Symptom Clusters in Patients With Gynecologic Cancer Receiving Chemotherapy

Decrements in Morning and Evening Energy Are Associated With a Higher Symptom Burden in Patients With Gynecologic Cancers Receiving Chemotherapy

BACKGROUND

Decrements in energy are a significant problem associated with chemotherapy. To date, no study examined the variability of energy in patients with gynecologic cancers.

OBJECTIVE

To identify distinct morning and evening energy profiles in patients with gynecologic cancers and evaluate for differences in demographic and clinical characteristics, other common symptoms, and quality-of-life (QOL) outcomes.

METHODS

A sample of 232 patients with gynecologic cancers completed questionnaires 6 times over 2 cycles of chemotherapy. Latent profile analysis was used to identify distinct morning and evening energy profiles. Differences in demographic and clinical characteristics, other common symptoms, and QOL outcomes were evaluated using parametric and nonparametric tests.

RESULTS

Three distinct morning (ie, high [9.2%], low [63.1%], very low [27.1%]) and 2 distinct evening (moderate [30.6%], very low [69.4%]) energy classes were identified. Clinical risk factors associated with the worst morning energy profiles included lower functional status and a higher comorbidity burden. Less likely to exercise on a regular basis was the only characteristic associated with the worst evening energy profile. For both symptoms, the worst profiles were associated with higher levels of depression and sleep disturbance, lower levels of cognitive function, and poorer QOL.

CONCLUSIONS

Approximately 70% of patients with gynecologic cancers experienced decrements in morning and evening energy. The study identified modifiable risk factors associated with more decrements in morning and evening energy.

IMPLICATIONS FOR PRACTICE

Clinicians can use these findings to identify higher-risk patients and develop individualized energy conservation interventions for these vulnerable patients.

Nonpharmacological Interventions for Managing Symptom Clusters in Adults: A Systematic Review

Objectives: The complex effects of multiple co-occurring symptoms are a major cause of reduced quality of life; thus, it is necessary to identify symptom clusters experienced by patients and explore interventions. This study aimed to provide an overview of non-pharmacological interventions based on symptom clusters in adults to identify effective intervention strategies and methods. Methods. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. For the search databases, PubMed, Embase, Cochrane Library, CINAHL, RISS, KISS, and KISTI were used. It includes English and Korean experimental studies published up to May 2023. The literature quality was evaluated using the Joanna Briggs Institute Quality Assessment Tool. Results. Of the 18 studies selected, 15 were randomized controlled trials and three were quasi-experimental studies, all of which were conducted on patients with cancer. The symptom clusters-based interventions in the literature are classified as movement-based, relaxation-based, integrated, and miscellaneous interventions. Integrated interventions, which were effective in all studies, might prove to be very effective for managing symptom clusters. Movement-based intervention studies, which include dance, Qigong, and Tai Chi, might be very effective in improving health-related quality of life (HRQoL). Conclusions. This review demonstrates that non-pharmacological interventions reduce the occurrence and severity of symptom clusters, thereby improving HRQoL. Further studies are required to evaluate the effects of these interventions in patients with various chronic conditions other than 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.

Psychometric validation of the Functional Assessment of Cancer Therapy-Endometrial among endometrial cancer patients

OBJECTIVE

To evaluate a psychometric validation of the endometrial cancer subscales (EnCS) in the Functional Assessment of Cancer Therapy-Endometrial (FACT-EN) among patients with endometrial cancer.

METHODS

This cross-sectional study was conducted at a tertiary university-based hospital in South Korea between April and October 2022. Participants completed a survey questionnaire that included the FACT-EN. Exploratory and confirmatory factor analyses (EFA, CFA) and the reliability were measured using the intraclass correlation coefficient (ICC) under a two-way mixed model. Pearson's correlations were used to evaluate the validity. We also tested known-group validity.

