity, and gender, have been associated with various inequities in cancer care outcomes.

OBJECTIVES

The aims were to distinguish subgroups of patients with different symptom patterns at the time of the initial oncology visit and determine which clinical and socio-demographic variables are associated the different symptom patterns.

METHOD

Responses to the Edmonton Symptom Assessment Scale- revised and clinical and socio-demographic variables were obtained via the Ontario Cancer Registry and linked health data files. Latent class analyses were conducted to identify and compare the subgroups.

RESULTS

The cohort (n = 216,110) with a mean age of 64.5 years consisted of 54.1% women. The analyses identified six latent classes (proportions ranging from 0.09 to 0.31) with distinct symptom patterns, including: 1) many severe symptoms, 2) many less severe symptoms, 3) predominantly mild symptoms, 4) severe psychosocial symptoms, 5) severe somatic symptoms, 6) few symptoms. The subgroups were associated not only with clinical differences (diagnoses and functional status), but also with various socio-demographic (age, sex) and community characteristics (neighborhood income, proportion of foreign born, rurality).

CONCLUSION

The results indicated that there were substantial differences in symptom patterns at the time of the initial oncology visit, which were associated with both clinical diagnoses and socio-demographic differences. These results point to the importance of taking the social situation of patients into account, and not just diagnosis, to better understand differences in symptom patterns of people living with cancer.

Cancer-Related Fatigue – Clinical Evaluation Scales and Interventions: A Systematic Review

Background:

Cancer-related fatigue (CRF) is one of the most frequent and prevalent symptoms expressed by cancer patients and cancer survivors. It is a multifactorial phenomenon that causes a direct detrimental impact on quality of life.

Objectives:

This systematic review aims to identify different clinical evaluation scales and interventions available for fatigue associated with cancer.

Materials and Methods:

A methodology of the systematic literature review was carried out. Two separate databases PubMed and Google Scholar searches were performed using different MeSH terms.

Results:

A total of 2611 research articles were screened and identified 10 unidimensional scales (four with one item scales and six with numerous item scales) and 13 multidimensional scales which are available for the screening and clinical evaluation of fatigue. Reviews have also revealed non-pharmacological interventions such as exercise, complementary therapies, nutritional and psychoeducational interventions, sleep therapy, energy therapy, bright white light, restorative therapies upcoming anthroposophical medicine, and various pharmacological agents effective in managing CRF.

Conclusion:

Clinical evaluation of fatigue and its management is crucial for improving the quality of life. Yet, more rigorous research studies with higher statistical power need to be conducted on these interventions to generate adequate evidences for managing the CRF.

THALIS: Human-Machine Analysis of Longitudinal Symptoms in Cancer Therapy

Although cancer patients survive years after oncologic therapy, they are plagued with long-lasting or permanent residual symptoms, whose severity, rate of development, and resolution after treatment vary largely between survivors. The analysis and interpretation of symptoms is complicated by their partial co-occurrence, variability across populations and across time, and, in the case of cancers that use radiotherapy, by further symptom dependency on the tumor location and prescribed treatment. We describe THALIS, an environment for visual analysis and knowledge discovery from cancer therapy symptom data, developed in close collaboration with oncology experts. Our approach leverages unsupervised machine learning methodology over cohorts of patients, and, in conjunction with custom visual encodings and interactions, provides context for new patients based on patients with similar diagnostic features and symptom evolution. We evaluate this approach on data collected from a cohort of head and neck cancer patients. Feedback from our clinician collaborators indicates that THALIS supports knowledge discovery beyond the limits of machines or humans alone, and that it serves as a valuable tool in both the clinic and symptom research.

Sleep Quality and Associated Factors Among Adult Cancer Patients Under Treatment at Oncology Units in Amhara Region, Ethiopia

INTRODUCTION

Poor sleep quality, a common, under-diagnosed, and under-treated problem in cancer patients, has negative physical and psychological consequences, but its prevalence and associated factors are not well studied in Ethiopia. Thus, the present study aimed to assess the prevalence of sleep quality and its associated factors among adult cancer patients receiving treatment at oncology units in Amhara region, Ethiopia.

METHODS AND MATERIALS

An institution-based cross-sectional study was conducted among adult patients with cancer under treatment at the oncology units in the Amhara region from April 12 to May 12/2021. A systematic random sampling technique was used to select 423 samples. Data were collected using a structured Interviewer-administered questionnaire. Sleep quality and depression were assessed by the Pittsburgh Sleep Quality Index and depression subscale of Hospital Anxiety and Depression Scale, respectively. Bivariable and multivariable logistic regression analyses were computed, considering p < 0.25 to select candidate variables for multivariable analysis and p < 0.05 to be statistically significant in the final model.

RESULTS

A total of 410 cancer patients participated in this study. The mean of the participant's age was 44.2 (range: 20-77) years. More than half (52.7%) of participants received chemotherapy and the remaining were treated with a combination of treatments. Two-hundred ninety-three (71.5%) of participants had poor sleep quality and 28.5% had good sleep quality. The factors found to be significantly associated with poor sleep quality were advanced age [AOR = 1.037, 95% CI: (1.012-1.062)]; having depressive symptoms [AOR = 2.862, 95% CI: (1.133, 7.228)]; having distant metastasis cancer [AOR = 3.758, 95% CI: (1.585, 8.909)]; and increased severity of pain [AOR = 1.331, 95% CI: (1.106, 1.601)].

