Symptom clusters in patients receiving chemotherapy: A systematic review

Correlation between cancer cachexia and psychosocial impact in older patients with advanced lung cancer undergoing chemotherapy

Objective

This study aimed to evaluate the association of cancer cachexia with psychosocial impact, nutrition impact symptoms (NIS), and geriatric assessment in older patients newly diagnosed with advanced lung cancer undergoing chemotherapy.

Methods

Older patients with advanced lung cancer scheduled to receive first-line chemotherapy between August 2021 and February 2022 were enrolled. Cachexia was diagnosed according to the International Consensus. NIS and psychosocial impacts were assessed using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaires (EORTC QLQ) C30, CAX24, and the Eating-Related Distress Questionnaire (ERD). Non-parametric tests evaluated the association between cachexia and its impacts. Patients with cachexia who consented to be interviewed were asked about their experiences with diet and weight changes. Three authors reviewed the interview data to ensure the analysis's veracity.

Results

Twenty-one of the 31 participants (68%) had cachexia at baseline. The cachexia group showed significantly greater severity of Food Aversion (P ​= ​0.035), Eating and Weight Loss Worry (P ​< ​0.001), and Loss of Control (P ​= ​0.005) compared to the non-cachexia group. There were no significant differences in the ERD and geriatric assessment (all P ​> ​0.05). The interview revealed that patients with cachexia perceived diet and weight changes early on and tried to manage their symptoms by themselves.

Conclusions

Cancer cachexia showed an association with NIS and psychosocial impacts. Older patients with advanced lung cancer scheduled to receive first-line chemotherapy should undergo a comprehensive assessment of cancer cachexia, including its potential physical and psychological impacts.

Trial registration

The trial registration number was UMIN 000053843.

Symptoms and Symptom Clusters in Adolescents Receiving Chemotherapy Treatment for Oncological Malignancy

This descriptive study evaluated the symptoms and their clustering in adolescents undergoing chemotherapy for oncological malignancies. Conducted between December 2022 and December 2023, the study included 133 adolescents aged 10 to 18 years who were treated for cancer in the pediatric oncology unit of a university hospital in Turkey. Data analysis involved mean and percentage calculations, factor analysis, hierarchical clustering methods, dendrograms, and correlation analysis. The mean age of participants was 14.13 ± 2.13 years, with 52.6% being male. The most frequently reported symptoms were lack of appetite (75.9%), feeling nervous (74.4%), and lack of energy (69.2%), while the least common symptoms included problems with urination (25.6%), constipation (22.6%), and swelling of the arms or legs (10.5%). Four distinct symptom clusters were identified: Cluster 1 included nausea, vomiting, pain, lack of appetite, lack of energy, and drowsiness; Cluster 2 encompassed dry mouth, irritability, sadness, and worry; Cluster 3 comprised changes in taste perception, altered self-image ("I don't look like myself"), weight loss, hair loss, skin changes, mouth sores, and nervousness; and Cluster 4 included diarrhea, itching, sweating, difficulty swallowing, urinary problems, insomnia, dyspnea, dizziness, limb swelling, constipation, and cough. The study highlighted that lack of appetite, feeling nervous, and lack of energy were the most prevalent symptoms and categorized symptoms into four distinct clusters, offering a framework for targeted nursing interventions. The identification of specific symptom clusters - ranging from gastrointestinal distress to emotional well-being - underscores the importance of cluster-based approaches in enhancing symptom management strategies.

Integrating Remote Symptom Monitoring, Person-Centered Analytics, and Artificial Intelligence to Advance Precision Health Symptom Science in Oncology

OBJECTIVES

To summarize the relevance of remote symptom monitoring, person-centered statistical analyses, and artificial intelligence to precision health symptom science in oncology; and propose ways in which these three approaches can be integrated to further advance the field.

METHODS

The following commentary was adapted from a talk delivered at the Symptom Science Experts Meeting in October 2023 at the University of Lausanne, Switzerland. The commentary and talk were informed by an informal review of recent literature in precision health oncology symptom science.

RESULTS

Several remote symptom monitoring interventions have demonstrated potential to reduce disease- and treatment-related symptom burden and improve health outcomes in patients with cancer. Data collected passively by wearable and sensor technologies are also being used to characterize patients' health status. Person-centered statistical analyses have identified interindividual variability in the symptom experiences of patients with cancer. Together with artificial intelligence-based approaches, these analyses have identified factors associated with relatively adverse symptom experiences. Future directions for the field include integrating these approaches to optimize clinical resource allocation, tailor symptom management in real-time, and advance scientific knowledge of the symptom experience.

CONCLUSIONS

Integrating remote symptom monitoring, person-centered statistical analyses and artificial intelligence may provide deeper insights into how patients with cancer experience symptoms.

IMPLICATIONS FOR NURSING PRACTICE

Findings from research that uses remote symptom monitoring, person-centered statistical analyses, and artificial intelligence may enhance clinicians' ability to deliver personalized symptom management interventions.

Cancer Symptom Clusters in Children and Adolescents with Cancer Undergoing Chemotherapy: A Systematic Review

Objective: To synthesize and analyze the prevalence, composition, longitudinal stability, and predictors of cancer symptom clusters in children and adolescents undergoing chemotherapy. Method: A systematic literature review was conducted in accordance with the PRISMA 2020 guidelines. Evidence was sourced from MEDLINE/PubMed, Cochrane Library, Embase, PsycINFO, and Web of Science, as well as clinical trial registries (Clinical Trials WHO-ICTRP) and gray literature. The search was performed in February 2025, with no restrictions on publication date or language. Two independent reviewers screened and selected the studies. The methodological quality of the included studies was assessed using design-specific tools, and the findings were synthesized narratively. Results: A total of 6221 records were identified, with 12 studies meeting the inclusion criteria. These studies were published between 2010 and 2024 in the United States, Brazil, China, and Turkey. Cancer symptom clusters in children and adolescents followed well-defined patterns, with the gastrointestinal, emotional, fatigue-related, somatic, and self-image clusters being the most prevalent. Conclusions: Early identification of these cancer symptom clusters is essential for guiding interprofessional teams in delivering personalized, evidence-based care to children and adolescents with cancer and their families.

Breaking the code: Using the Precision Health Model to guide research and clinical care

BACKGROUND

Precision health is a person-centered approach to health and well-being that is operationalized through evaluating omics-level profiles and their associations with the exposome. A precision health approach addresses the challenge that "one size does not fit all" in the management of an individual's health.

PURPOSE

The purpose of this white paper is to introduce a Precision Health Model and its application in research and clinical care.

METHODS

An expert panel reviewed and synthesized the extant literature related to precision health, the current state of omics' science, and common exposome factors that influence the health/illness continuum. A case study provides the framework for the application of the Precision Health Model.

DISCUSSION

Precision health and key domains are defined and serve as the platform for the development of the Precision Health Model.

CONCLUSION

Application of the Precision Health Model will provide inclusive, equitable, person-centered research and clinical care.

