Roles of biological and psychosocial factors in experiencing a psychoneurological symptom cluster in cancer patients

Identification of distinct symptom profiles in prostate cancer patients with cancer-related cognitive impairment undergoing androgen deprivation therapy: A latent class analysis

Objective

To identify latent classes of cognitive impairment and co-occurring symptoms (fatigue, pain, sleep disturbance, depression) as clusters in patients with prostate cancer undergoing androgen deprivation therapy and to explore the predictors among distinct latent classes.

Methods

A total of 228 patients with prostate cancer were recruited in this cross-sectional study. The assessment instrument included the Perceived Cognitive Impairment Scale, the Fatigue Severity Scale, the Athens Insomnia Scale, the Brief Pain Inventory, the Patient Health Questionnaire-9, the UCLA Loneliness Scale, the International Physical Activity Questionnaire - Short Form, the Charlson comorbidity index, and General Information questionnaire. The identification of different patient subgroups was done by the latent class analysis.

Results

The study identified three distinct latent classes: all low symptoms (class 1, 32%), high depression symptoms (class 2, 37.7%), and high physical symptoms (fatigue, sleep disturbance, and pain) with high cognitive impairment (class 3, 30.3%). Patients who had higher Charlson comorbidity index (P = 0.003) scores were more likely to be classified in class 3. Patients with higher loneliness scores (P < 0.001; P < 0.001) were significantly more likely to fall into class two or three than in class 1. However, having a higher level of physical activity (P = 0.014; P < 0.001) increased the likelihood of being in class 1.

Conclusions

This study exhibited the inter-individual variability of symptom experience in prostate cancer patients with cognitive impairment undergoing androgen deprivation therapy. The result suggests that more emphasis should be placed on screening for fatigue, sleep disturbance, and pain, and future interventions should focus on loneliness and physical activity.

Differential Characteristics of Fatigue-Pain-Sleep Disturbance-Depression Symptom Cluster and Influencing Factors of Patients With Advanced Cancer During Treatment: A Latent Class Analysis

BACKGROUND

Patients with advanced cancer may experience symptom clusters during treatment (eg, fatigue, pain, sleep disturbance, depression). Understanding the characteristics and factors associated with symptom cluster classes among this patient population is essential for effective symptom management.

OBJECTIVE

The aims of this study were to identify symptom cluster (fatigue-pain-sleep disturbance-depression) classes and explore influencing factors in patients with advanced cancer during the treatment.

METHODS

A cross-sectional survey was conducted in an oncology department of a tertiary hospital in China from September 2020 to March 2021. Cancer patients (stage III/IV) 18 years or older completed the questionnaires on pain, fatigue, sleep disturbance, depression, physical activity, and exercise self-efficacy. Latent class analysis and multinomial logistic regression were used.

RESULTS

Three hundred sixty-five patients who were male (65.2%) and younger than 60 years (59.5%) completed questionnaires. Three symptom cluster classes were identified: class 1 ("low symptom burden" class), class 2 ("fatigue-insomnia" class), and class 3 ("high symptom burden" class), with a percentage of 54.5%, 38.6%, and 6.8%, respectively. The quality-of-life score, introversion/extroversion, economic burden, Karnofsky Performance Status, albumin level, and exercise self-efficacy were significantly different among the 3 classes (P < .05).

CONCLUSION

Patients with advanced cancer were classified into 3 distinct classes, with class 1 having the best function. Results from this study reveal that Karnofsky Performance Status, albumin level, and exercise self-efficacy were significant factors for the latent classes of symptom cluster.

IMPLICATIONS FOR PRACTICE

Exercise self-efficacy is important for personalized interventions and improving symptom management efficiency.

Evaluation of a psychoneurological symptom cluster in patients with breast or digestive cancer: a longitudinal observational study

BACKGROUND

A psychoneurological symptom cluster composed of cancer-related fatigue, emotional distress, sleep difficulties, and pain is very common among patients with cancer. Cognitive difficulties are also frequently associated with this cluster. Network analyses allow for an in-depth understanding of the relationships between symptoms in a cluster. This paper details the study protocol of a longitudinal assessment of the psychoneurological symptom cluster in two distinct cohorts: breast cancer and digestive cancer survivors, using network analyses.