CONCLUSION

The study found a high prevalence of poor sleep quality among cancer patients. Early screening and management of sleep problems are crucial in patients with cancer.

Association of Genetic Polymorphisms with Psychological Symptoms in Cancer: A Systematic Review

Cancer patients suffer from a repertoire of symptoms, including such psychological and psychiatric symptoms as anxiety, depression, and posttraumatic stress. Exploration of genetic factors that modify the risk and severity of these symptoms may facilitate the development of personalised care plans for managing these symptoms. This review aims to provide an overview on the variations in genes that may contribute to the occurrence and severity of anxiety, depression, and posttraumatic stress disorder (PTSD) among cancer patients. Literature search was performed in nine English and Chinese electronic databases, and extracted data are presented narratively. The reporting quality of the included studies was assessed using selected items of The STrengthening the REporting of Genetic Association (STREGA) checklist. Twenty-nine studies were included in the review. Most studies involved breast cancer patients, while patients of other cancer types appeared to be understudied. A number of studies reported the association between genes involved in inflammatory pathways and depression and anxiety. Other genes found to show associations with anxiety, depression, and PTSD among cancer patients are those involved in neurotrophic signalling, serotonergic signalling, regulation of stress response, antioxidation, dopamine catabolism and cellular apoptosis, despite some inconsistencies in findings between studies. Our review highlighted a need for further research for enhancing our knowledge on the association between genetic variations and anxiety, depression, and PTSD of patients of various cancer types. Future studies examining such associations in patients of various cancers should utilise standardised instruments for outcome assessments and stratify the patients based on their age for analysis.

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.

Sleeping-related distress in a palliative care population: A national, prospective, consecutive cohort

BACKGROUND

Sleep, a multi-dimensional experience, is essential for optimal physical and mental wellbeing. Poor sleep is associated with worse wellbeing but data are scarce from multi-site studies on sleeping-related distress in palliative care populations.

AIM

To evaluate patient-reported distress related to sleep and explore key demographic and symptom distress related to pain, breathing or fatigue.

DESIGN

Australian national, consecutive cohort study with prospectively collected point-of-care data using symptoms from the Symptom Assessment Scale (SAS).

SETTING/PARTICIPANTS

People (n = 118,117; 475,298 phases of care) who died while being seen by specialist palliative care services (n = 152) 2013-2019. Settings: inpatient (direct care, consultative); community (outpatient clinics, home, residential aged care).

RESULTS

Moderate/severe levels of sleeping-related distress were reported in 11.9% of assessments, more frequently by males (12.7% vs 10.9% females); people aged <50 years (16.2% vs 11.5%); and people with cancer (12.3% vs 10.0% for other diagnoses). Sleeping-related distress peaked with mid-range Australia-modified Karnofsky Performance Status scores (40-60).Strong associations existed between pain-, breathing- and fatigue-related distress in people who identified moderate/severe sleeping-related distress, adjusted for age, sex and functional status. Those reporting moderate/severe sleeping-related distress were also more likely to experience severe pain-related distress (adjusted odds ratios [OR] 6.6; 95% confidence interval (CI) 6.3, 6.9); breathing-related distress (OR 6.2; 95% CI 5.8, 6.6); and fatigue-related distress (OR 10.4; 95% CI 9.99-10.8).

CONCLUSIONS

This large, representative study of palliative care patients shows high prevalence of sleeping-related distress, with strong associations shown to distress from other symptoms including pain, breathlessness and fatigue.

Identifying Symptom Clusters Through Association Rule Mining

Cancer patients experience many symptoms throughout their cancer treatment and sometimes suffer from lasting effects post-treatment. Patient-Reported Outcome (PRO) surveys provide a means for monitoring the patient's symptoms during and after treatment. Symptom cluster (SC) research seeks to understand these symptoms and their relationships to define new treatment and disease management methods to improve patient's quality of life. This paper introduces association rule mining (ARM) as a novel alternative for identifying symptom clusters. We compare the results to prior research and find that while some of the SCs are similar, ARM uncovers more nuanced relationships between symptoms such as anchor symptoms that serve as connections between interference and cancer-specific symptoms.

Symptom clusters among cancer survivors: what can machine learning techniques tell us?

PURPOSE

Knowledge regarding symptom clusters may inform targeted interventions. The current study investigated symptom clusters among cancer survivors, using machine learning techniques on a large data set.

METHODS

Data consisted of self-reports of cancer survivors who used a fully automated online application 'Oncokompas' that supports them in their self-management. This is done by 1) monitoring their symptoms through patient reported outcome measures (PROMs); and 2) providing a personalized overview of supportive care options tailored to their scores, aiming to reduce symptom burden and improve health-related quality of life. In the present study, data on 26 generic symptoms (physical and psychosocial) were used. Results of the PROM of each symptom are presented to the user as a no well-being risk, moderate well-being risk, or high well-being risk score. Data of 1032 cancer survivors were analysed using Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) on high risk scores and moderate-to-high risk scores separately.