Differences in symptom clusters based on multidimensional symptom experience and symptom burden in stroke patients

In the study of stroke symptoms, a significant unresolved issue remains: What are the similarities and differences in the use of three symptom dimensions-occurrence, severity, and distress-and symptom burden to identify symptom clusters, and which level is recommended for constructing symptom clusters? This study aimed to identify the number and types of symptom clusters in stroke patients on the basis of these dimensions and to determine the most suitable dimension for extracting symptom clusters. Data were collected from 656 stroke patients via a convenience sampling method at a tertiary-level hospital in Wuhan, China, between August 2023 and March 2024. Exploratory factor analysis was conducted to extract symptom clusters on the basis of the three dimensions of the symptom experience scale and symptom burden. Four similar symptom clusters were identified: the mood disturbance symptom cluster, the physical symptom cluster, the cognitive dysfunction symptom cluster, and the slurred speech and choking cough symptom cluster. The symptom of "fatigue" within the physical symptom cluster was not identified only in the dimension of distress (with a percentage agreement of 83.3%), whereas the symptom composition of other clusters remained consistent across all three symptom dimensions (with a percentage agreement of 100%). Moreover, all four symptom clusters exhibited high consistency in terms of both occurrence and symptom burden, regardless of whether the symptom with the highest factor loading or the overall symptom composition was considered. The use of symptom occurrence and symptom burden is recommended for identifying symptom clusters in stroke patients. Subsequently, trajectory studies of symptom clusters and symptom network analyses should be conducted on the basis of these two dimensions to establish a solid theoretical foundation for future clinical interventions and related scientific research.

Symptom Clusters in Patients with Brain Tumors: A Systematic Review

OBJECTIVES

To identify composition, predictors, outcomes and stability of symptom clusters in brain tumor patients and to examine assessment tools and statistical methods.

METHODS

The PubMed, Web of Science, Embase, CINAHL, and Cochrane Library databases were systematically searched. Two reviewers independently screened the titles, abstracts and full texts. Data were extracted and synthesized based on the aims of the review.

RESULTS

Eleven studies were included, covering eight symptom assessment tools and four analysis methods. Four symptom clusters in patients with primary brain tumors were identified: lack of energy cluster/ affective cluster/ gastrointestinal cluster/ neurocognitive cluster. Three symptom clusters in patients with brain metastases were identified: somatic stress cluster/ gastrointestinal cluster/ neurocognitive cluster. Longitudinal instability of symptom clusters was found. The severity of symptom clusters has a significant negative correlation with quality of life, performance status and functioning. There is little information on the predictors.

CONCLUSIONS

Although major symptom clusters of patients with primary brain tumors and brain metastases have been identified, methodological differences have affected the homogeneity of the inferences drawn. It is necessary to standardize the selection of assessment tools and statistical methods for symptom cluster research to facilitate comparison and combination across studies, and further clarify the temporal trajectories, predictive factors, and underlying mechanisms.

IMPLICATIONS FOR NURSING PRACTICE

Knowledge of symptom clusters contributes to the adoption of prevention strategies and management measures and the adjustment of treatments, thus alleviating symptom distress and improving quality of life.

Analyzing the Symptom Clusters Among Children With Acute Lymphoblastic Leukemia During Chemotherapy Based on Electronic Nursing Records

BACKGROUND

Children with acute lymphoblastic leukemia often experience various physical and psychological symptoms during chemotherapy. Previous studies have used predetermined symptom inventories to analyze the complex relationships between these symptoms, which has certain limitations.

OBJECTIVE

The aim of this study was to explore the dynamic changes in symptom clusters among children with acute lymphoblastic leukemia during chemotherapy using electronic nursing records.

METHODS

Electronic nursing records for 2021 (N = 14 490) were obtained from a pediatric hematology department. A natural language processing tool was used to identify the presence of 46 symptoms in 3 chemotherapy phases of induction, consolidation, and maintenance. Incidence of symptom documentation was calculated by notes and patients, and principal component analysis and cluster analysis were performed for symptoms with an incidence above 15%.

RESULTS

The most common symptoms included bleeding, cough, and vomiting. The number of symptom clusters in each chemotherapy period was 7, 6, and 4, respectively. There were upper gastrointestinal, respiratory system, lower gastrointestinal, skin-related, psychological, self-image disorder, and other discomfort symptom clusters in the induction period. Notably, the upper gastrointestinal, respiratory system, lower gastrointestinal, and skin-related symptom clusters persisted through the consolidation and maintenance periods. Neurological and other discomfort symptom clusters were observed during the consolidation period.

CONCLUSION

Symptom clusters of children with acute lymphoblastic leukemia at various stages of chemotherapy showed a certain level of stability and dynamics, informing healthcare providers in developing continuous symptom management.

IMPLICATIONS FOR PRACTICE

Medical staff should explore targeted intervention programs based on characteristics of symptom clusters at different chemotherapy stages, to improve the efficiency of symptom management and alleviate the symptom burden of children.

Symptom clusters and self-management experiences of cervical cancer patients undergoing concurrent chemoradiotherapy: a qualitative study

PURPOSE

To explore symptom clusters, symptom experiences, and self-management strategies in patients with cervical cancer undergoing concurrent chemoradiotherapy.

METHODS

A qualitative descriptive approach was used. Semi-structured interviews were conducted with patients with cervical cancer using an interview guide. The audio recording of the interviews was transcribed. Thematic analysis was conducted using Colaizzi's seven-step framework.

RESULTS

Thirteen participants were interviewed. The mean age of the participants was 47 years. Three themes were identified: (a) Struggle for survival among patients reintegrating into society; (b) Overcoming self-management challenges; and (c) Resilience and adaptation in the face of adversity.

CONCLUSION

Individuals diagnosed with cervical cancer who undergo concurrent chemoradiotherapy often experience various clusters of symptoms. Despite facing challenges in self-management, these patients maintain a positive attitude and persistently strive to coexist harmoniously with their health conditions.

BURN-OP: A screening tool for identifying a symptomatically distinct cluster of burn patients with the greatest healthcare needs at discharge

OBJECTIVE

To identify burn patients needing intensive rehabilitation based on discharge symptoms.

METHODS

We conducted a retrospective analysis of 1049 adult burn patients recruited to the Burn Injury Model System National Database. Using unsupervised hierarchical clustering, we identified three distinct patient clusters based on discharge symptoms and compared their clinical and demographic profiles, long-term rehabilitative needs, and self-reported quality of life. We also developed a weighted BUrn Rehabilitative Needs - OutPatient (BURN-OP) to prospectively identify patients with highest rehabilitative needs.

RESULTS

Three burn patient clusters were identified: Cluster 1 with low, Cluster 2 with moderate, and Cluster 3 with high symptom burdens. Cluster 3, comprising 6 % of discharged patients, had notably longer hospital stays, older age at burn, larger total body surface area (TBSA), increased days on ventilator, a higher number of surgical procedures, concomitant inhalation injury, and higher weight loss from admission to discharge. Cluster 3 patients preferentially utilized a wide spectrum of rehabilitative services (including physiotherapy, occupational therapy, speech-language pathology, social work, psychologic services, vocational services) extending up to 2 years post-discharge. Their self-reported health outcomes were worse, with greater limitations in work/activity and elevated pain interference persisting 5-years post-discharge. BURN-OP demonstrated high specificity (98.99 %) and accuracy (96.19 %, ROC AUC: 0.93) in identifying Cluster 3 patients at discharge.

CONCLUSIONS

We identify distinct burn patient clusters based on discharge symptoms, with Cluster 3 exhibiting the highest post-discharge healthcare needs. BURN-OP (https://burn-op.streamlit.app/) identifies high-risk patients, offering a tool for prioritizing interventions and designing trials that mitigate risk of Cluster 3 membership.

Impact of Multimorbidity on Symptom Burden and Symptom Clusters in Patients Receiving Chemotherapy

BACKGROUND

Detailed information on patient characteristics and symptom burden associated with multimorbidity in oncology patients is extremely limited. Purposes were to determine the prevalence of low (≤ 2) and high (≥ 3) multimorbidity in a sample of oncology outpatients (n = 1343) undergoing chemotherapy and evaluate for differences between the two multimorbidity groups in demographic and clinical characteristics; the occurrence, severity, and distress of 38 symptoms; and the stability and consistency of symptom clusters.