METHODS

Over two years, the symptoms involved in the psychoneurological symptom cluster, along with other common symptoms (e.g., digestive symptoms, financial difficulties) and variables (i.e., self-compassion, coping strategies) will be assessed in two cohorts: breast cancer survivors (N = 240) and digestive cancer survivors (N = 240). Online questionnaires will be completed at baseline, then 6, 12 and 24 months later. Network analyses will be used to assess the configuration of the symptom cluster at each measurement time and in each cohort. Comparison of networks between two measurement times or between the two cohorts will also be done with network comparison tests.

DISCUSSION

This study will enable a better understanding of the relationships between common symptoms endured by patients with cancer. The results will be employed to develop more cost-effective interventions which, ultimately, will significantly improve the quality of life of patients with breast or digestive cancer.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT05867966). Registered on the 27th of April 2023. url: https://classic.

CLINICALTRIALS

gov/ct2/show/NCT05867966 .

The role of cytokines and Indolamine-2.3 dioxygenase in experiencing a psycho-neurological symptom cluster in hematological cancer patients: IL-1alpha, IL-1beta, IL-4, IL-6, TNF-alpha, kynurenine, and tryptophan

OBJECTIVE

This study examined (a) whether there are a subgroup of cancer patients experiencing the selected psycho-neurological symptoms as a cluster (depression, cognitive impairment, fatigue, sleep disturbance, and pain); (b) whether demographic and clinical characteristics and pro-inflammatory cytokines (IL-1α, IL-1β, IL-4, IL-6, TNF-alpha) are associated with subgroup membership; and (c) whether the activity of indolamine-2.3 dioxygenase(IDO) is associated with pro-inflammatory cytokine activity and psycho-neurological symptom cluster experience.

METHODS

This was a prospective cohort study where 149 hematologic patients were recruited from a university hospital and 65 healthy volunteers provided control data. Latent profile analyses were conducted to identify subgroups at two time points: the last day of chemotherapy and 1 week after chemotherapy completion. Influencing factors of subgroup membership were examined by logistic regression.

RESULTS

A substantial number of patients (33%, 34% at each time point) experienced the selected psycho-neurological symptoms as a cluster. Older age and elevated IL-1α and IL-6 were associated with experiencing the psycho-neurological symptom cluster. IDO activity was higher in the patients experiencing psycho-neurological symptom cluster; and was positively associated with IL-6. Symptom severity, IL-1α, IL-6, and IDO activity were all significantly higher in cancer patients than in the healthy controls. The findings were preserved across time points.

CONCLUSIONS

The activation of pro-inflammatory cytokines and their cross-talk with IDO may be a common biological mechanism, underlying a psycho-neurological symptom cluster experience. The novel approaches for symptom assessment and management can be developed by assessing multiple psycho-neurological symptoms as a cluster and by targeting their common biological pathway.

Latent class symptom profiles of colorectal cancer survivors with cancer-related cognitive impairment

PURPOSE

Colorectal cancer (CRC) survivors experience cancer-related cognitive impairment and co-occurring symptoms after cancer treatments. There has been little data to inform the risk factors of complex symptom phenotypes in CRC survivors.

OBJECTIVES

To determine if subgroups of CRC survivors after cancer treatments could be identified based on the cognitive impairment and common co-occurring symptoms (depression, anxiety, sleep disturbance, fatigue, and pain); and to explore risk factors (sociodemographic and clinical characteristics, perceived stress, and social support) of these subgroups.

METHODS

Latent class profile analysis (LCPA) was used to identify subgroups based on self-reported symptoms in 64 CRC survivors. Cognitive impairment was measured by assessing subjective cognitive function using the Patient-Reported Outcome Measurement Information System (PROMIS) measure. The Kruskal-Wallis test and regression analyses were performed.

