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IntroductionIdentifying reliable biomarkers that reflect cancer survivorship symptoms remains a challenge for researchers. DNA methylation (DNAm) measurements reflecting epigenetic changes caused by anti-cancer therapy may provide needed insights. Given lack of consensus describing utilization of DNAm data to predict survivorship issues, a review evaluating the current landscape is warranted.ObjectiveProvide an overview of current studies examining associations of DNAm with survivorship burdens in cancer survivors.MethodsA literature review was conducted including studies if they focused on cohorts of cancer survivors, utilized peripheral blood cell DNAm data, and evaluated the associations of DNAm and survivorship issues.ResultsA total of 22 studies were identified, with majority focused on breast (n = 7) or childhood cancer (n = 9) survivors, and half studies included less than 100 patients (n = 11). Survivorship issues evaluated included those related to neurocognition (n = 5), psychiatric health (n = 3), general wellness (n = 9), chronic conditions (n = 5), and treatment specific toxicities (n = 4). Studies evaluated epigenetic age metrics (n = 10) and DNAm levels at individual CpG sites or regions (n = 12) for their associations with survivorship issues in cancer survivors along with relevant confounding factors. Significant associations of measured DNAm in the peripheral blood samples of cancer survivors and survivorship issues were identified.Discussion/conclusionStudies utilizing epigenetic age metrics and differential methylation analysis demonstrated significant associations of DNAm measurements with survivorship burdens. Associations were observed encompassing diverse survivorship outcomes and timeframes relative to anti-cancer therapy initiation. These findings underscore the potential of these measurements as useful biomarkers in survivorship care and research.

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 (

BACKGROUND: Shortness of breath occurs in 10%-70% of oncology patients. Very little is known about interindividual variability in its severity and distress and associated risk factors. Using latent profile analyses (LPAs), purpose was to identify subgroups of patients with distinct severity and distress profiles for shortness of breath as single symptom dimensions. In addition, a joint LPA was done using patients severity AND distress ratings. For each of the three LPAs, differences among the shortness of breath classes in demographic, clinical, symptom, stress, and resilience characteristics were evaluated. METHODS: Patients completed ratings of severity and distress from shortness of breath a total of six times over two cycles of chemotherapy. All of the other measures were completed at enrollment (i.e., prior to the second or third cycle of chemotherapy). Separate LPAs were done using ratings of severity and distress, as well as a joint analysis using severity AND distress ratings. Differences among the latent classes were evaluated using parametric and nonparametric tests. RESULTS: For severity, two classes were identified (Slight to Moderate [91.6%] and Moderate to Severe [8.4%]). For distress, two classes were identified (A Little Bit to Somewhat [83.9%] and Somewhat to Quite a Bit [16.1%]). For the joint LPA, two classes were identified (Lower Severity and Distress [79.9%] and Higher Severity and Distress [20.1%]). While distinct risk factors were associated with each of the LPAs, across the three LPAs, the common risk factors associated with membership in the worse class included: a past or current history of smoking, poorer functional status, and higher comorbidity burden. In addition, these patients had a higher symptom burden and higher levels of cancer-specific stress. CONCLUSIONS: Clinicians can use the information provided in this study to identify high-risk patients and develop individualized interventions.

BackgroundGene expression may be regulated by the DNA methylation of regulatory elements in cis, distal, and trans regions. One method to evaluate the relationship between DNA methylation and gene expression is the mapping of expression quantitative trait methylation (eQTM) loci (also called expression associated CpG loci, eCpG). However, no open-source tools are available to provide eQTM mapping. In addition, eQTM mapping can involve a large number of comparisons which may prevent the analyses due to limitations of computational resources. Here, we describe Torch-eCpG, an open-source tool to perform eQTM mapping that includes an optimized implementation that can use the graphical processing unit (GPU) to reduce runtime.ResultsWe demonstrate the analyses using the tool are reproducible, up to 18 × faster using the GPU, and scale linearly with increasing methylation loci.ConclusionsTorch-eCpG is a fast, reliable, and scalable tool to perform eQTM mapping. Source code for Torch-eCpG is available at https://github.com/kordk/torch-ecpg .

In vivo analysis of protein function in nociceptor subpopulations using antisense oligonucleotides and short interfering RNAs is limited by their non-selective cellular uptake. To address the need for selective transfection methods, we covalently linked isolectin B4 (IB4) to streptavidin and analyzed whether it could be used to study protein function in IB4(+)-nociceptors. Rats treated intrathecally with IB4-conjugated streptavidin complexed with biotinylated antisense oligonucleotides for protein kinase C epsilon (PKCε) mRNA were found to have: (a) less PKCε in dorsal root ganglia (DRG), (b) reduced PKCε expression in IB4(+) but not IB4(-) DRG neurons, and (c) fewer transcripts of the PKCε gene in the DRG. This knockdown in PKCε expression in IB4(+) DRG neurons is sufficient to reverse hyperalgesic priming, a rodent model of chronic pain that is dependent on PKCε in IB4(+)-nociceptors. These results establish that IB4-streptavidin can be used to study protein function in a defined subpopulation of nociceptive C-fiber afferents.