METHODS

Using the Self-Administered Comorbidity Questionnaire, patients were classified into low and high multimorbidity groups. Memorial Symptom Assessment Scale was used to assess the occurrence, severity, and distress of 38 symptoms prior to the patients' second or third cycle of chemotherapy. For each multimorbidity group, symptom clusters based on occurrence rates were identified using exploratory factor analysis.

RESULTS

Compared to the low group (61.4%), patients in the high group (38.6%) were older, had fewer years of education, were less likely to be married or partnered, less likely to be employed, and had a lower annual income. In addition, they had a higher body mass index, poorer functional status, were a longer time since their cancer diagnosis, and were more likely to have received previous cancer treatments and have metastatic disease. Patients in the low and high groups reported 12.7 (±6.7) and 15.9 (±7.5) concurrent symptoms, respectively. Eight and seven symptom clusters were identified for the low and high groups, respectively. Psychological, gastrointestinal, weight gain, hormonal, and respiratory clusters were stable across multimorbidity groups. Weight gain and respiratory clusters were consistent. Three unstable clusters were identified in the low group and two in the high group.

CONCLUSIONS

Findings suggest that higher multimorbidity is associated with various social determinants of health and a higher symptom burden. Differences between multimorbidity groups may be related to aging, treatments, and/or comorbid conditions.

The effect of honey in oral care intervention against chemotherapy-induced mucositis in pediatric cancer patients: a pilot study

OBJECTIVE

Mucositis is one of the common side effects of chemotherapy. This study aimed to identify the effects of honey on oral care interventions to reduce mucositis scores among children undergoing chemotherapy.

METHODS

This pilot study was quasi-experimental with pre-post intervention with the control group. The study employed consecutive sampling, with 24 patients in the control and 24 in the intervention group. The intervention group received an oral care protocol using honey, whereas the control group received regular oral care. The data were collected using demographic information form and the Oral Assessment Guide (OAG) to assess mucositis. The intervention group received oral care intervention using honey (35 ml of honey applied topically in the oral cavity and 15 ml of honey used as a mouthwash and for lip care), which was given thrice daily for five days. The data were analyzed using percentage distributions, means, chi-square tests, dependent and independent t-tests, and multivariate analysis using analysis of covariance (ANCOVA).

RESULTS

The findings of this study showed that the intervention group experienced a significant reduction (-0.51 ± 0.66) in the average mucositis score after the intervention, whereas the control group experienced an increase in the mucositis score (3.84 ± 1.28) after controlling for confounding variables (p = 0.000).

CONCLUSION

This study revealed that oral care with honey effectively reduced chemotherapy-induced mucositis in children with cancer. These findings suggest that oral care with honey should be used as a nursing intervention for chemotherapy patients.

TRIAL REGISTRATION

This clinical trial was retrospectively registered in the Australian New Zealand Clinical Trials Registry (ANZCTR) with registration number ACTRN12624001313527 (29/10/2024).

Symptom burden and clusters during chemotherapy in patients with lung cancer

OBJECTIVE

This study aims to investigate the distribution characteristics of symptoms in patients with lung cancer during chemotherapy, identify the symptom clusters (SCs) and explore the underlying mechanisms. The findings will provide evidence to assist clinical staff in effectively managing symptoms and SCs.

METHODS

Participants were recruited from the Oncology Department of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, between July 2022 and December 2022. The incidence and severity of symptoms were assessed and SCs were identified. Spearman's correlation analysis was used to examine the correlation between lung cancer-specific SC and routine blood indices.

RESULTS

A total of 169 patients participated in the study. The most prevalent and severe symptom was loss of appetite. Based on the occurrence rate and severity of symptoms, SC extraction was performed for mild, moderate, and severe symptoms, resulting in the identification of five SCs: psycho-emotional SC, chemotherapy-related SC, lung cancer-specific SC, urinary-related SC, and gastrointestinal SC. When only the moderate and severe symptoms were considered, two SCs were identified: chemotherapy-related SC and lung cancer-specific SC. Additionally, the lung cancer-specific SC showed a negative correlation with eosinophils.

CONCLUSION

Patients with lung cancer undergoing chemotherapy experience complex and diverse symptoms. A total of five SCs were extracted based on mild, moderate and severe symptoms and two SCs were extracted based on moderate and severe symptoms. The results of the study showed that lung cancer-specific SC was negatively correlated with eosinophils. Future research should focus on developing and refining research tools, methodologies, understanding the pathogenesis, and exploring intervention measures for SCs.

Exploring Symptom Cluster Patterns in Adult Cancer Patients Undergoing Chemotherapy: A Systematic Review

PURPOSE

This systematic review aimed to scrutinize the progression of symptom cluster research in adult cancer patients who received primary or adjuvant chemotherapy between 2001 and 2023, providing a comprehensive understanding of clinical practice and future research.

METHODS

PubMed, Ovid MEDLINE, Excerpta Medica Database, Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, and Web of Science databases were searched for theme words and free words related to symptom clusters, cancer, and chemotherapy. Eligible studies were published between January 1, 2001, and May 30, 2023; adults who were diagnosed with cancer and received primary or adjuvant chemotherapy were evaluated.

RESULTS

Twenty-nine studies were included in this review. The Memorial Symptom Assessment Scale emerged as the predominant instrument and exploratory factor analysis was the most frequently employed statistical method to identify symptom clusters. Psychological, gastrointestinal, and physical image symptom clusters were the most commonly delineated. Furthermore, the temporal stability of the symptom clusters showed varying dynamics, with psychological symptom clusters displaying relative consistency over time.

CONCLUSION

Interventions are needed for the most common and stable symptoms in patients with cancer undergoing chemotherapy. Future endeavors may necessitate more longitudinal studies to delve deeper into the temporal stability and dynamic variations of symptom clusters. Such investigations hold promise for advancing symptom cluster research, elucidating the underlying mechanisms, and fostering the development of targeted interventions, thereby enriching the symptom management paradigm in oncological care.

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.

[Patient-reported outcomes in chronic diseases under treatment with cannabis medicines : Analysis of the results of the Copeia survey]

BACKGROUND

The survey of Copeia captured early 2022 patient-reported outcomes (PRO) in Germany under cannabis medicinal product (CAM) therapy, with particular attention to symptoms, symptom changes, indications, side effects, dosages, and cost bearers.

GOAL

This study investigated the question of whether associations emerge from the results that could play a role in the indication and treatment monitoring of CAM in chronically ill patients.

MATERIALS AND METHODS

A standardized questionnaire was administered online nationwide in dialogue form over a 15-week period to collect itemized symptoms and PRO. Recruitment was supported by pharmacies, prescribing physicians, and patient associations. Inclusion criteria included physician-prescribed CAM therapy.

RESULTS AND DISCUSSION

Of 1582 participants, 1030 data sets (65%) could be completely analyzed. There was a heterogeneous patient population, whose common feature was disease chronicity. The frequency distribution of symptoms showed a homogeneous pattern for the respective indications, in which the most frequent six (pain 71%, sleep disturbance 64%, stress/tension 52%, inner restlessness 52%, depressive mood 44% and muscle tension 43%) seem to have a special significance. According to subjective assessment, quality of life improved significantly in 84% of all participating patients.

CONCLUSION

A symptom matrix (SMX) composed of different symptoms seems to play a special role in CAM therapy to improve the quality of life of chronically ill patients, regardless of the underlying disease. The SMX could contribute to the identification of an indication and to targeted treatment monitoring.