RESULTS

In total, 240 patients with endometrial cancer participated in the survey. In EFA, we found EnCS included four domains. In CFA, four-factor solution model was good: CFI = 0.659; SRMR = 0.066, and RMSEA = 0.073. The mean (SD) of total score of FACT-EN was 122.84 (23.58). The floor and ceiling effects were 0.4% and 0.4%, respectively. Cronbach's α coefficients for the five scales of the EnCS ranged from 0.78 to 0.91. The ICC of EnCS was 0.76. The convergent and discriminant validity of EnCS was acceptable. In the group analysis, older age and lower ECOG performance scores were associated with higher EnCS scores. The stomach and vaginal domains in EnCS were higher in patients who had completed treatment for more than 1 year compared to those who were still undergoing treatment.

CONCLUSIONS

FACT-EN has demonstrated its validity as an assessment tool with significant implications for capturing various symptoms in patients with endometrial cancer.

Stability and consistency of symptom clusters in younger versus older patients receiving chemotherapy

BACKGROUND

By 2035, the number of newly diagnosed cancer cases will double and over 50% will be in older adults. Given this rapidly growing demographic, a need exists to understand how age influences oncology patients' symptom burden. The study purposes were to evaluate for differences in the occurrence, severity, and distress of 38 symptoms in younger (< 60 years) versus older (≥ 60 years) oncology patients undergoing chemotherapy and to evaluate for differences in the stability and consistency of symptom clusters across the two age groups.

METHODS

A total of 1329 patients were dichotomized into the younger and older groups. Patients completed demographic and clinical questionnaires prior to the initiation of their second or third cycle of chemotherapy. A modified version of Memorial Symptom Assessment Scale was used to evaluate the occurrence, severity, and distress of 38 common symptoms associated with cancer and its treatment. Differences between the two age groups in demographic and clinical characteristics and ratings of occurrence, severity, and distress for the 38 symptoms were evaluated using parametric and nonparametric tests. Exploratory factor analyses were done within each age group to identify symptom clusters using symptom occurrence rates.

RESULTS

Compared to the younger group (14.8 (± 7.0)), older adults reported a lower mean number of symptoms (12.9 (± 7.2)). Older patients experienced lower occurrence rates for almost 50% of the symptoms. Regarding symptom clusters, an eight-factor solution was selected for both age groups. Across the two age groups, the eight symptom clusters (i.e., physical and cognitive fatigue, respiratory, psychological, hormonal, chemotherapy-related toxicity, weight gain, gastrointestinal, epithelial) were stable. However, symptoms within the physical and cognitive, chemotherapy-related toxicity, and gastrointestinal clusters were not consistent across the age groups.

CONCLUSIONS

To be able to provide tailored and effective symptom management interventions to older oncology patients, routine assessments of the core symptoms unique to the symptom clusters identified for this group warrants consideration. The underlying mechanism(s) for these inconsistencies in symptom burden is an important focus for future studies.

Systematic Review of the Literature on Multiple Co-occurring Symptoms in Patients Receiving Treatment for Gynecologic Cancers

OBJECTIVE

Patients with gynecologic cancers experience a very high symptom burden that has a negative impact on their quality of life. This systematic review aims to identify the common co-occurring symptoms, the prevalence of common symptoms, common instruments used to measure symptoms, associated risk factors, and the symptom burden in patients with gynecologic cancers.

DATA SOURCES

A search of four databases (ie, PubMed, Embase, Web of Science, and CINAHL) was done from January 1, 2012, through September 5, 2022. A qualitative synthesis of the extant literature was performed using Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (PRISMA 2020).

CONCLUSION

A total of 118 studies met the prespecified inclusion criteria. Ninety-six symptoms were assessed across these studies. The top six symptoms and their grand mean prevalence rates were lack of energy (64.4%), fatigue (62.1%), abdominal pain (53.3%), depression (52.6%), concentration dysfunction (52.0%), and drowsiness (51.9%). Numerous methodologic challenges were evident across studies. Future research needs to develop a disease-specific symptom assessment measure, evaluate for risk factors associated with a higher symptom burden, and determine the impact of multiple symptoms on patient outcomes.