The persistence of inflammatory and neuropathic pain is poorly understood. We investigated a novel therapeutic paradigm by targeting gene networks that sustain or reverse persistent pain states. Our prior observations found that Sp1-like transcription factors drive the expression of TRPV1, a pain receptor, that is blocked in vitro by mithramycin A (MTM), an inhibitor of Sp1-like factors. Here, we investigate the ability of MTM to reverse in vivo models of inflammatory and chemotherapy-induced peripheral neuropathy (CIPN) pain and explore MTMs underlying mechanisms. Mithramycin reversed inflammatory heat hyperalgesia induced by complete Freund adjuvant and cisplatin-induced heat and mechanical hypersensitivity. In addition, MTM reversed both short-term and long-term (1 month) oxaliplatin-induced mechanical and cold hypersensitivity, without the rescue of intraepidermal nerve fiber loss. Mithramycin reversed oxaliplatin-induced cold hypersensitivity and oxaliplatin-induced TRPM8 overexpression in dorsal root ganglion (DRG). Evidence across multiple transcriptomic profiling approaches suggest that MTM reverses inflammatory and neuropathic pain through broad transcriptional and alternative splicing regulatory actions. Mithramycin-dependent changes in gene expression following oxaliplatin treatment were largely opposite to and rarely overlapped with changes in gene expression induced by oxaliplatin alone. Notably, RNAseq analysis revealed MTM rescue of oxaliplatin-induced dysregulation of mitochondrial electron transport chain genes that correlated with in vivo reversal of excess reactive oxygen species in DRG neurons. This finding suggests that the mechanism(s) driving persistent pain states such as CIPN are not fixed but are sustained by ongoing modifiable transcription-dependent processes.

PurposeEvaluate for perturbed signaling pathways associated with subgroups of patients with low versus high levels of state anxiety. These pathways were compared to the pathways identified across eight network pharmacology studies of the anxiolytic effect(s) of a variety of compounds.MethodsAdult outpatients had a diagnosis of breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding four weeks; and were scheduled to receive at least two additional cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct anxiety profiles based on Spielberger State Anxiety Inventory scores that were obtained six times over two cycles of chemotherapy. Blood samples were processed using RNA sequencing (i.e., RNA-seq sample, n = 244) and microarray (i.e., microarray sample; n = 256) technologies. Pathway perturbations were assessed using pathway impact analysis. Fisher's combined probability method was used to combine test results using a false discovery rate of 0.01.ResultsIn the RNA-seq sample, 62.3% and 37.7% of the patients were in the low- and high-anxiety classes, respectively. In the microarray sample, 61.3% and 38.7% were in the low and high-anxiety classes, respectively. Forty-one perturbed signaling pathways were identified. Eight of these pathways were common to those identified in the network pharmacology studies.ConclusionsFindings increase our knowledge of the molecular mechanisms that underlie anxiety in patients receiving chemotherapy. This study provides initial insights into how anxiety in patients with cancer may share common mechanisms with anxiety in patients with other clinical conditions.

BackgroundAnxiety and sleep disturbance are frequent symptoms during chemotherapy.ObjectivesPurposes were to identify subgroups of oncology outpatients with distinct joint anxiety and sleep disturbance profiles, as well as evaluate for differences in demographic and clinical characteristics, sleep disturbance characteristics, severity of common symptoms, and quality-of-life outcomes among these subgroups.MethodsOncology outpatients (n = 1331) completed self-report measures of anxiety and sleep disturbance 6 times over 2 chemotherapy cycles. Latent profile analysis was done to identify subgroups of patients with distinct joint anxiety and sleep disturbance profiles.ResultsThree profiles were identified (ie, no anxiety and low sleep disturbance (59.7%), moderate anxiety and high sleep disturbance (32.5%), high anxiety and very high sleep disturbance (7.8%)). Compared with the no anxiety and low sleep disturbance class, the other 2 classes were younger; less likely to be married; had a lower annual household income; and had childcare responsibilities. Patients in the 2 worse profiles had problems with both sleep initiation and maintenance. These patients reported higher levels of depressive symptoms, trait and state anxiety, and evening fatigue, as well as lower levels of morning and evening energy, cognitive function, and poorer quality of life.ConclusionsMore than 40% of patients had moderate or high levels of anxiety and high or very high levels of sleep disturbance. Modifiable risk factors associated with these profiles may be used to develop targeted interventions for 1 or both symptoms.Implications for practiceClinicians need to assess for the co-occurrence of anxiety and sleep disturbance.

BackgroundCancer-related cognitive impairment (CRCI) is a common symptom in patients with breast cancer. In our previous study of 397 women with breast cancer, we identified 3 groups of patients with distinct CRCI profiles (ie, high, moderate, and low-moderate attentional function). Compared with the other 2 classes, the low-moderate class was younger, had more comorbidities, and with lower functional status.ObjectivesIn this study, we expand on this work and evaluate for differences among these latent classes in the severity of psychological (depression and anxiety) and physical (fatigue, decrements in energy, sleep disturbance, and pain) symptoms before surgery.MethodsCancer-related cognitive impairment was assessed using the Attentional Functional Index from before through 6 months after surgery. Lower Attentional Functional Index scores indicate higher levels of CRCI. Psychological and physical symptoms were assessed with valid instruments. Parametric and nonparametric tests were used to evaluate for differences in symptom severity scores among the latent classes.ResultsApproximately 60% of patients experienced CRCI (ie, moderate and low-moderate classes). Significant differences were found among the 3 classes in the severity of trait and state anxiety, depressive symptoms, fatigue, and sleep disturbance (ie, high < moderate < low-moderate). In addition, compared with the other 2 classes, the low-moderate class reported higher pain interference scores.ConclusionsThese findings suggest that women with clinically meaningful levels of persistent CRCI have a relatively high symptom burden before surgery.Implications for practiceClinicians need to routinely perform preoperative assessments of CRCI and associated symptoms and initiate therapeutic interventions.