Common patient-reported sources of cancer-related distress in adults with cancer: A systematic review

BACKGROUND

Cancer-related distress (CRD) is widely experienced by people with cancer and is associated with poor outcomes. CRD screening is a recommended practice; however, CRD remains under-treated due to limited resources targeting unique sources (problems) contributing to CRD. Understanding which sources of CRD are most commonly reported will allow allocation of resources including equipping healthcare providers for intervention.

METHODS

We conducted a systematic review to describe the frequency of patient-reported sources of CRD and to identify relationships with CRD severity, demographics, and clinical characteristics. We included empirical studies that screened adults with cancer using the NCCN or similar problem list. Most and least common sources of CRD were identified using weighted proportions computed across studies. Relationships between sources of CRD and CRD severity, demographics, and clinical characteristics were summarized narratively.

RESULTS

Forty-eight studies were included. The most frequent sources of CRD were worry (55%), fatigue (54%), fears (45%), sadness (44%), pain (41%), and sleep disturbance (40%). Having enough food (0%), substance abuse (3%), childbearing ability (5%), fevers (5%), and spiritual concerns (5%) were infrequently reported. Sources of CRD were related to CRD severity, sex, age, race, marital status, income, education, rurality, treatment type, cancer grade, performance status, and timing of screening.

CONCLUSIONS

Sources of CRD were most frequently emotional and physical, and resources should be targeted to these sources. Relationships between sources of CRD and demographic and clinical variables may suggest profiles of patient subgroups that share similar sources of CRD. Further investigation is necessary to direct intervention development and testing.

Breast cancer symptom profile longitudinal changes: data mining study

OBJECTIVES

Identifying stable co-occurring symptoms in breast cancer (BC) patients during chemotherapy can improve symptom management and the treatment process. This study examines symptom cluster stability in Iranian BC patients receiving chemotherapy and evaluates stability across three-time points within each cluster.

METHODS

This study collected data from three-time points: initial chemotherapy commencement, 2½ months postdiagnosis, and 5 months postdiagnosis. The research used exploratory factor analysis (EFA) in combination with hierarchical cluster analysis (HCA) and K means clustering to address research questions.

RESULTS

In the initial clustering step, EFA identified five clusters with high consistency across three-time points. The first cluster showed depression, anxiety and irritability, while the second cluster was characterised by sexual interest and pain. The third cluster was associated with diarrhoea and vomiting. In the second step, we obtained the HCA item output and two clusters of K means clustering that recorded depression and anxiety symptoms over time. Vomiting, dry mouth, sexual interest, worrying and numbness were observed during the first and second points, but the frequency has decreased since then.

CONCLUSIONS

Cancer's psychological and physiological symptoms, including depression, anxiety, digestive and hormonal issues, remain stable throughout the disease. Palliative care centres can improve patients' quality of life and treatment process by addressing persistent symptoms.

Comparing symptom clusters in cancer survivors by cancer diagnosis: A latent class profile analysis

PURPOSE

Research on symptom clusters in oncology is progressing, but knowledge gaps remain. One question is whether the number and types of symptom subgroups (i.e., latent classes) differ based on cancer diagnosis. The purpose of this study was to: (1) identify and compare latent class subgroups based on four highly prevalent symptoms (pain, fatigue, sleep disturbance, and depression), and (2) examine the differences in sociodemographic and clinical factors in the identified latent classes across the seven cancer types (i.e., prostate, non-small cell lung, non-Hodgkin's lymphoma, breast, uterine, cervical, and colorectal cancer).

METHODS

This study is a cross-sectional secondary analysis of data obtained from the My-Health study in partnership with four Surveillance, Epidemiology, and End Results (SEER) cancer registries located in California (two), Louisiana, and New Jersey. The sample included 4,762 cancer survivors 6-13 months following diagnosis of one of the seven cancer types mentioned. Latent class profile analysis was used.

RESULTS

Subjects were primarily young (59% age 21-64 years), Caucasian (41%), married/cohabitating (58%) and unemployed (55%). The number and types of symptom subgroups varied across these seven cancer populations: four-subgroups were the common in prostate, lung, non-Hodgkin's lymphoma, and breast cancer survivors. Unmarried, low education, and unemployment status were associated with high risk of symptom burden across the cancer types.

CONCLUSION

Identifying symptom subgroups by cancer diagnosis has the potential to develop innovative and effective targeted interventions in cancer survivors. Further research is needed to establish extensive knowledge in symptom clustering between treatment regimens, and short-term and long-term cancer survivors.

Symptom clusters and their impact on quality of life in multiple myeloma survivors: Secondary analysis of BMT CTN 0702 trial

Autologous haematopoietic cell transplantation (autoHCT) and continuous post-transplant maintenance therapy are the standard of care in transplant-eligible multiple myeloma (MM) patients. We sought to describe symptom burden and identify symptom clusters occurring in MM patients after autoHCT using data from the BMT CTN 0702 randomized controlled trial comparing the outcomes of three treatment interventions after an autoHCT in 758 MM patients. We analysed individual transplant-related symptoms assessed via the FACT-BMT questionnaire at enrolment and annually for 4-year post-autoHCT. We also described the effect the individual symptoms and symptom clusters have on quality of life (QoL). We identified three stable symptom clusters: malaise symptom cluster (lack of energy, feeling ill, having pain, experiencing nausea, loss of appetite), physical symptom cluster (having skin problems, tremors, worsening eyesight, change in taste, shortness of breath, frequent colds) and emotional symptom cluster (feeling sad, being nervous, experiencing sleep problems). Malaise and emotional symptom clusters have a greater impact on QoL than the physical symptoms cluster. Identifying these symptoms warrant additional support in terms of psychosocial support, in addition to treatment of the physical symptoms themselves.

Network analysis used to investigate the interplay among somatic and psychological symptoms in patients with cancer and cancer survivors: a scoping review

PURPOSE

Patients with cancer often experience multiple somatic and psychological symptoms. Somatic and psychological symptoms are thought to be connected and may reinforce each other. Network analysis allows examination of the interconnectedness of individual symptoms. The aim of this scoping review was to examine the current state of knowledge about the associations between somatic and psychological symptoms in patients with cancer and cancer survivors, based on network analysis.

METHODS

This scoping review followed the five-stage framework of Arksey and O'Malley. The literature search was conducted in May, 2023 in PubMed, APA PsycINFO, Embase Cochrane central, and CINAHL databases.

RESULTS

Thirty-two studies were included, with eleven using longitudinal data. Seventeen studies reported on the strength of the associations: somatic and psychological symptoms were associated, although associations among somatic as well as among psychological symptoms were stronger. Other findings were the association between somatic and psychological symptoms was stronger in patients experiencing more severe symptoms; associations between symptoms over time remained rather stable; and different symptoms were central in the networks, with fatigue being among the most central in half of the studies.

IMPLICATIONS FOR CANCER SURVIVORS

Although the associations among somatic symptoms and among psychological symptoms were stronger, somatic and psychological symptoms were associated, especially in patients experiencing more severe symptoms. Fatigue was among the most central symptoms, bridging the somatic and psychological domain. These findings as well as future research based on network analysis may help to untangle the complex interplay of somatic and psychological symptoms in patients with cancer.

Machine Learning Approaches to Predict Symptoms in People With Cancer: Systematic Review

BACKGROUND

People with cancer frequently experience severe and distressing symptoms associated with cancer and its treatments. Predicting symptoms in patients with cancer continues to be a significant challenge for both clinicians and researchers. The rapid evolution of machine learning (ML) highlights the need for a current systematic review to improve cancer symptom prediction.

OBJECTIVE

This systematic review aims to synthesize the literature that has used ML algorithms to predict the development of cancer symptoms and to identify the predictors of these symptoms. This is essential for integrating new developments and identifying gaps in existing literature.