IMPLICATION FOR NURSING PRACTICE

The results are relevant for oncology clinicians to assess patients with gynecologic cancers for the presence of common symptoms and risk factors for higher symptom burden in the patients and to offer effective management interventions.

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 breast cancer survivors with and without type 2 diabetes over the cancer trajectory

Objective

This study aimed to investigate symptoms and symptom clusters in breast cancer survivors (BCS) with and without type 2 diabetes across three crucial periods during the cancer trajectory (0-6 months, 12-18 months, and 24-30 months) post-initial chemotherapy.

Methods

Eight common symptoms in both BCS and individuals with diabetes were identified through natural language processing of electronic health records from January 2007 to December 2018. Exploratory factor analysis was employed to discern symptom clusters, evaluating their stability, consistency, and clinical relevance.

Results

Among the 4601 BCS in the study, 20% (n = 905) had a diabetes diagnosis. Gastrointestinal symptoms and fatigue were prevalent in both groups. While BCS in both groups exhibited an equal number of clusters, the composition of these clusters differed. Symptom clusters varied over time between BCS with and without diabetes. BCS with diabetes demonstrated less stability (repeated clusters) and consistency (same individual symptoms comprising clusters) than their counterparts without diabetes. This suggests that BCS with diabetes may experience distinct symptom clusters at pivotal points in the cancer treatment trajectory.

Conclusions

Healthcare providers must be attentive to BCS with diabetes throughout the cancer trajectory, considering intensified and/or unique profiles of symptoms and symptom clusters. Interdisciplinary cancer survivorship models are essential for effective diabetes management in BCS. Implementing a comprehensive diabetes management program throughout the cancer trajectory could alleviate symptoms and symptom clusters, ultimately enhancing health outcomes and potentially reducing healthcare resource utilization.

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.

Relationship between illness perception and family resilience in gynecologic cancer patients: the mediating role of couple illness communication

OBJECTIVE

To analyze the current family resilience levels of Chinese patients with gynecologic cancer and explore the mediating role of couple illness communication between illness perception and family resilience to facilitate patient adaptation to cancer.

METHODS

A total of 310 patients with gynecologic cancer were selected from the gynecology ward of a tertiary care hospital in Jinan, Shandong Province, China. All participants provided their demographic and clinical information and completed the Brief Illness Perception Questionnaire (BIPQ), Couples' Illness Communication Scale (CICS), and Family Hardiness Index (FHI). The mediating effect of couple illness communication was analyzed using SPSS26.0 and Amos21.0.

RESULTS

The family resilience score of patients with gynecologic cancer was moderate (55.78 ± 8.65). Illness perception was negatively correlated with couple illness communication(p < 0.05) and family resilience(p < 0.01), while couple illness communication was positively correlated with family resilience (p < 0.01). Couple illness communication mediated the relationship between illness perception and family resilience [β = - 0.071; 95% confidence interval: (- 0.127)-(- 0.013)].

CONCLUSIONS

The family resilience of patients with gynecologic cancer must be further improved. Since couple illness communication mediates the relationship between illness perception and family resilience in this population, it is important to improve patients' illness perceptions and couple illness communication to enhance their family resilience.

Age-related differences in the occurrence, severity, and distress of symptoms in older patients at the initiation of chemotherapy

BACKGROUND

Evaluate for differences in occurrence, severity, and distress ratings for 32 symptoms between younger older adults (YOA, < 70 years) and older adults (OA, ≥ 70 years) at initiation of chemotherapy.

METHODS

Patients (n = 125) were recruited prior to the initiation of chemotherapy and completed the Memorial Symptom Assessment Scale. Differences in occurrence, severity, and distress ratings were evaluated using Independent sample t-tests and Chi-square or Fisher's exact tests.