RESULTS

When analyzing the high risk scores, seven clusters were extracted: one main cluster which contained most frequently occurring physical and psychosocial symptoms, and six subclusters with different combinations of these symptoms. When analyzing moderate-to-high risk scores, three clusters were extracted: two main clusters were identified, which separated physical symptoms (and their consequences) and psycho-social symptoms, and one subcluster with only body weight issues.

CONCLUSION

There appears to be an inherent difference on the co-occurrence of symptoms dependent on symptom severity. Among survivors with high risk scores, the data showed a clustering of more connections between physical and psycho-social symptoms in separate subclusters. Among survivors with moderate-to-high risk scores, we observed less connections in the clustering between physical and psycho-social symptoms.

Symptom Clusters Change Over Time in Patients With Lung Cancer During Perichemotherapy

BACKGROUND

Lung cancer has become the leading cause of cancer-related deaths in China, and patients often experience multiple symptoms and substantial discomfort. Understanding and managing concurrent symptoms of patients with lung cancer are crucial during perichemotherapy.

OBJECTIVE

To determine the types and components of symptom clusters according to the severity dimension and to understand how they change over time during perichemotherapy in a homogeneous population of patients with lung cancer.

METHODS

Patients were recruited using convenience sampling. The Chinese version of the MD Anderson Symptom Inventory and the revised lung cancer module were used to measure multiple symptoms at the following 3 separate points: 2 weeks before chemotherapy (T1), chemotherapy cycle 1 (T2), and chemotherapy cycle 4 (T3). Symptom clusters were identified by exploratory factor analysis.

RESULTS

A total of 144 patients with non-small cell lung cancer participated in the study. Six symptom clusters were identified at the 3 time points. Among the 6 symptom clusters, 3 symptom clusters remained stable at all time points, and differences were found in symptom clusters before and after chemotherapy.

CONCLUSIONS

Symptom clusters can change during perichemotherapy, showing some stability and differences over time.

IMPLICATIONS FOR PRACTICE

An improved understanding of symptom cluster trajectories in patients with lung cancer may facilitate effective assessment, prevention, and management of multiple concurrent symptoms. These findings will help clinicians to develop predictive interventions and reduce the symptom burden of patients undergoing chemotherapy.

Chinese Medicine Syndromes and Stages of Early Breast Cancer: Hierarchical Cluster Analysis and Implication for Clinical Practice

Background: Chinese medicine (CM) has been widely used for women's health, including those with early breast cancer. Contemporary literature varies in descriptions of the CM syndromes that are critical for determining CM treatment options for breast cancer patients. However, the corresponding syndromes have not been standardized to align with the conventional medicine treatment stages. This review aimed to address this knowledge gap to enhance the quality and consistency of CM interventions for early breast cancer patients. Methods: In total, eight Chinese and English language databases were searched, and textbooks and clinical care documents were gathered. Sources were classified according to five treatment stages: preoperative, postoperative, chemotherapy, radiation therapy, and endocrine therapy. Descriptive statistics were used to examine the syndromes, and hierarchical cluster analysis was conducted to investigate clusters of signs and symptoms. Results: The CM syndrome of dual deficiency of qi and Blood was one of the most common syndromes across all treatment stages, whereas lack of strength and lassitude were the most common clinical presentations throughout all stages, except the preoperative stage. Cluster analyses identify three or four syndromes in each treatment stage. Cluster results for the preoperative stage were: Blood stasis, Liver depression and qi stagnation, and Kidney yin deficiency. Dual deficiency of qi and Blood existed at different stages except for the preoperative stage. In the postoperative stage and chemotherapy stages, some symptoms were categorized into clusters that related to the Spleen and Stomach. Syndromes such as yin deficiency with fire toxin and yin deficiency with fluid depletion were unique to the radiation therapy stage. Clusters for endocrine therapy stage included the dual deficiency of Spleen and Kidney, Liver depression and qi stagnation, and Kidney yin deficiency. Conclusions: Systematic review of the contemporary literature for early breast cancer revealed that the most frequently seen CM syndromes and cluster results have some similarities but some important distinctions. Clinical data are needed to confirm whether the syndromes described in contemporary literature reflect those seen in women with early breast cancer.

Characteristics of Cancer Symptom Clusters Reported through a Patient-Centered Symptom Cluster Assessment

In the scope of symptom cluster research, few investigators have obtained patients' perceptions of their symptom clusters, even though this information is central to designing effective interventions. In this cross-sectional study, 38 adults with cancer completed measures of demographics, health outcomes (functional status, well-being, quality of life) and a symptom cluster assessment that captured symptom occurrence, severity, distress, clustering, a priority cluster, causal attributions, duration, directional relationships, and cluster interference with daily life. Participants described 72 distinct symptom clusters. Symptoms were most frequently attributed to the cancer diagnosis. Participants' priority symptom cluster typically included two symptoms of continuous duration and one intermittent symptom. Temporal order and direction of symptom relationships varied, with 75 different relationships described among symptom pairs. Greater symptom cluster burden and interference were related to poorer health outcomes. This patient-centered view of symptom clusters revealed substantial variability in symptom cluster characteristics with important implications for symptom management.