METHODS

We conducted this systematic review in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. We conducted a systematic search of CINAHL, Embase, and PubMed for English records published from 1984 to August 11, 2023, using the following search terms: cancer, neoplasm, specific symptoms, neural networks, machine learning, specific algorithm names, and deep learning. All records that met the eligibility criteria were individually reviewed by 2 coauthors, and key findings were extracted and synthesized. We focused on studies using ML algorithms to predict cancer symptoms, excluding nonhuman research, technical reports, reviews, book chapters, conference proceedings, and inaccessible full texts.

RESULTS

A total of 42 studies were included, the majority of which were published after 2017. Most studies were conducted in North America (18/42, 43%) and Asia (16/42, 38%). The sample sizes in most studies (27/42, 64%) typically ranged from 100 to 1000 participants. The most prevalent category of algorithms was supervised ML, accounting for 39 (93%) of the 42 studies. Each of the methods-deep learning, ensemble classifiers, and unsupervised ML-constituted 3 (3%) of the 42 studies. The ML algorithms with the best performance were logistic regression (9/42, 17%), random forest (7/42, 13%), artificial neural networks (5/42, 9%), and decision trees (5/42, 9%). The most commonly included primary cancer sites were the head and neck (9/42, 22%) and breast (8/42, 19%), with 17 (41%) of the 42 studies not specifying the site. The most frequently studied symptoms were xerostomia (9/42, 14%), depression (8/42, 13%), pain (8/42, 13%), and fatigue (6/42, 10%). The significant predictors were age, gender, treatment type, treatment number, cancer site, cancer stage, chemotherapy, radiotherapy, chronic diseases, comorbidities, physical factors, and psychological factors.

CONCLUSIONS

This review outlines the algorithms used for predicting symptoms in individuals with cancer. Given the diversity of symptoms people with cancer experience, analytic approaches that can handle complex and nonlinear relationships are critical. This knowledge can pave the way for crafting algorithms tailored to a specific symptom. In addition, to improve prediction precision, future research should compare cutting-edge ML strategies such as deep learning and ensemble methods with traditional statistical models.

Perceived communication efficacy and unmet needs for chemotherapy-associated symptom management in patients with lung and colorectal cancer: a cross-sectional study

BACKGROUND

Understanding cancer patients' unmet needs for chemotherapy-related symptom management will assist clinicians in developing tailored intervention programs. Little is known about the association between perceived communication efficacy and unmet care needs for symptom management in patients with lung and colorectal cancer.

OBJECTIVES

To examine the unmet care needs for symptom management of patients with lung and colorectal cancer and their association with perceived communication efficacy.

METHODS

A cross-sectional survey was conducted in a tertiary hospital in China from July to November 2020. A convenience sample of 203 patients with lung and colorectal cancer undergoing chemotherapy completed survey questionnaires, including the MD Anderson Symptom Inventory Scale and the Perceived Efficacy in Patient‒Physician Interactions Scale.

RESULTS

Approximately 43% of participants had at least one symptom with unmet needs. Fatigue was reported as the symptom with the highest occurrence (66%), the highest demand for supportive care (36%), and the highest prevalence of unmet needs (19%). Low levels of perceived communication efficacy independently predicted participants' unmet needs for symptom management (β=-0.13, p = 0.011).

CONCLUSIONS

This study highlights the necessity of introducing clinical assessment tools and guidelines to address fatigue and other chemotherapy-induced symptoms in patients with lung and colorectal cancer. Clinical programs designed to actively engage cancer patients to voice their needs and strengthen their communication efficacy are also warranted.

Associations of Cancer Patients' Demographic and Clinical Characteristics With Cannabis-Related Interest and Behaviors

Background: Cannabis interest and use is increasing in the United States, yet research on its use among cancer patients is limited. Methods: Individuals with cancer completed an anonymous cross-sectional questionnaire. Multivariable logistic regressions estimated odds ratios (OR) between patients' demographic and clinical characteristics with cannabis-related interest, current use, and provider recommendation. Results: Participants (n = 943) were, on average, 61.7 years old. Older patients were less likely to use cannabis products (OR = 0.42, confidence interval [95% CI]: 0.26-0.69) and less likely to be interested in cannabis (OR = 0.60, 95% CI: 0.44-0.84) than younger patients. Those with higher education were less likely to be using cannabis (OR = 0.41, 95% CI: 0.25-0.67) and less likely to have received a provider recommendation of cannabis use than the least educated (OR = 0.38, 95% CI: 0.19-0.76). Cancer spread and type were significant correlates of provider recommendation of cannabis use. Conclusions: Additional research is warranted to better understand cancer patients' motivations for cannabis use and interest.

Patient-reported outcomes and symptom clusters pattern of chemotherapy-induced toxicity in patients with early breast cancer

OBJECTIVE

This study aims to characterize patient-reported chemotherapy-induced toxicity in patients with breast cancer, determine its association with treatment regimens and patient characteristics, identify toxicity symptom clusters within a specific chemotherapy timeframe and analyze the correlation between symptom clusters within and between the timeframe to understand the changes and influences across chemotherapy.

METHODS

Forty-six patient-reported toxicities during neoadjuvant/adjuvant chemotherapy for breast cancer were evaluated using adapted CTCAE version 4.0. Chi-Square/Fisher's Exact test was performed to analyze the difference in the incidence of toxicity symptoms by chemotherapy regimens. Poisson regression performed to assess factors associated with patient's total chemotherapy toxicity. Exploratory factor analysis (EFA) conducted to identify symptom clusters at T1 (first half) and T2 (second half of planned cycle). Factor scores were generated and Spearman correlation performed to explore the factor scores correlation between symptom clusters.

RESULTS

A total of 142 patients with stage I-III breast cancer were included. The incidence of several toxicities differed significantly among three chemotherapy regimens. Subjects age ≥51 years are associated with lower number of reported toxicity (IRR/incidence rate ratio = 0.94, 95% confidence interval/CI 0.88 to 0.99, p = 0.042). Receiving more chemotherapy cycles are associated with higher number of reported toxicity (IRR = 1.06, 95% CI 1.03 to 1.10, p<0.001). Two symptom clusters identified at T1 (psychoneurological-pain/PNP-T1 and gastrointestinal-psychological/GIP-T1 cluster) and three at T2 (psychoneurological-pain/PNP-T2, epithelial/EPI-T2, and gastrointestinal cluster/GI-T2), with moderate-strong positive correlation between PNP-T1 and GIP-T2 (p<0.001), PNP-T1 and PNP-T2 (p<0.001), and GIP-T1 and PNP-T2 (p<0.001).

CONCLUSIONS

This study investigated 46 patient-reported toxicities prospectively during adjuvant/neoadjuvant chemotherapy for early breast cancer. Anthracycline-taxane combination regimen had higher proportions of toxicity incidence. Subject's age and number of chemotherapy cycles significantly associated with total number of toxicity symptoms. Two symptom clusters at T1 and three at T2 were identified, with significant correlation between symptom clusters within and between chemotherapy timeframe.

Symptom clusters in oncology outpatients: stability and consistency across a cycle of chemotherapy

OBJECTIVES

Improved understanding of the stability and consistency of symptom clusters across time, symptom dimensions and cancer diagnoses will lead to refinements in symptom assessments and management, and provide direction for mechanistic studies. Study purposes were to describe the occurrence, severity and distress of 38 symptoms; evaluate the stability and consistency of symptom clusters across a cycle of chemotherapy, three symptom dimensions and four distinct cancer types; and identify common and distinct symptom clusters.