RESULTS

Three distinct latent classes were identified (Class 1: All Low '28.1%'; Class 2: High Psychological Symptoms (depression/anxiety) '25%'; Class 3: High Somatic Symptoms (fatigue, sleep disturbance, and pain) with High Cognitive Impairment'46.9%'). The pain was the most distinguishable symptom across the latent classes. The high symptom burden group was associated with less time since cancer diagnosis, higher perceived stress levels, and poor emotional social support.

CONCLUSION

Our study adds to the information on interindividual variability in symptom experience of CRC survivors with cognitive impairment. Findings suggest a need for increased attention to screening for co-occurring symptoms (e.g., high pain) and future interventions focused on stress management and social support.

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

Purpose

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

Methods

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

Results

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

Conclusions

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

Distinct Worst Pain Profiles in Oncology Outpatients Undergoing Chemotherapy

BACKGROUND

While pain is a significant problem for oncology patients, little is known about interindividual variability in pain characteristics.

OBJECTIVE

The aims of this study were to identify subgroups of patients with distinct worst pain severity profiles and evaluate for differences among these subgroups in demographic, clinical, and pain characteristics and stress and symptom scores.

METHODS

Patients (n = 934) completed questionnaires 6 times over 2 chemotherapy cycles. Worst pain intensity was assessed using a 0- to 10-point numeric rating scale. Brief Pain Inventory was used to assess various pain characteristics. Latent profile analysis was used to identify subgroups of patients with distinct pain profiles.

RESULTS

Three worst pain profiles were identified (low [17.5%], moderate [39.9%], severe [42.6%]). Compared with the other 2 classes, severe class was more likely to be single and unemployed and had a lower annual household income, a higher body mass index, a higher level of comorbidity, and a poorer functional status. Severe class was more likely to have both cancer and noncancer pain, a higher number of pain locations, higher frequency and duration of pain, worse pain quality scores, and higher pain interference scores. Compared with the other 2 classes, severe class reported lower satisfaction with pain management and higher global, disease-specific, and cumulative life stress, as well as higher anxiety, depression, fatigue, sleep disturbance, and cognitive dysfunction scores.

CONCLUSIONS

Unrelieved pain is a significant problem for more than 80% of outpatients.

IMPLICATIONS FOR PRACTICE

Clinicians need to perform comprehensive pain assessments; prescribe pharmacologic and nonpharmacologic interventions; and initiate referrals for pain management and psychological services.

Predictors of psychoneurological symptoms in cancer caregivers over time: Role of caregiving burden, stress, and patient symptoms

PURPOSE

In cancer patients, stress is associated with a psychoneurologic (PN) symptom cluster of depressed mood, anxiety, pain, fatigue, and sleep disturbance. The stress of caregiving may trigger similar symptoms among caregivers and warrants investigation. The purpose of this analysis was to characterize correlates of PN symptom burden in cancer caregivers.

METHODS

Cancer patient-caregiver dyads (n = 29) provided eight weekly symptom reports using a web-based survey. Primary and secondary stressors of caregiving were also assessed. Mixed models accounting for repeated measurement were used to assess the between- and within-dyad predictors of caregiver PN symptom burden. The interaction of patient PN symptom burden and stress was tested. Exploratory cross-lagged Actor-Partner Interdependence Models were used to assess the week-to-week interdependence between patient and caregiver symptoms.

RESULTS

Caregivers most frequently reported feeling anxious (44% on average across timepoints), sleep problems (31%), fatigue (25%), and depressed mood (24%). Mixed models indicated that within dyads, greater hours of care and more patient symptoms were associated with greater caregiver PN symptom burden. Greater baseline perceived stress was also associated with higher caregiver PN symptom burden and moderated the association between patient and caregiver PN symptom burden. Cross-lagged Actor-Partner Interdependence Models indicated longitudinal interdependence among survivor and caregiver symptom burden.

CONCLUSIONS

The findings provide preliminary evidence of the interrelationship of PN symptom burden in caregivers and patients and the potential for stress to amplify this interrelationship, with implications for symptom management and supportive care practice.