Symptom clusters in cancer patients: An Italian survey to validate and describe unwarranted clinical variation, inequality in access to healthcare, knowledge, and risk of malpractice

Background and aims:

The perceptions of professionals involved in cancer care regarding the importance of their symptoms-specific knowledge, unwarranted clinical variation (UCV), and inequalities in access to healthcare are still underdescribed. This study aims to confirm the construct validity of a previously initially developed questionnaire and describe nurses’ perceptions about the relevance of their knowledge referred to cancer symptoms management, the UCV, the inequalities in access to healthcare, and malpractice risk.

Method:

A cross-sectional pan-national study was conducted using a convenience sample, collecting data through a previously initially validated questionnaire. Construct validity was corroborated through confirmatory factor analysis, and descriptive statistics were employed for summarizing the questionnaire’s scores. The scores between the nurses working in accredited cancer centers and nurses employed in general hospitals were inferentially compared.

Results:

The sample comprised 810 nurses, 480 were nurses working in accredited cancer centers, and 330 were nurses working in general hospitals. The questionnaire showed adequate construct validity and reliability. Nurses perceived the cluster of psychosocial symptoms with a greater risk of UCV and inequalities in access to cancer services than the cluster of physical symptoms.

Discussion and conclusions:

A paradigm shift aimed at integrating psychosocial cancer symptoms in the care paths emerged as pivotal for improving cancer care in Italy.

The Influence of Multiple Chronic Conditions on Symptom Clusters in People With Solid Tumor Cancers

BACKGROUND

People with cancer who also have multiple chronic conditions (MCCs) experience co-occurring symptoms known as symptom clusters.

OBJECTIVE

To describe MCC and symptom clusters in people with cancer and to evaluate the relationships between MCCs and symptom severity, symptom interference with daily life, and quality of life (QoL).

METHODS

Weekly over a 3-week chemotherapy cycle, 182 adults with solid tumor cancer receiving chemotherapy completed measures of symptom severity, symptom interference with daily life, and QoL. Medical records reviewed to count number of MCCs in addition to cancer. Exploratory factor analysis was performed to identify symptom clusters. The relationships between the number of MCCs and the outcomes (symptom severity and symptom interference with daily life and QoL) at each time point were examined using the χ2 test. Longitudinal changes in outcomes were examined graphically.

RESULTS

The number of MCCs ranged from 0 to 9, but most participants (62.1%) had 2 or fewer MCCs. Obesity was the most prevalent chronic condition. Four symptom clusters were identified: nutrition, neurocognitive, abdominal discomfort, and respiratory clusters. At each time point, no significant differences were found for MCCs and any outcome. However, symptom severity in all the symptom clusters, symptom interference with daily life, and QoL demonstrated a worsening in the week following chemotherapy.

CONCLUSION

A majority of our sample had 2 or fewer MCCs, and MCCs did contribute to patient outcomes. Rather, timing of chemotherapy cycle had the greatest influence of patient outcomes.

IMPLICATIONS FOR PRACTICE

Additional support on day 7 of chemotherapy treatment is needed for people with MCCs.

Telomere lengths in women treated for breast cancer show associations with chemotherapy, pain symptoms, and cognitive domain measures: a longitudinal study

Background

Survival rates for breast cancer (BC) have improved, but quality of life post-diagnosis/treatment can be adversely affected, with survivors reporting a constellation of psychoneurological symptoms (PNS) including stress, anxiety, depression, pain, fatigue, sleep disturbance, and cognitive dysfunction.

Methods

To assess a potential relationship between telomere length (TL) and the development/persistence of PNS, we longitudinally studied 70 women (ages 23–71) with early stage BC (I-IIIA) at 5 time-points: prior to treatment (baseline), the mid-point of their chemotherapy cycle, 6 months, 1 year, and 2 years following the initiation of chemotherapy.

Measures quantified included assessments of each of the PNS noted above and TL [using both a multiplex qPCR assay and a chromosome-specific fluorescence in situ hybridization (FISH) assay].

Results

Variables associated with qPCR mean TLs were age (p = 0.004) and race (T/S ratios higher in Blacks than Whites; p = 0.019). Significant differences (mostly decreases) in chromosome-specific TLs were identified for 32 of the 46 chromosomal arms at the mid-chemo time-point (p = 0.004 to 0.049). Unexpectedly, the sequential administration of doxorubicin [Adriamycin], cyclophosphamide [Cytoxan], and docetaxel [Taxotere] (TAC regimen) was consistently associated with higher TLs, when compared to TLs in women receiving a docetaxel [Taxotere], Carboplatin [Paraplatin], and trastuzumab [Herceptin] [TCH] chemotherapy regimen [association was shown with both the qPCR and FISH assays (p = 0.036)]. Of the PNS, pain was significantly negatively associated with TL (higher pain; shorter telomeres) for a subset of chromosomal arms (5q, 8p, 13p, 20p, 22p, Xp, Xq) (p = 0.014–0.047). Chromosomal TLs were also associated with 7 of the 8 cognitive domains evaluated, with the strongest relationship being noted for chromosome 17 and the visual memory domain (shorter telomeres; lower scores).