RESULTS

On average, the older patients reported ten concurrent symptoms that equates with a moderate symptom burden. Symptoms with the highest occurrence rates were not always the most severe and/or the most distressing. Few age-related differences were found in patients' symptom experiences. When age-related differences were identified, OA reported lower occurrence, severity, and distress ratings. Nine of the ten symptoms with highest occurrence rates were common for both age groups. For severity and distress, only half of the symptoms were common. In terms of severity and distress, all of the top ten ranked symptoms were in the moderate to severe range.

CONCLUSIONS

Both YOA and OA reported a moderate symptom burden and severity and distress scores in the moderate to severe range. The symptoms with the highest occurrence rates were not always the most severe/or the most distressing. Our findings suggest that different dimensions of the symptom experience (i.e., occurrence, severity, and distress) warrant evaluation in older oncology patients.

Development and validation of the scale for symptom clusters in patients with myasthenia gravis

BACKGROUND

Patients with myasthenia gravis(MG)often experience multiple symptoms concurrently, which can have an adverse effect on their quality of life(QOL). However, a specific, systemic and reliable scale for symptom clusters in MG is lacking.

AIMS

To develop reliable assessment scale for symptom clusters in patients with MG.

DESIGN

A cross-sectional descriptive study.

METHODS

Based on the unpleasant symptom theory(TOUS), the first draft of the scale was developed through review literature, qualitative interview, and Delphi expert correspondence, the items of the scale were presented and adjusted through cognitive interviews with 12 patients. To conveniently assess the validity and reliability of the scale, a cross-sectional survey was conducted in 283 patients with MG who were recruited from Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, from June to September 2021.

RESULTS

The final symptom cluster scale for patients with MG consisted of 19 items(MGSC-19), with a content validity index ranging from 0.828 to 1.000 for each item and the content validity index was 0.980. Four common variables (ocular muscle weakness, general muscular weakness, treatment-related side effects, and psychiatric problems) were identified by exploratory factor analysis, which explained 70.187% of the total variance. The correlation coefficients between the scale dimension and the overall score ranged from 0.395 to 0.769 (all P < 0.01), while the correlation coefficients between dimensions varied from 0.324 to 0.510 (all P < 0.01). The Cronbach's alpha, retest reliability, and half reliability were 0.932, 0.845, and 0.837, respectively.

CONCLUSION

The validity and reliability of MGSC-19 were generally good. This scale can be employed to identify the symptom clusters to help healthcare givers develop individualized symptom management measures for patients with MG.

Symptom distress and suicidal ideation among Chinese ovarian cancer patients: A moderated mediation model of depression and suicide resilience

Objective

The aim of this study was to examine whether depression mediates the relationship between symptom distress and suicidal ideation in Chinese patients with ovarian cancer, and whether this mediating effect was moderated by suicide resilience.

Methods

From March to October 2022, this cross-sectional study was performed in a three Grade 3A hospital and an oncology specialty hospital in Wuhan, Hubei Province, China. Ultimately, 213 ovarian cancer patients completed anonymous self-report. Bootstrapping method was used for regression analysis to test the mediating and moderating effects.

Results

Among the 213 participants, 29.58% (n = 63) exhibited significant suicidal ideation. Symptom distress was positively associated with suicidal ideation, and depression partially mediated this relationship. Suicide resilience moderated the relationship between depression and suicidal ideation. In ovarian cancer patients with low suicide resilience, the effect of symptom distress on suicidal ideation through depression was greater, while in patients with high suicide resilience, this effect was attenuated.

Conclusion

Our study suggests that symptom distress could be more likely to lead to suicidal ideation as depression levels increase in ovarian cancer patients. Fortunately, suicide resilience could attenuate this negative effect.

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.