BACKGROUND: Morning and evening fatigue are distinct and distressing symptoms experienced during chemotherapy that demonstrate a large amount of interindividual variability. OBJECTIVES: The objectives of this study were to identify subgroups of patients with distinct morning and evening fatigue co-occurrence profiles and evaluate for differences among these subgroups in demographic, clinical, and symptom characteristics and quality of life. METHODS: Oncology patients ( n = 1,334) completed the Lee Fatigue Scale to self-report morning and evening fatigue, six times over two cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct morning and evening physical fatigue profiles. RESULTS: Four distinct morning and evening fatigue profiles were identified (i.e., Both Low, Low Morning + Moderate Evening, Both Moderate, and Both High). Compared to the Both Low profile, the Both High profile was significantly younger, less likely to be married or partnered, more likely to live alone, had a higher comorbidity burden, and lower functional status. The Both High profile had higher levels of anxiety, depressive symptoms, sleep disturbance, and pain and lower levels of quality of life. DISCUSSION: The variability in the morning and evening severity scores among the four profiles supports the hypothesis that morning and evening fatigue are distinct but related symptoms. Clinically meaningful levels of both morning and evening fatigue were reported by 50.4% of our sample, which suggests that the co-occurrence of these two symptoms is relatively common. Patients in Both Moderate and Both High profiles experienced an extremely high symptom burden that warrants ongoing assessments and aggressive symptom management interventions.

BackgroundUp 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.ObjectivesThe 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.MethodsThis 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.ResultsOn 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.DiscussionThese 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.

ObjectiveTo review the state of oncology nursing science as it pertains to big data. The authors aim to define and characterize big data, describe key considerations for accessing and analyzing big data, provide examples of analyses of big data in oncology nursing science, and highlight ethical considerations related to the collection and analysis of big data.Data sourcesPeer-reviewed articles published by investigators specializing in oncology, nursing, and related disciplines.ConclusionBig data is defined as data that are high in volume, velocity, and variety. To date, oncology nurse scientists have used big data to predict patient outcomes from clinician notes, identify distinct symptom phenotypes, and identify predictors of chemotherapy toxicity, among other applications. Although the emergence of big data and advances in computational methods provide new and exciting opportunities to advance oncology nursing science, several challenges are associated with accessing and using big data. Data security, research participant privacy, and the underrepresentation of minoritized individuals in big data are important concerns.Implications for nursing practiceWith their unique focus on the interplay between the whole person, the environment, and health, nurses bring an indispensable perspective to the interpretation and application of big data research findings. Given the increasing ubiquity of passive data collection, all nurses should be taught the definition, characteristics, applications, and limitations of big data. Nurses who are trained in big data and advanced computational methods will be poised to contribute to guidelines and policies that preserve the rights of human research participants.

BackgroundA 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.ObjectivesThis 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.MethodsPrior 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.ResultsCluster 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.ConclusionsThis 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.

BackgroundWhile pain is a significant problem for oncology patients, little is known about interindividual variability in pain characteristics.ObjectiveThe 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.MethodsPatients (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.ResultsThree 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.ConclusionsUnrelieved pain is a significant problem for more than 80% of outpatients.Implications for practiceClinicians need to perform comprehensive pain assessments; prescribe pharmacologic and nonpharmacologic interventions; and initiate referrals for pain management and psychological services.

OBJECTIVES: Palpitations are common and have a negative impact on womens quality of life. While evidence suggests that inflammatory mechanisms may play a role in the development of palpitations, no studies have evaluated for this association in patients with breast cancer who report palpitations prior to surgery. The purpose of this pilot study was to evaluate for associations between the occurrence of palpitations and single nucleotide polymorphisms (SNPs) in genes for pro- and anti-inflammatory cytokines, their receptors, and transcriptional regulators. METHODS: Patients were recruited prior to surgery and completed a self-report questionnaire on the occurrence of palpitations. Genotyping of SNPs in cytokine genes was performed using a custom array. Multiple logistic regression analyses were done to identify associations between the occurrence of palpitations and SNPs in fifteen candidate genes. RESULTS: Of the 82 SNPs evaluated in the bivariate analyses, eleven SNPs in 6 genes were associated with the occurrence of palpitations. After controlling for functional status, the occurrence of back pain, and self-reported and genomic estimates of race/ethnicity, 3 SNPs in 3 different genes (i.e., interleukin (IL) 1-beta (IL1B) rs1143643, IL10 rs3024505, IL13 rs1295686) were associated with the occurrence of palpitations prior to surgery (all p ≤ .038). CONCLUSIONS: While these preliminary findings warrant replication, they suggest that inflammatory mechanisms may contribute to the subjective sensation of palpitations in women prior to breast cancer surgery.

ContextCognitive and physical fatigue are common symptoms experienced by oncology patients. Exposure to stressful life events (SLE), cancer-related stressors, coping styles, and levels of resilience may influence the severity of both dimensions of fatigue.ObjectivesEvaluate for differences in global, cancer-specific, and cumulative life stress, as well as resilience and coping in oncology patients (n=1332) with distinct cognitive fatigue AND evening physical fatigue profiles.MethodsLatent profile analysis, which combined the two symptom scores, identified three subgroups of patients with distinct cognitive fatigue AND evening physical fatigue profiles (i.e., Low, Moderate, High). Patients completed measures of global, cancer-specific, and cumulative life stress as well measures of resilience and coping. Differences among the latent classes in the various measures were evaluated using parametric and nonparametric tests.ResultsCompared to Low class, the other two classes reported higher global and cancer-specific stress. In addition, they reported higher occurrence rates for sexual harassment and being forced to touch prior to 16 years of age. Compared to the other two classes, High class reported lower resilience scores and higher use of denial, substance use, and behavioral disengagement.ConclusionTo decrease both cognitive and evening physical fatigue, clinicians need to assess for relevant stressors and initiate interventions to increase resilience and the use of engagement coping strategies. Additional research is warranted on the relative contribution of various social determinants of health to both cognitive and physical fatigue in oncology patients receiving chemotherapy.