METHODS

Oncology outpatients (n=1329) completed the Memorial Symptom Assessment Scale prior to their next cycle of chemotherapy (T1), 1 week after chemotherapy (T2) and 2 weeks after chemotherapy (T3). Symptom clusters were identified using exploratory factor analysis using unweighted least squares. GEOMIN rotated factor loadings with absolute values ≥0.40 were considered meaningful. Clusters were stable if they were identified across each time point and/or dimension. Clusters were consistent if the same two or three symptoms with the highest factor loadings were identified across each time point and/or dimension.

RESULTS

Patients reported 13.9 (±7.2) symptoms at T1, 14.0 (±7.0) at T2 and 12.2 (±6.8) at T3. Psychological, weight gain, gastrointestinal and respiratory clusters were stable across time and dimensions. Only the psychological, weight gain and respiratory clusters were consistent across time and dimensions.

CONCLUSION

Given the stability of the psychological, weight gain and gastrointestinal clusters across cancer diagnoses, symptoms within these clusters need to be routinely assessed. However, respiratory and hormonal clusters are unique to specific cancer types and the symptoms within these clusters are variable.

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.

Subjective Toxicity Profiles of Children With Cancer During Treatment: A Latent Class Analysis

BACKGROUND

Children and adolescents may experience a variety of subjective adverse events (AEs) caused by cancer treatment. The identification of distinct groups of patients is crucial for guiding symptomatic AE management interventions to prevent AEs from worsening.

OBJECTIVE

The aim of this study was to identify subgroups of children with cancer experiencing similar patterns of subjective toxicities and evaluate differences among these subgroups in demographic and clinical characteristics.

METHODS

A cross-sectional survey was conducted of 356 children in China with malignancies who received chemotherapy within the past 7 days using the pediatric Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events. A latent class analysis (LCA) was conducted to identify subgroups of patients with distinct profiles of symptomatic AE occurrence.

RESULTS

Nausea (54.5%), anorexia (53.4%), and headache (39.3%) were the top 3 AEs children experienced. Nearly all participants (97.8%) experienced ≥1 core AEs, and 30.3% experienced ≥5 AEs. The LCA results identified 3 subgroups ("high gastrotoxicity and low neurotoxicity" [53.2%], "moderate gastrotoxicity and high neurotoxicity" [23.6%], and "high gastrotoxicity and high neurotoxicity" [22.8%]). The subgroups were differentiated by monthly family per-capita income, time since diagnosis, and Karnofsky Performance Status score.

CONCLUSIONS

Children experienced multiple subjective toxicities during chemotherapy, especially gastrotoxicity and neurotoxicity. Heterogeneity was found in the LCA in the patients' toxicities. The prevalence of toxicities could be distinguished by the children's characteristics.

IMPLICATIONS FOR PRACTICE

The results showing different subgroups in our study may assist clinical staff in focusing on patients with higher toxicities to provide effective interventions.

A Systematic Review of Experimental Studies on the Impact of Empowerment-Based Interventions on Child and Parent Outcomes in the Pediatric Oncology Setting

Background

Cancer has an impact not only on children but also on parents. Parents play the most crucial role in cancer's symptom control and management. However, as the primary caretakers, parents are frequently unprepared or engage in inappropriate behavior when caring for their children. Increasing parents' role through empowerment is critical in pediatric cancer care.

Purpose

This systematic review aimed to identify the effect of empowerment interventions on parent and child outcomes in pediatric oncology.

Methods

In this review, studies published between 2013 and 2023 in The Cumulative Index to Nursing and Allied Health Literature (CINAHL), PubMed, Embase, Medline, and Scopus databases were identified using a search strategy to identify relevant studies that determined empowerment-based intervention for parents in the pediatric oncology. This study used the Joanna Briggs Institute (JBI) critical appraisal tools to assess the quality of the studies. This systematic review followed the recommended reporting items for systematic reviews and meta-analysis (PRISMA) standards.

Results

Seven studies met the inclusion criteria: four randomized and three non-randomized experimental studies. Children range in age from 1-14 years. The intervention is mostly delivered through face-to-face learning using booklets or modules as a learning tool. The intervention is delivered in 2-6 sessions over 1-8 weeks, lasting 20-45 minutes each. In most studies, the interventions positively affect parents' outcomes (knowledge, caring behavior, distress, care burden, quality of life) and children's outcomes (oral mucositis, gastrointestinal complications, quality of life). The intervention, however, has no significant effect on the coping style. Barriers to implementation include parent-nurse commitment, the retention of parent-nurse participation, and more time spent to provide interventions.

Conclusion

Our study highlights that empowerment-based interventions positively impact parents and children. These findings suggest that an empowerment-based intervention should be developed to provide better cancer care for a parent and their children.

Systematic Review Registration

PROSPERO registration number was CRD42023422834.

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

Background

Cervical cancer patients have a high symptom burden during concurrent chemoradiotherapy (CCRT) and urgently need precise symptom management strategies. Nonetheless, the symptom profile and influencing factors are unclear.

Methods

A total of 234 patients with cervical cancer who underwent CCRT in a tertiary care hospital clinical oncology center in Guangxi Zhuang Autonomous Region from March 2022 to March 2023 were included in the study. The general information questionnaire, M.D. Anderson symptom inventory, Fatigue Scale-14, Pittsburgh Sleep Quality Index, and grip strength test were used for the investigation. Symptom clusters were extracted by exploratory factor analysis, and latent profile analysis was performed using Mplus 8.0 software. Multinomial logistic regression was used to explore the factors influencing the potential categories of symptom clusters.

Results

Exploratory factor analysis extracted four symptom clusters: a fatigue-related symptom cluster, a gastrointestinal-related symptom cluster, a mood-related symptom cluster, and a physical-related symptom cluster, of which the fatigue-related symptom cluster was more severe and was divided into three potential categories: low fatigue-good muscle fitness type (25.63%), general fatigue-moderate muscle fitness type (68.37%) and high fatigue-low muscle fitness type (6%). Multinomial logistic regression analysis showed that hemoglobin levels, tumor stage, absence of complications, and unemployment were factors influencing the fatigue-related symptom cluster in patients undergoing CCRT for cervical cancer.

Conclusions

Cervical cancer patients experience multiple symptom clusters during CCRT. Different characteristics appeared in different clusters. Among them, fatigue-related symptom clusters were more severe and heterogeneous. In clinical practice, we should pay attention to and use high symptom feature predictors, focusing on the core symptoms that play a dominant role, achieving early identification and management, and reducing patients' symptom burden.

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

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

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

BACKGROUND

Patients with inflammatory bowel disease report multiple symptoms, but the relationships among co-occurring symptoms are poorly understood. This study aimed to examine the prevalence of symptoms and explore symptom clusters and possible associations between symptom clusters and socio-demographic and clinical variables in patients newly diagnosed with inflammatory bowel disease.

METHODS

The IBSEN III study is a prospective population-based inception cohort of patients with inflammatory bowel disease. This study used patient data from the three largest hospitals in the study catchment area. The Memorial Symptom Assessment Scale was used to assess the prevalence of symptoms. Symptom clusters were identified using principal component analysis. Possible associations between socio-demographic and clinical variables and symptom cluster membership were estimated using regression analysis.

RESULTS

Of the 573 patients (age, ≥18 years) diagnosed with inflammatory bowel disease, 350 (61.1%) completed the questionnaire (responders). Eleven symptoms were reported by >50% of the responders. The three most prevalent symptoms were bloating (84%), drowsiness (81%), and lack of energy (81%). Three symptom clusters were identified: psychological (56% of the patients), impaired energy (28%), and physical (16%) clusters. Multinomial regression analysis revealed that vitamin D deficiency was significantly associated with the impaired energy cluster (odds ratio=2.49, 95% confidence interval [1.00-6.2], p=0.05).