Conclusions

We showed that race and age were significantly associated with telomere length in women treated for early stage BC and that acquired telomere alterations differed based on the woman’s treatment regimen. Our study also demonstrated that pain and cognitive domain measures were significantly related to telomere values in this study cohort. Expanding upon the knowledge gained from this longitudinal study could provide insight about the biological cascade of events that contribute to PNS related to BC and/or its treatment.

Supplementary information

The online version contains supplementary material available at 10.1186/s13058-020-01368-6.

Symptom Profiles of Latina Breast Cancer Survivors: A Latent Class Analysis

BACKGROUND

Symptom research among Latinas with breast cancer is limited-especially as it relates to multiple co-occurring symptoms.

OBJECTIVE

The aim of the study was to identify subgroups (latent classes) of Latinas who have distinct symptom profiles while receiving radiation, chemotherapy, and/or hormonal therapy for breast cancer.

METHODS

This secondary analysis included intake data from three randomized trials of supportive care psychosocial interventions for Latinas treated for breast cancer (n = 290). Prevalence of 12 symptoms-measured using the General Symptom Distress Scale-was entered into the latent class analysis to identify classes of women with different symptom profiles.

RESULTS

Most of the participants had Stage II or III disease, and 81% reported receiving chemotherapy. On average, women reported 4.2 (standard deviation [SD] = 3) symptoms with an overall symptom distress score of 6.4 (SD = 2.5) on a 1-10 scale, with 10 being most distressing. Latent class analysis resulted in three classes that were labeled based on symptoms with the highest prevalence. Class 1 (n = 192) was "Disrupted Sleep and Tired," Class 2 (n = 74) was "Tired," and Class 3 (n = 24) was "Pain, Disrupted Sleep, and Tired." Depression, anxiety, and difficulty concentrating had moderate prevalence in each of the three classes.

DISCUSSION

Beyond the core six symptoms (depression, anxiety, fatigue, pain, disrupted sleep, difficulty concentration), the classes differed in the prevalence of other burdensome symptoms (e.g., nausea, vomiting, constipation), which provide implications for treatment. Thus, it is important to assess for the full range of symptoms so that supportive care interventions can be tailored for the distinct symptom profiles of Latinas with breast cancer.

Religious/spiritual coping and spiritual distress in people with cancer

ABSTRACT Objective: To investigate the relation between the presence of spiritual distress and use of RSC and sociodemographic, clinical and religious/spiritual variables in people with cancer. Method: Cross-sectional study conducted in an association for support to people with cancer. The data obtained with the tools were analyzed using the Spearman‘s correlation coefficient and the Mann-Whitney Test. Results: 129 volunteers participated in the study, of which 57% showed moderate spiritual distress, 96% used medium and high positive religious/spiritual coping. Spiritual distress showed positive correlation with negative religious/spiritual coping (P<0.001) and inverse correlation with age (p 0.002). The use of positive religious coping was statistically significant in people who have religious practices (p 0.001). Conclusão: Spiritual distress is a phenomenon that is present in the lives of people with cancer and has significant relation with the use, in a negative manner, of religion/spirituality as a way of coping with the disease.

Feasibility of a Symptom Management Intervention for Honduran Adults Undergoing Chemotherapy

Evidence-based interventions often need to be adapted to maximize their implementation potential in low-to middle-income countries. A single-arm feasibility study was conducted to determine the feasibility and acceptability of a telephone-delivered, nurse-led, symptom management intervention for adults undergoing chemotherapy in Honduras. Over the course of 6 months, nurses engaged 25 patients undergoing chemotherapy in the intervention. Each participant received an average of 16.2 attempts to contact them for telephone sessions (SD = 8.0, range = 2-28). Collectively, the participants discussed 24 different types of symptoms. The most commonly discussed symptoms were pain (12%), nausea (7%), and constipation (5%). Qualitative and quantitative data were used to identify treatment manual modifications (i.e., adding content about different symptoms and addressing scheduling of treatment) and workplace modifications (i.e., dedicated nurse time and space) that are needed to optimize implementation of the intervention.

Relationship among symptom clusters, quality of life, and treatment-specific optimism in patients with cancer

PURPOSE

There is increasing evidence that disease and therapy-related symptoms frequently co-occur in so-called symptom clusters (SCs), which may significantly impair quality of life in patients with cancer. Although psychosocial resources may play pivotal roles in maintaining or improving quality of life, they have been neglected in SC research. Therefore, we aim to identify SCs and their relative impact on quality of life when psychosocial resources are accounted for.