BackgroundUnrelieved chemotherapy-induced nausea (CIN) occurs 48% of patients undergoing chemotherapy and is one of the most debilitating symptoms that patients report.ObjectiveThe aims of this study were to identify subgroups of patients with distinct CIN profiles and determine how these subgroups differed on demographic and clinical characteristics; severity, frequency, and distress of CIN; and the co-occurrence of common gastrointestinal symptoms.MethodsPatients (n = 1343) completed demographic questionnaire and Memorial Symptom Assessment Scale 6 times over 2 cycles of chemotherapy. Latent class analysis was used to identify subgroups of patients with distinct CIN profiles. Differences among these subgroups were evaluated using parametric and nonparametric statistics.ResultsFour distinct CIN profiles were identified: none (40.8%), increasing-decreasing (21.5%), decreasing (8.9%), and high (28.8%). Compared with the none class, patients in the high class were younger, had a lower annual household income, had child care responsibilities, had a lower Karnofsky Performance Status score and a higher Self-administered Comorbidity Questionnaire score, and were more likely to have received chemotherapy on a 14-day cycle and a highly emetogenic chemotherapy regimen. In addition, patients in the high class reported high occurrence rates for dry mouth, feeling bloated, diarrhea, lack of appetite, abdominal cramps, difficulty swallowing, mouth sores, weight loss, and change in the way food tastes.ConclusionsThat 60% of the patients reported moderate to high CIN occurrence rates confirms that this unrelieved symptom is a significant clinical problem.Implications for practiceNurses need to evaluate patients' level of adherence to their antiemetic regimen and make appropriate referrals for physical therapy, psychological services, and dietary counseling.

BackgroundModerate to severe fatigue occurs in up to 94% of patients with cancer. Recent evidence suggests that morning and evening fatigue are distinct dimensions of physical fatigue. The purposes of this study were to evaluate the transcriptome for common and distinct perturbed inflammatory pathways in patients receiving chemotherapy who reported low versus high levels of morning or low versus high levels of evening cancer-related fatigue.MethodsPatients completed questionnaires during the week prior to their chemotherapy treatment. Severity of morning and evening fatigue was evaluated using the Lee Fatigue Scale. Gene expression and pathway impact analyses (PIA) were performed in two independent samples using RNA-sequencing (n = 357) and microarray (n = 360). Patterns of interactions between and among these perturbed pathways were evaluated using a knowledge network (KN).ResultsAcross the PIA, nine perturbed pathways (FDR

Unrelieved pain occurs in 55% of cancer patients. Identification of molecular mechanisms for pain may provide insights into therapeutic targets. Purpose was to evaluate for perturbations in neuroinflammatory pathways between oncology patients with and without severe pain. Worst pain severity was rated using a 0 to 10 numeric rating scale six times over two cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct pain profiles. Pathway impact analyses were performed in two independent samples using gene expression data obtained from RNA sequencing (n = 192) and microarray (n = 197) technologies. Fisher's combined probability test was used to identify significantly perturbed pathways between None versus the Severe pain classes. In the RNA sequencing and microarray samples, 62.5% and 56.3% of patients were in the Severe pain class, respectively. Nine perturbed pathways were related to neuroinflammatory mechanisms (i.e., retrograde endocannabinoid signaling, gamma-aminobutyric acid synapse, glutamatergic synapse, Janus kinase-signal transducer and activator of transcription signaling, phagosome, complement and coagulation cascades, cytokine-cytokine receptor interaction, chemokine signaling, calcium signaling). First study to identify perturbations in neuroinflammatory pathways associated with severe pain in oncology outpatients. Findings suggest that complex neuroimmune interactions are involved in the maintenance of chronic pain conditions. Perspective: In this study that compared oncology patients with none versus severe pain, nine perturbed neuroinflammatory pathways were identified. Findings suggest that complex neuroimmune interactions are involved in the maintenance of persistent pain conditions.

Objective/backgroundSleep disturbance is a common problem in patients receiving chemotherapy. Purpose was to evaluate for perturbations in immune-inflammatory pathways between oncology patients with low versus very high levels of sleep disturbance.Patients/methodsSleep disturbance was evaluated using the General Sleep Disturbance Scale six times over two cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct sleep disturbance profiles. Pathway impact analyses were performed in two independent samples using gene expression data obtained from RNA sequencing (n = 198) and microarray (n = 162) technologies. Fisher's combined probability test was used to identify significantly perturbed pathways between Low versus Very High sleep disturbance classes.ResultsIn the RNA sequencing and microarray samples, 59.1% and 51.9% of patients were in the Very High sleep disturbance class, respectively. Thirteen perturbed pathways were related to immune-inflammatory mechanisms (i.e., endocytosis, phagosome, antigen processing and presentation, natural killer cell mediated cytotoxicity, cytokine-cytokine receptor interaction, apoptosis, neutrophil extracellular trap formation, nucleotide-binding and oligomerization domain-like receptor signaling, Th17 cell differentiation, intestinal immune network for immunoglobulin A production, T-cell receptor signaling, complement and coagulation cascades, and tumor necrosis factor signaling).ConclusionsFirst study to identify perturbations in immune-inflammatory pathways associated with very high levels of sleep disturbance in oncology outpatients. Findings suggest that complex immune-inflammatory interactions underlie sleep disturbance.