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

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

Moving beyond Table 1: A critical review of the literature addressing social determinants of health in chronic condition symptom cluster research

Variability in the symptom experience in patients diagnosed with chronic conditions may be related to social determinants of health (SDoH). The purpose of this critical review was to (1) summarize the existing literature on SDoH and symptom clusters (i.e., multiple, co-occurring symptoms) in patients diagnosed with common chronic conditions, (2) evaluate current variables and measures used to represent SDoH, (3) identify gaps in the evidence base, and (4) provide recommendations for the incorporation of SDoH into future symptom cluster research. We identified 118 articles including information on SDoH in chronic condition symptom cluster research. Articles primarily focused on cancer populations. Few articles had the explicit purpose of investigating relationships between SDoH and symptom clusters, and the inclusion of SDoH was often limited to variables used to describe samples. Future studies should be designed to "move beyond Table 1" in their utilization of SDoH as variables and examine relationships between SDoH and symptom clusters. Attention should be paid to the appropriateness of measures being used to collect information on SDoH, and analysis methods that estimate causal connections between variables should be considered. Research regarding the relationship of SDoH with symptom clusters in patients with chronic conditions has the potential to reveal mechanisms of symptom disparities and guide changes to alleviate these disparities.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

LAY SUMMARY

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

Effect of "timing it right" on comprehensive unmet needs and psychological pain in patients with head and neck cancer undergoing radiotherapy: a randomized controlled trial

PURPOSE

We assessed the effectiveness of "timing it right" (TIR) applications in patients undergoing radiotherapy for head and neck cancer through a carefully designed TIR intervention program. The assessment in this study emphasized the impact of the TIR intervention on the unmet needs and psychological pain of patients with head and neck cancer at different stages of radiotherapy.

METHODS

In total, 140 radiotherapy patients were randomly recruited into two study groups: (1) the TIR intervention group received routine nursing follow-up and comprehensive nursing intervention based on TIR, and (2) the control group received routine nursing care. Assessments were conducted at baseline, before discharge, and 3 months and 6 months after discharge. The comprehensive needs and psychological pain of patients with radiotherapy were measured using the Comprehensive Needs Assessment Tool in Cancer for Patients (CNAT) and the Distress Thermometer (DT), respectively. A linear mixed model was applied to analyze the effects.

RESULTS

A total of 137 patients completed the study. Compared to the control group, the TIR group showed significant improvements in information needs, health and psychological problems, healthcare staff, physical symptoms, health facilities and services, religious/spiritual support, and psychological pain (F=8.503, p=0.004; F=1.896, p=0.003; F=12.422, p<0.001; F=9.634, p=0.001; F=7.310, p=0.006; F=1.684, p=0.009; F=1.692, p=0.041). In addition to practical support, the remaining indicators differed significantly by time point, group, and group-time interaction.

CONCLUSIONS

The patient support application based on TIR can effectively address unmet needs and improve psychological pain, supporting TIR as an effective psychological management and intervention strategy for radiotherapy patients in the early stage of long-term rehabilitation.

TRIAL REGISTRATION

Chictr.org.cn Chi CTR2100047960.

A high stress profile is associated with severe pain in oncology patients receiving chemotherapy

PURPOSE

Oncology patients receiving chemotherapy can experience both cancer and non-cancer pain. In addition, oncology patients face numerous stressors and their responses are highly variable. Stress and pain are intricately linked. The purpose of this study was to evaluate for differences in pain characteristics and mood disturbance among oncology patients with distinct stress profiles.

METHODS

From a sample of 957 patients with and without pain, latent profile analysis identified three groups of patients with distinct stress profiles (i.e., Stressed, Normative, Resilient). In the subset of 671 patients with pain, receiving chemotherapy for breast, lung, gastrointestinal, or gynecologic cancer, we evaluated for differences among the stress profiles in terms of pain characteristics (e.g., intensity, qualities, interference) and mood disturbance (anxiety, depressive symptoms).

RESULTS

Compared to Normative patients (n = 333; 49.6%), Stressed patients (n = 305; 45.5%) reported higher levels of pain intensity, pain interference, anxiety, and depressive symptoms and more commonly described pain as throbbing, shooting, burning, exhausting, tiring, penetrating, nagging, miserable, and unbearable. Compared to Resilient patients (n = 33; 4.9%), Stressed patients reported significantly higher mood-related pain interference scores and more severe anxiety and depressive symptoms.