METHODS

Patients with cancer (n = 304) undergoing chemotherapy or chemo-radiation therapy participated in a cross-sectional survey consisting of measures assessing symptoms, quality of life, resilience, treatment-specific optimism (TSO), and social support. Exploratory factor analyses and multiple regression analyses were used to identify SCs and significant explanatory variables of overall quality of life.

RESULTS

Fatigue-pain, anxiety-depression, cancer therapy-related toxicity, and nausea-vomiting clusters were identified. In our final model, the fatigue-pain cluster (β = - 0.41, p < 0.001), nausea-vomiting cluster (β = - 0.28, p < 0.001), TSO (β = 0.21, p < 0.001), and receiving chemo-radiation treatment (β = - 0.11, p = 0.03) accounted for 44% of variance in overall quality of life. However, the identified SCs explained quality of life in patients with varying levels of TSO to a different extent.

CONCLUSIONS

Our findings indicate that the TSO of patients may be a major factor to consider in managing SCs, because-depending on its level-different SCs and even clusters encompassing comparatively less distressing symptoms (i.e., cancer therapy-related toxicities) may strongly affect quality of life.

Misery Loves Company: Presenting Symptom Clusters to Urgent Care by Patients Receiving Antineoplastic Therapy

PURPOSE

The Centers for Medicare & Medicaid Services (CMS) identifies suboptimal management of treatment toxicities as a care gap and proposes the measurement of hospital performance on the basis of emergency department visits for 10 common symptoms. Current management strategies do not address symptom co-occurrence.

METHODS

We evaluated symptom co-occurrence in three patient cohorts that presented to a cancer hospital urgent care center in 2016. We examined both the CMS-identified symptoms and an expanded clinician-identified set defined as symptoms that could be safely managed in the outpatient setting if identified early and managed proactively. The cohorts included patients who presented with a CMS-defined symptom within 30 days of treatment, patients who presented within 30 days of treatment with a symptom from the expanded set, and patients who presented with a symptom from the expanded set within 30 days of treatment start. Symptom co-occurrence was measured by Jaccard index. A community detection algorithm was used to identify symptom clusters on the basis of a random walk process, and network visualizations were used to illustrate symptom dynamics.

RESULTS

There were 6,429 presentations in the CMS symptom-defined cohort. The network analysis identified two distinct symptom clusters centered around pain and fever. In the expanded symptom cohort, there were 5,731 visits and six symptom clusters centered around fever, emesis/nausea, fatigue, deep vein thrombosis, pain, and ascites. For patients who newly initiated treatment, there were 1,154 visits and four symptom clusters centered around fever, nausea/emesis, fatigue, and deep vein thrombosis.

CONCLUSION

Uncontrolled symptoms are associated with unplanned acute care. Recognition of the complexity of symptom co-occurrence can drive improved management strategies.

The effectiveness of non-pharmacological interventions in the management of symptom clusters in adult cancer patients: a systematic review protocol

REVIEW QUESTION/OBJECTIVE

To what extent are non-pharmacological interventions effective in reducing symptom clusters in terms of presence, frequency and severity, compared with standard care?More specifically, the objectives are to: CENTER CONDUCTING THE REVIEW:: The Hanoi Medical University Nursing Research Center for Evidence Based Health Care: a Collaborating Centre of the Joanna Briggs Institute; and Centre for Evidence-based Healthy Aging: an Affiliate Centre of the Joanna Briggs Institute, School of Nursing, Queensland University of Technology, Australia.

Patient-Reported Outcomes and Opioid Use by Outpatient Cancer Patients

The Memorial Sloan Kettering Pain Registry contains patient characteristics, treatments, and outcomes for a prospective cohort of 1,534 chronic pain cancer patients who were seen at outpatient pain service clinics. Average pain intensity (Brief Pain Inventory) was reported as mild by 24.6% of patients, moderate by 41.5%, and severe by 33.9%. The patient's report of average percent pain relief and health state (EuroQOL 5 dimensions) was inversely related to average pain intensity category, whereas measures of pain interference, number of worst pain locations, and physical and psychological distress were directly related to pain intensity category. Eighty-six percent of patients received an opioid at 1 or more clinic encounters. Regression analysis revealed that male sex or being younger (65 years of age or younger) was associated with a greater likelihood of an opioid ordered. Male sex nearly doubled the likelihood of a higher dose being ordered than female sex. Bivariate analysis found that patients receiving opioids reported significantly more pain relief than no-opioid patients. However, patients receiving opioids had higher pain interference scores, lower index of health state, and more physical distress than no-opioid patients Our results identify the need to consider opioid use and dosage when attempting to understand patient-reported outcomes (PROs) and factors affecting pain management.

PERSPECTIVE

This report describes the results of the analyses of PROs and patient-related electronic health record data collected under standard of care from cancer patients at outpatient pain management clinics of Anesthesiology and Palliative Care at the Memorial Sloan Kettering Cancer Center. Consideration of sex and age as predictors of opioid use is critical in attempting to understand PROs and their relationship to pain management.

Lung cancer–associated pulmonary hypertension: Role of microenvironmental inflammation based on tumor cell–immune cell cross-talk

Lung cancer–associated pulmonary hypertension is associated with microenvironmental inflammation caused by tumor cell–immune cell cross-talk.