BACKGROUND: Patients undergoing cancer treatment experience global stress and cancer-specific stress. Both types of stress are associated with a higher symptom burden. OBJECTIVE: In this cross-sectional study, we used a comprehensive set of demographic, clinical, and symptom characteristics to evaluate their relative contribution to the severity of global and cancer-specific stress. METHODS: Patients (N = 941) completed study questionnaires before their second or third cycle of chemotherapy. RESULTS: Consistent with our a priori hypothesis, we found both common and distinct characteristics associated with higher levels of global stress and cancer-specific stress. A significant proportion of our patients had scores on the Impact of Event Scale-Revised suggestive of subsyndromal (29.4%) or probable (13.9%) posttraumatic stress disorder. Four of the 5 stepwise linear regression analyses for the various stress scales explained between 41.6% and 54.5% of the total variance. Compared with various demographic and clinical characteristics, many of the common symptoms associated with cancer and its treatments uniquely explained a higher percentage of the variance in the various stress scales. Symptoms of depression made the largest unique contribution to the percentage of total explained variance across all 5 scales. CONCLUSION: Clinicians need to assess for global stress, cancer-specific stress, and depression in patients receiving chemotherapy. IMPLICATIONS FOR PRACTICE: Patients may benefit from integrative interventions (eg, mindfulness-based stress reduction, cognitive behavioral therapy, acupuncture) that simultaneously address stress and symptoms commonly associated with cancer and its treatments.

ObjectivesWhile 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.MethodsPrior 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.ResultsFor 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.ConclusionsThis 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.

IntroductionIntegrated transcriptome and microRNA differential gene expression (DEG) analyses may help to explain type 2 diabetes (T2D) pathogenesis in at-risk populations. The purpose of this study was to characterize DEG in banked biospecimens from underactive adult participants who responded to a randomized clinical trial measuring the effects of lifestyle interventions on T2D risk factors. DEGs were further examined within the context of annotated biological pathways.MethodsParticipants (n = 52) in a previously completed clinical trial that assessed a 12-week behavioural intervention for T2D risk reduction were included. Participants who showed >6mg/dL decrease in fasting blood glucose were identified as responders. Gene expression was measured by RNASeq, and overrepresentation analysis within KEGG pathways and weighted gene correlation network analysis (WGCNA) were performed.ResultsNo genes remained significantly differentially expressed after correction for multiple comparisons. One module derived by WGCNA related to body mass index was identified, which contained genes located in KEGG pathways related to known mechanisms underlying risk for T2D as well as pathways related to neurodegeneration and protein misfolding. A network analysis showed indirect connections between genes in this module and islet amyloid polypeptide (IAPP), which has previously been hypothesized as a mechanism for T2D.DiscussionWe validated prior studies that showed pathways related to metabolism, inflammation/immunity, and endocrine/hormone function are related to risk for T2D. We identified evidence for new potential mechanisms that include protein misfolding. Additional studies are needed to determine whether these are potential therapeutic targets to decrease risk for T2D.

Endometriosis is a leading cause of pain and infertility affecting millions of women globally. Herein, we characterize variation in DNA methylation (DNAm) and its association with menstrual cycle phase, endometriosis, and genetic variants through analysis of genotype data and methylation in endometrial samples from 984 deeply-phenotyped participants. We estimate that 15.4% of the variation in endometriosis is captured by DNAm and identify significant differences in DNAm profiles associated with stage III/IV endometriosis, endometriosis sub-phenotypes and menstrual cycle phase, including opening of the window for embryo implantation. Menstrual cycle phase was a major source of DNAm variation suggesting cellular and hormonally-driven changes across the cycle can regulate genes and pathways responsible for endometrial physiology and function. DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent cis-mQTLs including 51 associated with risk of endometriosis, highlighting candidate genes contributing to disease risk. Our work provides functional evidence for epigenetic targets contributing to endometriosis risk and pathogenesis. Data generated serve as a valuable resource for understanding tissue-specific effects of methylation on endometrial biology in health and disease.

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.

PurposeRelatively 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.MethodsA 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.ResultsPatients 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.ConclusionsPsychological, 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.

Background: In patients with lymphedema (LE), in addition to hand dominance, between-group comparisons of interlimb soft tissue differences need to account for differences in whole-body adiposity, measured directly by dual energy X-ray absorptiometry (DXA) or indirectly by body mass index. No study has evaluated the effects of hand dominance and whole-body adiposity on limb composition in patients with LE. This studys purpose was to compare soft tissue composition of affected and unaffected limbs of women with breast cancer, who did and did not have LE, controlling for dominance and percent body fat. Methods and Results: Whole-body DXA scans were acquired and included measures of percent body fat, upper limb total mass, upper limb fat mass, and upper limb fat-free mass. Participants were classified into one of three groups: women without LE; women with only subjective LE; and women with objective signs of LE at the time of assessment. Differences among the LE groups were evaluated using analysis of variance (ANOVA) and Chi-square analyses. Analysis of covariance (ANCOVA) was used to control for percent body fat and for the affected limb dominance. Compared to women without LE, women with objective signs of LE have greater total limb mass, fat mass, and fat-free mass in their affected limbs, independent of affected side dominance and percent body fat. In addition, the interlimb differences in total mass, fat mass, and fat-free mass were greater for the women with objective signs of LE, compared to the other two groups. Conclusions: DXA is useful in identifying soft tissue changes in patients with LE. Given that limb circumferences measure only changes in limb volume and that bioimpedance provides estimates of extracellular fluid, DXA has the advantage of being able to estimate the volumes of specific tissues in the limb.