CONCLUSIONS

A high stress profile is common (45.5%) and is associated with more severe pain and associated symptoms. Efforts to identify and target this group for interventions may improve patient outcomes.

Exploring Psychoneurological Symptom Clusters in Acute Stroke Patients: A Latent Class Analysis

Purpose

To identify latent classes of acute stroke patients with distinct experiences with the symptom clusters of depression, anxiety, fatigue, sleep disturbance, and pain symptoms and assess, if the selected variables determine a symptom-cluster experience in acute stroke patients.

Participants and Methods

A sample of 690 participants were collected from July 2020 to December 2020 in a cross-sectional descriptive study. Latent class analysis was conducted to distinguish different clusters of acute stroke participants who experienced five patient-reported symptoms. Furthermore, multinomial logistic regression was selected to verify the influencing indicators of each subgroup, with selected socio-demographic variables, clinical characteristics, self-efficacy, and perceived social support as independent variables and the different latent classes as the dependent variable.

Results

Three latent classes, named “all high symptom,” “high psychological disorder,” and “all low symptom,” were identified, accounting for 9.6%, 26.3%, and 64.1% of symptom clusters, respectively. Patients in the “all high symptom” and “high psychological disorder” classes reported significantly lower quality of life (F=40.21, p <0.05). Female gender, younger age, higher National Institutes of Health Stroke Scale scores, and lower self-efficacy and perceived social support were risk factors associated with the “high psychological disorder” class. Younger patients with lower self-efficacy and perceived social support were more likely to be in the “all high symptom” class.

Conclusion

This study identified latent classes of acute stroke patients that can be used in predicting symptom-cluster experiences following a stroke. Also, the ability to characterize subgroups of patients with distinct symptom experiences helps identify high-risk patients. Focusing on symptom clusters in clinical practice can inspire us to create effective targeted interventions for subgroups of stroke patients suffering from the same symptom cluster.

Symptom Clusters and Quality of Life in Gastric Cancer Patients Receiving Chemotherapy

CONTEXT

Although gastric cancer is one of the most common tumors worldwide, there is little knowledge about symptom clusters and quality of life (QoL) in this population.

OBJECTIVES

The objectives were to identify the symptom clusters in gastric cancer patients receiving chemotherapy, and explore their effects on QoL.

METHODS

Gastric cancer patients receiving chemotherapy were recruited. Data were collected using the Memorial Symptom Assessment Scale Short Form, the Functional Assessment of Cancer Therapy-Gastric and the self-designed General Information Evaluation Form. The symptom clusters were extracted through the exploratory factor analysis. The influencing factors of symptom clusters and their effects on QoL were identified using multiple linear regression analysis.

RESULTS

A total of 322 participants were enrolled from three medical centers. Five factors were identified in this exploratory factor analysis based on symptom prevalence, namely fatigue related symptom cluster, epithelial symptom cluster, neurologic symptom cluster, malnutrition related symptom cluster and psychological symptom cluster (χ² = 31.470, P < 0.05). The affecting factors across symptom clusters and QoL subscales were relatively stable, but also different. Generally, fatigue related symptom cluster, malnutrition related symptom cluster and psychological symptom cluster demonstrated significantly negative effects on all aspects of QoL except social well being.

CONCLUSION

Five symptom clusters were identified in gastric cancer patients receiving chemotherapy in mainland China. The symptom clusters negatively contributed to the variance in all aspects of QoL except social well being. Further studies should examine interventions for symptom clusters, their influencing factors, and their effects on improving QoL.