Informatics and data science perspective on Future of Nursing 2020-2030: Charting a pathway to health equity

The Future of Nursing 2020 to 2030 report explicitly addresses the need for integration of nursing expertise in designing, generating, analyzing, and applying data to support initiatives focused on social determinants of health (SDOH) and health equity. The metrics necessary to enable and evaluate progress on all recommendations require harnessing existing data sources and developing new ones, as well as transforming and integrating data into information systems to facilitate communication, information sharing, and decision making among the key stakeholders. We examine the recommendations of the 2021 report through an interdisciplinary lens that integrates nursing, biomedical informatics, and data science by addressing three critical questions: (a) what data are needed?, (b) what infrastructure and processes are needed to transform data into information?, and (c) what information systems are needed to "level up" nurse-led interventions from the micro-level to the meso- and macro-levels to address social determinants of health and advance health equity?

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.

Symptom clusters in patients receiving chemotherapy: A systematic review

BACKGROUND AND PURPOSE

Since 2001, symptom cluster research has grown considerably. However, because multiple methodological considerations remain, ongoing synthesis of the literature is needed to identify gaps in this area of symptom science. This systematic review evaluated the progress in symptom clusters research in adults receiving primary or adjuvant chemotherapy since 2016.

METHODS

Eligible studies were published in English between 1 January 2017 and 17 May 2021; evaluated for and identified symptom clusters 'de novo;' and included only adults being treated with primary or adjuvant chemotherapy. Studies were excluded if patients had advanced cancer or were receiving palliative chemotherapy; symptoms were measured after treatment; symptom clusters were pre-specified or a patient-centred analytic approach was used. For each study, symptom instrument(s); statistical methods and symptom dimension(s) used to create the clusters; whether symptoms were allowed to load on more than one factor; method used to assess for stability of symptom clusters and associations with secondary outcomes and biomarkers were extracted.

RESULTS

Twenty-three studies were included. Memorial Symptom Assessment Scale was the most common instrument and exploratory factor analysis was the most common statistical method used to identify symptom clusters. Psychological, gastrointestinal, and nutritional clusters were the most commonly identified clusters. Only the psychological cluster remained relatively stable over time. Only five studies evaluated for secondary outcomes.

DISCUSSION

While symptom cluster research has evolved, clear criteria to evaluate the stability of symptom clusters and standardised nomenclature for naming clusters are needed. Additional research is needed to evaluate the biological mechanism(s) for symptom clusters.

PROSPERO REGISTRATION NUMBER

CRD42021240216.

Distinct sleep disturbance profiles among patients with gynecologic cancer receiving chemotherapy

OBJECTIVE

In a sample of patients with gynecologic cancer receiving chemotherapy, we sought to identify subgroups of patients with distinct sleep disturbance profiles and assess for differences in patient characteristics and the severity of co-occurring symptoms among these subgroups.

METHODS

Adults with gynecologic cancer (n = 232) completed questionnaires six times over two chemotherapy cycles. Sleep disturbance was assessed using the General Sleep Disturbance Scale (GSDS). Clinically meaningful sleep disturbance was defined as a GSDS total score of ≥43. Subgroups of patients with distinct sleep disturbance profiles were identified using latent profile analysis. Differences in patient characteristics and co-occurring symptoms were assessed using Chi-square, Kruskal Wallis, and one-way analysis of variance.

RESULTS

Four distinct sleep disturbance profiles were identified: Low (18.5%), Moderate (43.6%), High (29.3%), and Very High (8.6%). Compared to the Low class, patients in the other three classes had lower functional status scores and higher levels of depressive symptoms, trait anxiety, and morning and evening fatigue. Compared to the Low class, patients in the Very High class were younger, had a higher body mass index, and were more likely to report a diagnosis of depression or back pain.

CONCLUSIONS

Over 80% of the patients with gynecologic cancer reported sleep disturbance that persisted over two cycles of chemotherapy. Patients in the Very High class experienced problems with both sleep initiation and maintenance. Clinicians should routinely assess sleep disturbance alongside depression, anxiety, and fatigue. Interventions that target the underlying mechanisms of these co-occurring symptoms are warranted.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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