BackgroundPatients with gynecologic cancer undergoing chemotherapy experience multiple co-occurring symptoms. Understanding how symptom clusters change over time is essential to the development of interventions that target multiple co-occurring symptoms.ObjectiveThe aim of this study was to assess the relative stability of symptom clusters across a chemotherapy cycle in patients with gynecologic cancer.MethodsThis is a longitudinal, descriptive study. Eligible patients (n = 232) were English-speaking adults (≥18 years old) with gynecologic cancer. Data were collected in the week before patients' second or third cycle of chemotherapy (T1) and at 1 (T2) and 2 (T3) weeks after chemotherapy. Three dimensions of the symptom experience (occurrence, severity, and distress) were assessed using a modified version of the Memorial Symptom Assessment Scale. Symptom clusters for each dimension and time point were identified through exploratory factor analysis.ResultsA 5-factor solution was selected for each exploratory factor analysis. Hormonal, respiratory, and weight change clusters were identified across all dimensions and time points. A psychological symptom cluster was identified at T1 for occurrence and severity and at T2 and T3 for all 3 dimensions. A gastrointestinal symptom cluster was identified at T1 for occurrence and at T2 and T3 for all 3 dimensions. The hormonal, respiratory, psychological, and weight change symptom clusters exhibited common symptoms across dimensions and time points.ConclusionsHormonal, respiratory, weight change, and psychological symptom clusters are relatively stable across a cycle of chemotherapy in patients with gynecologic cancer.Implications for practiceClinicians need to assess patients for multiple co-occurring symptoms and initiate multimodal interventions.

PurposeIn a sample of oncology patients, identify subgroups of patients with distinct depressive symptom profiles and evaluate for differences in demographic and clinical characteristics, levels of stress and resilience, and the severity of common co-occurring symptoms.MethodsPatients (n = 1327) had a diagnosis of breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding four weeks; and were scheduled to receive at least two additional cycles of chemotherapy. Demographic and clinical characteristics, stress, resilience, and co-occurring symptoms were evaluated at enrollment. Depressive symptoms were evaluated using the Center for Epidemiological Studies-Depression (CES-D) scale a total of six times over two cycles of chemotherapy. Latent profile analysis (LPA) was used to identify subgroups of patients (i.e., latent classes) with distinct depressive symptom profiles using the six CES-D scores.ResultsBased on the findings from the LPA, 47.3% of the patients were classified as "None"; 33.6% as "Subsyndromal"; 13.8% as "Moderate"; and 5.3% as "High". Compared to None class, patients in the Subsyndromal, Moderate, and High classes had a lower functional status, a higher comorbidity burden, and a self-reported diagnosis of depression or back pain. Those patients with higher levels of depressive symptoms reported higher levels of stress, lower levels of resilience, and increased severity of co-occurring symptoms.ConclusionsInter-individual variability in depressive symptoms was associated with demographic and clinical characteristics, multiple types of stress and levels of resilience, as well as with the increased severity of multiple co-occurring symptoms. The risk factors associated with worse depressive symptom profiles can assist clinicians to identify high risk patients and initiate more timely supportive care interventions.

BackgroundUnrelieved chemotherapy-induced nausea (CIN) is a significant problem for patients with breast cancer (BC).ObjectiveIn a sample of patients with BC who were assessed before their second or third cycle of chemotherapy, study purposes were to evaluate for the occurrence, severity, frequency, and distress associated with CIN; evaluate for differences in demographic and clinical characteristics and gastrointestinal (GI) symptom occurrence rates between patients who did and did not report CIN; and determine which demographic, clinical, and symptom characteristics were associated with the occurrence of CIN.MethodsPatients completed demographic and clinical questionnaires and the Memorial Symptom Assessment Scale for nausea and common GI symptom assessments. Univariate analyses evaluated for differences in demographic and clinical characteristics and GI symptom occurrence between patients who did and did not report CIN. Multiple logistic regression analysis evaluated for characteristics associated with CIN.ResultsOf the 532 patients with BC, 47.2% reported CIN occurrence. Characteristics associated with CIN group membership were poorer functional status, receipt of chemotherapy on a 14-day cycle, and higher occurrence rates of 5 GI symptoms (ie, dry mouth, vomiting, constipation, change in the way food tastes, and lack of appetite; all P < .001).ConclusionsUnrelieved CIN is a common symptom in patients with BC. This study is the first to demonstrate that 5 co-occurring GI symptoms were associated with CIN occurrence.Implications for practiceThis study identified new risk factors for CIN occurrence in patients with BC. Clinicians may be able to initiate additional interventions to alleviate CIN.

Background and purposeSince 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.MethodsEligible 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.ResultsTwenty-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.DiscussionWhile 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 numberCRD42021240216.