CONCLUSIONS

We found high symptom prevalence in patients newly diagnosed with inflammatory bowel disease. Three distinct symptom clusters were identified, and the psychological cluster includes >50% of the patients. Vitamin D deficiency is the only factor associated with cluster membership, namely the impaired energy cluster.

An Evaluation of the Multifactorial Model of Cancer-Related Cognitive Impairment

BACKGROUND

Up to 45% of patients report cancer-related cognitive impairment (CRCI). A variety of characteristics are associated with the occurrence and/or severity of CRCI. However, an important gap in knowledge of risk factors for CRCI is the relative contribution of each factor. The multifactorial model of cancer-related cognitive impairment (MMCRCI) is a conceptual model of CRCI that can be used to evaluate the strength of relationships between various factors and CRCI.

OBJECTIVES

The purpose of this study was to use structural regression methods to evaluate the MMCRCI using data from a large sample of outpatients receiving chemotherapy ( n = 1,343). Specifically, the relationships between self-reported CRCI and four MMCRCI concepts (i.e., social determinants of health, patient-specific factors, treatment factors, and co-occurring symptoms) were examined. The goals were to determine how well the four concepts predicted CRCI and determine the relative contribution of each concept to deficits in perceived cognitive function.

METHODS

This study is part of a larger, longitudinal study that evaluated the symptom experience of oncology outpatients receiving chemotherapy. Adult patients were diagnosed with breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding 4 weeks; were scheduled to receive at least two additional cycles of chemotherapy; were able to read, write, and understand English; and gave written informed consent. Self-reported CRCI was assessed using the attentional function index. Available study data were used to define the latent variables.

RESULTS

On average, patients were 57 years of age, college educated, and with a mean Karnofsky Performance Status score of 80. Of the four concepts evaluated, whereas co-occurring symptoms explained the largest amount of variance in CRCI, treatment factors explained the smallest amount of variance. A simultaneous structural regression model that estimated the joint effect of the four exogenous latent variables on the CRCI latent variable was not significant.

DISCUSSION

These findings suggest that testing individual components of the MMCRCI may provide useful information on the relationships among various risk factors, as well as refinements of the model. In terms of risk factors for CRCI, co-occurring symptoms may be more significant than treatment factors, patient-specific factors, and/or social determinants of health in patients receiving chemotherapy.

Epigenetic Regulation of Inflammatory Mechanisms and a Psychological Symptom Cluster in Patients Receiving Chemotherapy

BACKGROUND

A psychological symptom cluster is the most common cluster identified in oncology patients. Although inflammatory mechanisms are hypothesized to underlie this cluster, epigenetic contributions are unknown.

OBJECTIVES

This study's purpose was to evaluate associations between the occurrence of a psychological symptom cluster and levels of DNA methylation for inflammatory genes in a heterogeneous sample of patients with cancer receiving chemotherapy.

METHODS

Prior to their second or third cycle of chemotherapy, 1,071 patients reported the occurrence of 38 symptoms using the Memorial Symptom Assessment Scale. A psychological cluster was identified using exploratory factor analysis. Differential methylation analyses were performed in two independent samples using Illumina Infinium 450K and EPIC microarrays. Expression-associated CpG (eCpG) loci in the promoter region of 114 inflammatory genes on the 450K and 112 genes on the EPIC microarray were evaluated for associations with the psychological cluster. Robust rank aggregation was used to identify differentially methylated genes across both samples. Significance was assessed using a false discovery rate of 0.05 under the Benjamini-Hochberg procedure.

RESULTS

Cluster of differentiation 40 ( CD40 ) was differentially methylated across both samples. All six promoter eCpGs for CD40 that were identified across both samples were hypomethylated in the psychological cluster group.

CONCLUSIONS

This study is the first to suggest associations between a psychological symptom cluster and differential DNA methylation of a gene involved in tissue inflammation and cell-mediated immunity. Our findings suggest that increased CD40 expression through hypomethylation of promoter eCpG loci is involved in the occurrence of a psychological symptom cluster in patients receiving chemotherapy. These findings suggest a direction for mechanistic studies.

Gastrointestinal Symptom Cluster is Associated With Epigenetic Regulation of Lymphotoxin Beta in Oncology Patients Receiving Chemotherapy

OBJECTIVES

While the gastrointestinal symptom cluster (GISC) is common in patients receiving chemotherapy, limited information is available on its underlying mechanism(s). Emerging evidence suggests a role for inflammatory processes through the actions of the nuclear factor kappa B (NF-κB) signaling pathway. This study evaluated for associations between a GISC and levels of DNA methylation for genes within this pathway.

METHODS

Prior to their second or third cycle of chemotherapy, 1071 outpatients reported symptom occurrence using the Memorial Symptom Assessment Scale. A GISC was identified using exploratory factor analysis. Differential methylation analyses were performed in two independent samples using EPIC (n = 925) and 450K (n = 146) microarrays. Trans expression-associated CpG (eCpG) loci for 56 NF-κB signaling pathway genes were evaluated. Loci significance were assessed using an exploratory false discovery rate (FDR) of 25% for the EPIC sample. For the validation assessment using the 450K sample, significance was assessed at an unadjusted p-value of 0.05.

RESULTS

For the EPIC sample, the GISC was associated with increased expression of lymphotoxin beta (LTB) at one differentially methylated trans eCpG locus (cg03171795; FDR = 0.168). This association was not validated in the 450K sample.

CONCLUSIONS

This study is the first to identify an association between a GISC and epigenetic regulation of a gene that is involved in the initiation of gastrointestinal immune responses. Findings suggest that increased LTB expression by hypermethylation of a trans eCpG locus is involved in the occurrence of this cluster in patients receiving chemotherapy. LTB may be a potential therapeutic target for this common cluster.

Identifying participants' preferences for modifiable chemotherapy-induced peripheral neuropathy prevention clinical trial factors: an adaptive choice-based conjoint analysis

PURPOSE

There are no recommended treatments for chemotherapy-induced peripheral neuropathy (CIPN) prevention. Recruitment to CIPN prevention clinical trials is challenging because it is difficult to enroll patients between the time of cancer diagnosis and the initiation of neurotoxic chemotherapy. The purpose of this exploratory-sequential mixed-methods study was to determine patients' preferences that could affect the choice to participate in CIPN prevention clinical trials.

METHODS

First, twenty cognitive interviews were conducted with adults who completed less than three neurotoxic chemotherapy infusions to clarify clinical trial attributes and levels thought to be important to patients when deciding whether to enroll in CIPN prevention trials (i.e., type of treatment, clinical tests, reimbursement, survey delivery; length of visits, timing of follow-up, when to begin treatment). Second, another eighty-eight patients completed an adaptive choice-based conjoint analysis survey that incorporated the finalized attributes and levels. Each level was assigned a part-worth utility score using Hierarchical Bayes Estimation. The relative importance of each attribute was calculated.

RESULTS

The attributes with the highest relative importance values were type of treatment (27.1%) and length of study visits (20.2%). The preferred levels included non-medicine treatment (53.49%), beginning treatment after experiencing CIPN (60.47%), email surveys (63.95%), assessments that include surveys and clinical exams (39.53%), under 30-min visits (44.19%), $50/week reimbursement (39.53%), and 1-month post-chemotherapy follow-up visits (32.56%).

CONCLUSIONS

Patients' preferences for participation may be included in the design of future CIPN prevention clinical trials to potentially bolster study enrollment.