End-of-life care in children with hematologic malignancies

Introduction

Hematologic malignancies (HM) represent the most common neoplasms in childhood. Despite improved overall survival rates, they are still a major contributor to cancer death in children.

Aims

To determine the proportion of children with HM in pediatric palliative care (PPC) and to identify the clinical characteristics and symptoms in comparison to children with extracranial solid tumors (non HM patients).

Patients and Methods

This study was conducted as a single-center retrospective cohort study of patients in the care of a large specialized PPC team.

Results

Fifteen HM and 50 non HM patients were included. Symptoms in which HM patients scored significantly higher than non HM patients were mucositis, difficulty moving, somnolence, fatigue, petechiae and paleness. Blood transfusions were more frequently administered to HM patients, but large external hemorrhage was not observed in any child. A large variety of drugs and appliances were needed by the patients, with morphine being the most frequently prescribed drug. During the study period, a much larger and over the years even increasing number of HM patients (not in the care of the PPC team) died in hospital with an (assumed) curative intent, with two thirds dying in the ICU.

Conclusions

Children with HM were referred to outpatient PPC with almost the full clinical picture of advanced leukemia. Noteworthy, the number of children with HM dying at home is decreasing in our center, instead a substantial proportion received high-intensity medical hospital care including novel anticancer therapies. These patients thus seem to be at an increased risk of dying in hospital as the right time to transfer them to palliative care is oftentimes missed.

Los grupos de síntomas en personas con cáncer: una revisión integrativa

Objetivo: explorar el estado actual de desarrollo investigativo del área temática de grupos de síntomas en adultos con cáncer. Método: revisión integrativa de producción científica generada entre 2001 y 2016. Se incluyeron 61 artículos por su aporte en la comprensión del área temática. Resultados: el estudio de los grupos de síntomas en personas con cáncer se consolida como un área temática novedosa, pertinente y necesaria para la investigación y práctica de enfermería en oncología, con tendencias y retos que incluyen: (1) El desarrollo de marcos conceptuales que aporten a la fundamentación, atributos y efectos (2) La determinación de métodos y formas de crearlos y clasificarlos (3) La generación de estudios con poblaciones específicas por tipos de cáncer y tratamiento y la consolidación de intervenciones de enfermería. Conclusiones: los pacientes con cáncer experimentan múltiples síntomas de forma simultánea durante las distintas fases de la enfermedad. Es incipiente el estudio de este fenómeno, los retos para la enfermería se centran en la generación de respuestas que alivien la carga de los grupos de síntomas y mejoren la calidad de vida de estos pacientes. Es necesario validar escalas de carga del síntoma y explorar los grupos de síntomas incluyendo variables clínicas ligadas a los tratamientos oncológicos.

Symptom Clusters Change Over Time in Women Receiving Adjuvant Chemotherapy for Breast Cancer

CONTEXT

Patients with breast cancer receiving chemotherapy (CTX) experience multiple concurrent symptoms, but little is known about how symptoms change during and after treatment. Knowledge of the identity and trajectory of symptom clusters (SCs) would enhance measurement and management.

OBJECTIVES

We aimed to identify SCs and their change over time from baseline to completion of breast cancer CTX.

METHODS

SCs were identified and assessed for change in 219 women from Nebraska at four times: baseline, during cycles #3 and #4 of CTX, and one month after finishing CTX. Ten symptoms were measured: two using the Hospital Anxiety and Depression Scale and eight using the Symptom Experience Scale. Exploratory factor analysis was conducted at each time point, then changes in SCs were evaluated at different times.

RESULTS

Two SCs were identified before and after initiating CTX: gastrointestinal and treatment-related. The number and type of symptoms in each cluster differed over time. Clusters were dynamic during CTX with changes in the number and type of symptoms. Only one treatment-related SC, which consisted of fatigue, pain, and sleep disturbance, was identified after CTX completion.

CONCLUSION

SCs during CTX appear to be dynamic, changing over time from before until after CTX completion. Repeated assessments of SCs reveal symptoms that are present and when patients are most burdened and in need of additional support.

Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations

An overview of proceedings, findings, and recommendations from the workshop on "Advancing Symptom Science Through Symptom Cluster Research" sponsored by the National Institute of Nursing Research (NINR) and the Office of Rare Diseases Research, National Center for Advancing Translational Sciences, is presented. This workshop engaged an expert panel in an evidenced-based discussion regarding the state of the science of symptom clusters in chronic conditions including cancer and other rare diseases. An interdisciplinary working group from the extramural research community representing nursing, medicine, oncology, psychology, and bioinformatics was convened at the National Institutes of Health. Based on expertise, members were divided into teams to address key areas: defining characteristics of symptom clusters, priority symptom clusters and underlying mechanisms, measurement issues, targeted interventions, and new analytic strategies. For each area, the evidence was synthesized, limitations and gaps identified, and recommendations for future research delineated. The majority of findings in each area were from studies of oncology patients. However, increasing evidence suggests that symptom clusters occur in patients with other chronic conditions (eg, pulmonary, cardiac, and end-stage renal disease). Nonetheless, symptom cluster research is extremely limited and scientists are just beginning to understand how to investigate symptom clusters by developing frameworks and new methods and approaches. With a focus on personalized care, an understanding of individual susceptibility to symptoms and whether a "driving" symptom exists that triggers other symptoms in the cluster is needed. Also, research aimed at identifying the mechanisms that underlie symptom clusters is essential to developing targeted interventions.