Background: Lymphedema (LE) is a significant clinical problem for breast cancer survivors. While the water displacement test and circumferential assessment using a tape measure (TM) are common methods to assess differences in arm volumes, faster and more reliable methods are needed. Study purposes, in breast cancer survivors (n = 294), were to compare the average total arm volumes and interlimb volume ratios for women with and without a history of LE, using a TM and three-dimensional (3D), whole-body surface scanner (3D scan); compare the level of agreement between arm volumes and interlimb volume ratios obtained using the two devices; and evaluate the percent agreement between the two measures in classifying cases of LE using three accepted thresholds. Methods and Results: Measurements were done using a spring-loaded TM and Fit3D ProScanner. Paired t-tests and Bland-Altman analyses were used to achieve the study aims. For circumference and volume comparisons, compared with the 3D scan, values obtained using the TM were consistently smaller. In terms of level of agreement, the Bland-Altman analyses demonstrated large biases and wide limits of agreement for the calculated arm volumes and volume ratios. In terms of the classification of caseness, using the 200-mL interlimb volume difference criterion resulted in 81.6% overall agreement; using the >10% volume difference between the affected and unaffected arms resulted in 78.5% overall agreement; and using the volume ratio ≥1.04 criterion resulted in 62.5% overall agreement. For all three accepted threshold criteria, the percentage of cases was significantly different between the TM and 3D scan techniques. Conclusions: The 3D technology evaluated in this study has the potential to be used for self-initiated surveillance for LE. With improvements in landmark identification and software modifications, it is possible that accurate and reliable total arm volumes can be calculated and used for early detection.

BackgroundThe earliest measurable changes to postinjury platelet biology may be in the platelet transcriptome, as platelets are known to carry messenger ribonucleic acids (RNAs), and there is evidence in other inflammatory and infectious disease states of differential and alternative platelet RNA splicing in response to changing physiology. Thus, the aim of this exploratory pilot study was to examine the platelet transcriptome and platelet RNA splicing signatures in trauma patients compared with healthy donors.MethodsPreresuscitation platelets purified from trauma patients (n = 9) and healthy donors (n = 5) were assayed using deep RNA sequencing. Differential gene expression analysis, weighted gene coexpression network analysis, and differential alternative splicing analyses were performed. In parallel samples, platelet function was measured with platelet aggregometry, and clot formation was measured with thromboelastography.ResultsDifferential gene expression analysis identified 49 platelet RNAs to have differing abundance between trauma patients and healthy donors. Weighted gene coexpression network analysis identified coexpressed platelet RNAs that correlated with platelet aggregation. Differential alternative splicing analyses revealed 1,188 splicing events across 462 platelet RNAs that were highly statistically significant (false discovery rate

ContextCutpoints can be used as a threshold for screening symptom(s) that warrant intervention(s) and for monitoring patients' responses to these interventions.ObjectivesIn a sample of oncology patients undergoing chemotherapy, study purposes were to determine the optimal cutpoints for low, moderate, and high symptom burden and determine if these cutpoints distinguished among the symptom groups in any demographic, clinical, and stress characteristics, as well as QOL outcomes.MethodsTotal of 1329 patients completed a modified version of the Memorial Symptom Assessment Scale (38 symptoms). Using the methodology of Serlin and colleagues, cutpoints were created using symptom occurrence rates and cancer-specific quality of life (QOL) scores. Cutpoints were validated using measures of stress and resilience and a generic measure of QOL (i.e., Medical Outcomes Study Short Form 12 (SF-12)).ResultsOf the 25 possible cutpoints evaluated, the optimal cutpoint, with the largest between category F statistic, was CP8,15 (Low = 0-8, Moderate = 9-15, High = 16-38 symptoms). Percentage of patients in the Low, Moderate, and High cutpoint groups were 25.3%, 36.3%, and 38.4%, respectively. Significant differences were found among the symptom burden groups in global, cancer-specific, and cumulative life stress (i.e., Low < Moderate < High) and resilience and SF-12 (i.e., Low > Moderate > High) scores.ConclusionOur findings provide evidence for clinically meaningful cutpoints that can be used to guide symptom assessment and management. These cutpoints may be used to establish alert thresholds for electronic monitoring of symptoms in oncology patients.

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.

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.

Because extracellular vesicle (EV)-associated cytokines, both encapsulated and surface bound, have been associated with symptom severity, and may vary over the lifespan, they may be potential biomarkers to uncover underlying mechanisms of various conditions. This study evaluated the associations of soluble and EV-associated cytokine concentrations with distinct symptom profiles reported by 290 women with breast cancer prior to surgery. Patients were classified into older (≥60 years, n = 93) and younger (< 60 years, n = 197) cohorts within two previously identified distinct symptom severity profiles, that included pain, depressive symptoms, sleep disturbance, and fatigue (i.e., High Fatigue Low Pain and All Low). EVs were extracted using ExoQuick. Cytokine concentrations were determined using Luminex multiplex assay. Mann Whitney U test evaluated the differences in EV and soluble cytokine levels between symptom classes and between and within the older and younger cohorts adjusting for Karnofsky Performance Status (KPS) score, body mass index (BMI), and stage of disease. Partial correlation analyses were run between symptom severity scores and cytokine concentrations. Results of this study suggest that levels of cytokine concentrations differ between EV and soluble fractions. Several EV and soluble pro-inflammatory cytokines had positive associations with depressive symptoms and fatigue within both age cohorts and symptom profiles. In addition, in the older cohort with High Fatigue Low Pain symptom profile, EV GM-CSF concentrations were higher compared to the All Low symptom profile (p < 0.05). Albeit limited by a small sample size, these exploratory analyses provide new information on the association between cytokines and symptom profiles of older and younger cohorts. Of note, unique EV-associated cytokines were found in older patients and in specific symptom classes. These results suggest that EVs may be potential biomarker discovery tools. Understanding the mechanisms that underlie distinct symptom class profiles categorized by age may inform intervention trials and offer precision medicine approaches.