Network analysis to identify symptoms clusters and temporal interconnections in oncology patients

Oncology patients experience numerous co-occurring symptoms during their treatment. The identification of sentinel/core symptoms is a vital prerequisite for therapeutic interventions. In this study, using Network Analysis, we investigated the inter-relationships among 38 common symptoms over time (i.e., a total of six time points over two cycles of chemotherapy) in 987 oncology patients with four different types of cancer (i.e., breast, gastrointestinal, gynaecological, and lung). In addition, we evaluated the associations between and among symptoms and symptoms clusters and examined the strength of these interactions over time. Eight unique symptom clusters were identified within the networks. Findings from this research suggest that changes occur in the relationships and interconnections between and among co-occurring symptoms and symptoms clusters that depend on the time point in the chemotherapy cycle and the type of cancer. The evaluation of the centrality measures provides new insights into the relative importance of individual symptoms within various networks that can be considered as potential targets for symptom management interventions.

Advances in Conceptual and Methodological Issues in Symptom Cluster Research: A 20-Year Perspective

Two conceptual approaches are used to evaluate symptom clusters: "clustering" symptoms (ie, variable-centered analytic approach) and "clustering" patients (ie, person-centered analytic approach). However, these methods are not used consistently and conceptual clarity is needed. Given the emergence of novel methods to evaluate symptom clusters, a review of the conceptual basis for older and newer analytic methods is warranted. Therefore, this article will review the conceptual basis for symptom cluster research; compare and contrast the conceptual basis for using variable-centered versus patient-centered analytic approaches in symptom cluster research; review their strengths and weaknesses; and compare their applications in symptom cluster research.

Cancer symptom clusters in adult patients undergoing chemotherapy: A systematic review and meta-analysis protocol

BACKGROUND

In oncology, the prevalence of symptoms is preferentially analyzed in isolation instead of being considered in clusters. However, clinical practice shows that symptoms rarely occur separately but rather form clusters that share common underlying mechanisms in terms of intensity and severity, creating a synergistic effect among them, which can even help predict the development of future symptoms.

OBJECTIVE

To identify and gather evidence on the prevalence, composition, severity, and predictors of cancer symptom clusters in adult cancer patients undergoing chemotherapy.

METHODS

This systematic review and meta-analysis protocol was developed in compliance with PRISMA-P. Observational and experimental study designs will be included. MEDLINE/PubMed, Cochrane Library, Embase, CINAHL, PsycINFO, Web of Science, Scopus, LILACS, clinical trials.gov-NIH, the British Library, Google Scholar, and preprints [medRXiv] will be searched with no restrictions on idioms, dates, or settings. Two investigators will independently select the studies, perform data extraction, and critically appraise the risk of bias of the included studies. Heterogeneity among the studies will be assessed using the I2 statistic. If meta-analysis was feasible, a random-effect model analysis will be carried out. For data analysis, the pooled effect will be estimated considering 95% confidence interval and α = 5%. In addition, the certainty of evidence will be rated based on Cochrane methods in accordance with the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE).

DISCUSSION

To the best of our knowledge, this systematic review and meta-analysis will be the first to identify and critically assess evidence regarding the prevalence, composition, severity, and predictors of cancer symptom clusters in adult cancer patients undergoing chemotherapy. We intend to provide health professionals with subsidies to reflect on a better understanding of symptom clusters in adult cancer patients, with the aim of contributing to the development of evidence-based therapeutic interventions and success in clinical practice.

PROSPERO REGISTRATION NUMBER

CRD42021248406.

Symptom clusters change over time among patients with gynecological cancer receiving chemotherapy

PURPOSE

This study aimed to explore symptom clusters at different time points among patients with gynecological cancer undergoing chemotherapy.

METHODS

A longitudinal design was used to explore the patterns of symptom clusters four times: during prechemotherapy (T0), first (T1), second (T2), and third (T3) cycles of chemotherapy. The Memorial Symptom Assessment Scale was used to assess the dimension of symptoms. The study was conducted in Indonesia. Exploratory factor analysis was used to analyze the structures of symptom clusters across time.

RESULTS

A total of 120 subjects provided baseline data, and 82 were retained at T3. Before chemotherapy, the most prevalent symptoms were pain and difficulty in sleeping. However, after starting chemotherapy, the patients suffered from chemotherapy-related side effects, including nausea, change in taste, lack of appetite, hair loss, fatigue, and feeling of "I don't look like myself." Six symptom clusters were identified in patients with gynecological cancer across four time points during chemotherapy: pain-related, nutritional, emotional, hormonal-related, fatigue-related, and body-image symptom clusters. Nutrition and emotion symptom clusters occurred consistently from T0 to T3, fatigue-related clusters appeared after chemotherapy at T1 and T2, and body-image symptom clusters emerged at late T2 and T3.

CONCLUSION

The structures of symptom clusters in this study were dynamic and various. The nutrition and emotional-related symptoms constituted a cluster during chemotherapy. Oncology nurses should provide physical and psychosocial interventions to relieve these symptoms in patients with gynecological cancer undergoing chemotherapy.

Symptom clusters in outpatients with cancer using different dimensions of the symptom experience

PURPOSE

Relatively few studies have evaluated for symptom clusters across multiple dimensions. It is unknown whether the symptom dimension used to create symptom clusters influences the number and types of clusters that are identified. Study purposes were to describe ratings of occurrence, severity, and distress for 38 symptoms in a heterogeneous sample of oncology patients (n = 1329) undergoing chemotherapy; identify and compare the number and types of symptom clusters based on three dimensions (i.e., occurrence, severity, and distress); and identify common and distinct clusters.

METHODS

A modified version of the Memorial Symptom Assessment Scale was used to assess the occurrence, severity, and distress ratings of 38 symptoms in the week prior to patients' next cycle of chemotherapy. Symptom clusters for each dimension were identified using exploratory factor analysis.

RESULTS

Patients reported an average of 13.9 (±7.2) concurrent symptoms. Lack of energy was both the most common and severe symptom while "I don't look like myself" was the most distressing. Psychological, gastrointestinal, weight gain, respiratory, and hormonal clusters were identified across all three dimensions. Findings suggest that psychological, gastrointestinal, and weight gain clusters are common while respiratory and hormonal clusters are distinct.

CONCLUSIONS

Psychological, gastrointestinal, weight gain, hormonal, and respiratory clusters are stable across occurrence, severity, and distress in oncology patients receiving chemotherapy. Given the stability of these clusters and the consistency of the symptoms across dimensions, the use of a single dimension to identify these clusters may be sufficient. However, comprehensive and disease-specific inventories need to be used to identify distinct clusters.

Holistic Needs Assessment of Cancer Survivors-Supporting the Process Through Digital Monitoring of Circadian Physiology

The year 2022 could represent a significant juncture in the incorporation of mHealth solutions in routine cancer care. With the recent global COVID-19 pandemic leading a surge in both observation- and intervention-based studies predominantly aimed at remote monitoring there has been huge intellectual investment in developing platforms able to provide real time analytics that are readily usable. Another fallout from the pandemic has seen record waiting times and delayed access to cancer therapies leading to exhausting pressures on global healthcare providers. It seems an opportune time to utilize this boom in platforms to offer more efficient “at home” clinical assessments and less “in department” time for patients. Here, we will focus specifically on the role of digital tools around cancer survivorship, a relevant aspect of the cancer journey, particularly benefiting from integrative approaches. Within that context a further concept will be introduced and that is of the likely upsurge in circadian-based interpretation of continuous monitoring and the engendered therapeutic modifications. Chronobiology across the 24-hour span has long been understood to control key bodily aspects and circadian dysregulation plays a significant role in the risk of cancer and also the response to therapy and therefore progressive outcome. The rapid improvement in minimally invasive monitoring devices is, in the opinion of the authors, likely to advance introducing chronobiological amendments to routine clinical practices with positive impact on cancer survivors.