Symptom clusters in patients receiving haemodialysis: a systematic review of observational studies

AIMS AND OBJECTIVES

To systematically review the common composition and the analytical methods performed to derive symptom clusters in patients receiving haemodialysis, and to examine their common predictive and outcome variables.

BACKGROUND

Patients receiving haemodialysis may suffer from multiple and interactive symptoms simultaneously, which may impact their mortality, morbidity and quality of life. The composition of these symptom clusters varies depending on the different assessment tools, the variant evaluation timing points and the various statistical methodologies. A detailed review of existing studies is needed.

DESIGN

A systematic review of observational studies.

METHODS

Medline from 1950, CINAHL from 1960, Embase from 1980 and PsycINFO from 1967 as well as additional sources were searched. Content analysis was conducted to identify articles assessing the interrelationships of multiple symptoms.

RESULTS

Five studies were identified. Several symptom clusters were identified with five common groupings being uraemic cluster, neuromuscular cluster, skin cluster, gastrointestinal cluster and energy/fatigue cluster. Four studies performed the principal component analysis with varimax rotation to extract symptom clusters and one study used correlation analysis. Different symptom assessment tools were used and each involving different array of symptoms. The predictive and outcome variables of symptom clusters also varied considerably. No studies have examined the longitudinal course and patients' subjective experiences of symptom clusters.

CONCLUSIONS

Inconsistencies in the composition of symptom clusters across studies were identified due to inconsistencies in symptom assessment tools and statistical methodologies. Future studies should focus on an agreement about a robust and clinically relevant definition on symptom clusters; a multidimensional, valid and reliable symptom assessment tool; and an optimal analytical method in patients receiving haemodialysis.

RELEVANCE TO CLINICAL PRACTICE

Knowledge of symptom clusters may contribute to understanding the aetiology and pathophysiology of multiple concurrent and interactive symptoms in patients receiving haemodialysis and exploring the effects of these symptoms on clinical outcomes.

Identification of Symptom Clusters in Cancer Patients at Palliative Care Clinic

Objective:

Cancer patients often experience a large number of symptoms together. The aim of this study is to determine the symptom clusters in cancer patients at palliative care clinic.

Methods:

Hundred and seventy consecutive patients were enrolled in the study. Memorial Symptom Assessment Scale was used for symptom assessment of the patients.

Results:

The most experienced symptoms by the patients during the past week before hospitalization in palliative care clinic were lack of energy (95.4%), weight loss (91.2%), lack of appetite (89.4%), pain (88.2%), dry mouth (87.6%), feeling sad (87.6%), feeling nervous (82.9%), worrying (81.2%), and feeling irritable (80.6%). Five symptom clusters were defined. First cluster: pain, feeling nervous, dry mouth, worrying, feeling irritable, weight loss; second cluster: feeling drowsy, numbness/tingling in hands/feet, difficulty in sleeping, dizziness, constipation, I do not look like myself; third cluster: nausea, vomiting; fourth cluster: shortness of breath, difficulty in swallowing, cough, change in the way food tastes; and fifth cluster: feeling bloated, problems with urination, diarrhea, itching, mouth sores, hair loss, swelling of arm or legs, change in the skin.

Conclusions:

We encountered various symptom clusters in advanced cancer patients. Identification of symptom clusters and knowledge of cluster composition in oncological population may particularly contribute individualization of the treatment.

Cancer Symptom Cluster Management

OBJECTIVES

To discuss the importance of cancer symptom clusters in clinical practice, review evidence for symptom cluster interventions, and make recommendations for symptom cluster identification, patient education, and management in clinical practice.

DATA SOURCES

Primary research and review articles identified through CINAHL, PubMed, and PsycINFO databases.

CONCLUSION

Several studies have investigated interventions for multi-symptom management or have evaluated the secondary effects of a single-symptom intervention on related symptoms. To date, only five studies have tested an intervention designed to manage a specific cancer symptom cluster. Those studies used nonpharmacologic approaches (psycho-education, cognitive-behavioral strategies, and acupressure) to address the pain, fatigue, and sleep disturbance symptom cluster, or the respiratory distress symptom cluster with some initial evidence of success. Further development and efficacy testing of symptom cluster interventions is needed.

IMPLICATIONS FOR NURSING PRACTICE

Clinical practice can be guided by knowledge of individual and multi-symptom management, and clinical judgment regarding possible etiologies of cancer symptom clusters. Clinicians should be aware of co-occurring symptoms in their patients, educate and involve patients in identifying symptom clusters and aggravating/alleviating factors, and coordinate treatment recommendations using strategies that are likely to be beneficial across symptoms.