Worst Pain Severity Profiles of Oncology Patients Are Associated With Significant Stress and Multiple Co-Occurring Symptoms

Little is known about the associations between pain, stress, and co-occurring symptoms in oncology patients. Purpose was to identify subgroups of patients with distinct worst pain profiles and evaluate for differences among the subgroups in demographic and clinical characteristics, as well as stress and symptom scores. Oncology outpatients (n = 1305) completed questionnaires prior to their second or third chemotherapy cycle. Worst pain intensity was assessed 6 times over 2 chemotherapy cycles using a 0 to 10 numeric rating scale. The 371 patients (28.4%) who had ≤1 occurrence of pain over the 6 assessments were classified as the None class. For the remaining 934 patients whose data were entered into the latent profile analysis, 3 distinct worst pain profiles were identified (ie Mild [12.5%], Moderate [28.6%], Severe [30.5%]). Compared to None class, Severe class had fewer years of education and a lower annual income; were less likely to be employed and married; less likely to exercise on a regular basis, had a higher comorbidity burden, and a worse functional status. Compared to None class, Severe class reported higher levels of general, disease-specific, and cumulative life stress and lower levels of resilience, as well as higher levels of depressive symptoms, anxiety, fatigue, sleep disturbance, and cognitive dysfunction. This study is the first to identify distinct worst pain profiles in a large sample of oncology patients receiving chemotherapy and associated risk factors. PERSPECTIVE: Unrelieved pain remains a significant problem for oncology patients receiving chemotherapy. High levels of stress and co-occurring symptoms contribute to a more severe pain profile in these patients.

Exploring interpersonal theory of suicide typologies in patients with cancer: A latent profile analysis

The current study examined patterns of endorsement of Interpersonal Theory of Suicide constructs in a group of patients with cancer (N = 133) via Latent Profile Analysis. Four profiles were identified: (1) Interpersonally Distressed (n = 7; 5.2%), (2) Burdened (n = 11; 8.3%), (3) Fearless About Death (n = 40; 30.1%), (4) Non-Distressed (n = 75; 56.4%). Profiles with higher levels of thwarted belongingness, perceived burdensomeness, and hopelessness were associated with greater suicide ideation. Results also suggest there may be characteristics of patients with cancer that require unique consideration about the potential meaning and relevance of such constructs.

Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes

Data-driven characterization of symptom clusters in chronic conditions is essential for shared cluster detection and physiological mechanism discovery. This study aims to computationally describe symptom documentation from electronic nursing notes and compare symptom clusters among patients diagnosed with four chronic conditions-chronic obstructive pulmonary disease (COPD), heart failure, type 2 diabetes mellitus, and cancer. Nursing notes (N = 504,395; 133,977 patients) were obtained for the 2016 calendar year from a single medical center. We used NimbleMiner, a natural language processing application, to identify the presence of 56 symptoms. We calculated symptom documentation prevalence by note and patient for the corpus. Then, we visually compared documentation for a subset of patients (N = 22,657) diagnosed with COPD (n = 3339), heart failure (n = 6587), diabetes (n = 12,139), and cancer (n = 7269) and conducted multiple correspondence analysis and hierarchical clustering to discover underlying groups of patients who have similar symptom profiles (i.e., symptom clusters) for each condition. As expected, pain was the most frequently documented symptom. All conditions had a group of patients characterized by no symptoms. Shared clusters included cardiovascular symptoms for heart failure and diabetes; pain and other symptoms for COPD, diabetes, and cancer; and a newly-identified cognitive and neurological symptom cluster for heart failure, diabetes, and cancer. Cancer (gastrointestinal symptoms and fatigue) and COPD (mental health symptoms) each contained a unique cluster. In summary, we report both shared and distinct, as well as established and novel, symptom clusters across chronic conditions. Findings support the use of electronic health record-derived notes and NLP methods to study symptoms and symptom clusters to advance symptom science.

A Preliminary Investigation of Psychoneurological Symptoms in Low-Income Mothers

BACKGROUND

Exposure to chronic stressors may contribute to the development of psychoneurological symptoms (i.e., fatigue, cognitive dysfunction, sleep disturbance, depressed mood, and pain) that can compromise maternal function.

OBJECTIVES

In two studies of low-income mothers, we investigated the presence of psychoneurological symptoms and explored associations between mothers' stressors and psychoneurological symptoms as well as between symptoms and function. We also considered the possible mediating role of the symptoms between stressors and function.

METHODS

We conducted secondary analyses of psychoneurological symptoms in two studies of low-income mothers of infants and toddlers in the United States. Study 1 sampled Latina women with limited English proficiency, whereas Study 2 was conducted with English-speaking women from diverse backgrounds. In both studies, symptoms were measured using items from the Center for Epidemiological Studies Depression Scale and the Medical Outcomes Study Short-Form Health Survey. Maternal function was measured through self-report and researcher observation. In Study 2, stressors were measured using the Everyday Stressors Index. Multiple linear regressions were used to investigate associations while controlling for relevant covariates.

RESULTS

In both studies, mothers endorsed a wide range of psychoneurological symptoms. In Study 1, psychoneurological symptoms had significant negative associations with role function, social function, and developmental stimulation. In Study 2, psychoneurological symptoms had significant negative associations with role function, social function, and physical function. Using Aroian test for mediation, we found that psychoneurological symptoms mediated all significant relationships between stressors and maternal functions in Study 2.

DISCUSSION

In two samples of low-income mothers, psychoneurological symptoms were prevalent and associated with chronic stressors and with maternal function and may mediate the association between those two factors. These findings extend prior research on depressive symptoms in mothers by investigating pain as an additional key symptom. The studies advance symptom science by highlighting psychoneurological symptoms in a heterogeneous sample without known health conditions.

Chronic Obstructive Pulmonary Disease Symptom Cluster Composition, Associated Factors, and Methodologies: A Systematic Review

This systematic review details symptom clusters, their compositions, and associated factors and appraises the methodologies of studies that reported symptom clusters in patients with chronic obstructive pulmonary disease (COPD). Ten studies were eligible for inclusion in this study. Four common symptom clusters were identified. Two theoretical frameworks, four statistical methods, and various symptom assessment tools were used to identify symptom clusters. Factors associated with symptom clusters included demographic, clinical, and biological factors. No studies examined the subjective experiences of symptom clusters. Overall, inconsistencies were identified in the composition of symptom clusters across studies. This may be due to variations in study design, assessment tools, and statistical methods. Future studies should attempt to arrive at a common definition, especially that is theoretically derived, for symptom clusters, standardize the criteria for symptoms for inclusion in the clusters, and focus on patients' subjective experience to inform which clusters are clinically relevant.

Two Methods for Calculating Symptom Cluster Scores

BACKGROUND

Symptom clusters are conventionally distilled into a single score using composite scoring, which is based on the mathematical assumption that all symptoms are equivalently related to outcomes of interest; this may lead to a loss of important variation in the data.

OBJECTIVES

This article compares two ways of calculating a single score for a symptom cluster: a conventional, hypothesis-driven composite score versus a data-driven, reduced rank regression score that weights the symptoms based on their individual relationships with key outcomes.

METHODS

We conducted a secondary analysis of psychoneurological symptoms from a sample of 356 low-income mothers. Four of the psychoneurological symptoms (fatigue, cognitive dysfunction, sleep disturbance, and depressed mood) were measured with the Center for Epidemiological Studies Depression Scale; the fifth (pain) was measured using an item from the Medical Outcomes Study 12-item Short Form Health Survey (SF-12). Mothers' function was measured using the 12-item Short Form Health Survey. The composite score was calculated by summing standardized scores for each individual psychoneurological symptom. In contrast, reduced rank regression weighted the individual symptoms using their respective associations with mothers' function; the weighted individual symptom scores were summed into the reduced rank regression symptom score.

RESULTS

The composite score and reduced rank regression score were highly correlated at .93. The cluster of psychoneurological symptoms accounted for 53.7% of the variation in the mothers' function. Depressed mood and pain accounted for almost all the explained variation in mothers' function at 37.2% and 15.0%, respectively.

DISCUSSION

The composite score approach was simpler to calculate, and the high correlation with the reduced rank regression score indicates that the composite score reflected most of the variation explained by the reduced rank regression approach in this data set. However, the reduced rank regression analysis provided additional information by identifying pain and depressed mood as having the strongest association with a mother's function, which has implications for understanding which symptoms to target in future interventions. Future studies should also explore composite versus reduced rank regression approaches given that reduced rank regression may yield different insights in other data sets.