PurposeThe purposes of this study, in a sample of oncology patients (n = 1326) receiving chemotherapy, were to identify subgroups of patients with distinct anxiety profiles and evaluate for differences in demographic and clinical characteristics, stress and resilience measures, and severity of co-occurring symptoms (i.e., depression, sleep disturbance, attentional function, fatigue, pain).MethodsPatients completed self-report questionnaires a total of six times over two cycles of chemotherapy. Severity of state anxiety was evaluated using the Spielberger State Anxiety Inventory and resilience was assessed using the Connor-Davidson Resilience Scale. Symptoms were assessed using the Center for Epidemiologic Studies Depression Scale, General Sleep Disturbance Scale, Lee Fatigue Scale, Attentional Function Index and Brief Pain Inventory.ResultsBased on the findings from the latent profile analysis that utilized the six assessments of state anxiety, 47.7% of the patients were classified as "Low," 28.3% as "Moderate," 19.5% as "High," and 4.5.% as "Very High." Anxiety levels remained relatively stable across the six timepoints. Compared to the Low class, membership in the Moderate, High, and Very High classes was associated with a number of characteristics (e.g., younger age, female gender, lower functional status, more comorbidities). Those patients with higher levels of anxiety reported higher levels of stress, lower levels of resilience, and increased severity of co-occurring symptoms.ConclusionOur findings suggest that a substantial number of oncology patients may warrant referral to psychological services. Clinicians need to perform systematic assessments of anxiety, stress, and common symptoms and initiate appropriate interventions to enhance resilience and coping.

Cancer-related cognitive impairment (CRCI) is a significant problem for patients receiving chemotherapy. While a growing amount of pre-clinical and clinical evidence suggests that inflammatory mechanisms underlie CRCI, no clinical studies have evaluated for associations between CRCI and changes in gene expression. Therefore, the purpose of this study was to evaluate for differentially expressed genes and perturbed inflammatory pathways across two independent samples of patients with cancer who did and did not report CRCI. The Attentional Function Index (AFI) was the self-report measure used to assess CRCI. AFI scores of 7.5 indicate low versus high levels of cognitive function, respectively. Of the 185 patients in Sample 1, 49.2% had an AFI score of 7.5. Of the 158 patients in Sample 2, 50.6% had an AFI score of 7.5. Data from 182 patients in Sample 1 were analyzed using RNA-seq. Data from 158 patients in Sample 2 were analyzed using microarray. Twelve KEGG signaling pathways were significantly perturbed between the AFI groups, five of which were signaling pathways related to inflammatory mechanisms (e.g., cytokine-cytokine receptor interaction, tumor necrosis factor signaling). This study is the first to describe perturbations in inflammatory pathways associated with CRCI. Findings highlight the role of cytokines both in terms of cytokine-specific pathways, as well as pathways involved in cytokine production and cytokine activation. These findings have the potential to identify new targets for therapeutics and lead to the development of interventions to improve cognition in patients with cancer.

Background: While supine bioimpedance devices are used to evaluate for lymphedema (LE), stand-on devices are gaining popularity. Because research on differences in bioimpedance values between the two devices is limited, this study's purposes were to: (1) determine the average upper limb impedance values and inter-limb ratios for women who self-reported having (n = 34) or not having (n = 61) a history of LE, using a single-frequency supine device and a multifrequency stand-on device; (2) compare the level of agreement in inter-limb impedance ratios between the two devices; evaluate the percent agreement between the two devices in classifying cases of LE using established supine thresholds; and evaluate the percent agreement in classifying cases of LE between the supine device using previously established supine thresholds and the stand-on device using two published standing thresholds. Methods and Results: Bioimpedance measures were done using the two devices. For the entire sample, absolute impedance values for both the affected and unaffected limbs were significantly higher for the stand-on device in women with and without LE. Impedance values for the two methods were highly correlated. Bland-Altman analysis determined that for the entire range of impedance ratios the values for the two devices could not be used interchangeably. Conclusions: Findings suggest that the stand-on device can be a useful and valid tool to assess for LE. However, because agreement is not perfect, values obtained from the two devices should not be used interchangeably to evaluate for changes in impedance ratios, particularly for ratios of >1.20.

PurposeTo identify subgroups of female breast cancer patients with distinct self-reported employment interference (EI) profiles and determine which demographic, clinical, and symptom characteristics, and quality of life outcomes were associated with subgroup membership.MethodsWomen with breast cancer (n = 385) were assessed for changes in EI over ten times, from prior to, through 12 months after breast cancer surgery. Latent profile analysis (LPA) was used to identify subgroups of patients with distinct EI profiles.ResultsThree distinct EI profiles (i.e., None - 26.2% (n = 101), Low - 42.6% (n = 164), High - 31.2% (n = 120)) were identified. Compared to the None and Low groups, patients in the High group were more likely to be younger. Higher proportions in the High group were non-White, pre-menopausal prior to surgery, had more advanced stage disease, had received an axillary lymph node dissection, had received neoadjuvant chemotherapy, had received adjuvant chemotherapy, and had a re-excision or mastectomy on the affected breast within 6 months after surgery. In addition, these patients had lower quality of life scores. Compared to the None group, the High group had higher levels of trait and state anxiety, depressive symptoms, fatigue and sleep disturbance and lower levels of cognitive function.ConclusionsThis study provides new knowledge regarding EI profiles among women in the year following breast cancer surgery. The non-modifiable risk factors (e.g., younger age, being non-White, having more advanced stage disease) can inform current screening procedures. The potentially modifiable risk factors can be used to develop interventions to improve employment outcomes of breast cancer patients.

The incorporation of omics approaches into symptom science research can provide researchers with information about the molecular mechanisms that underlie symptoms. Most of the omics analyses in symptom science have used a single omics approach. Therefore, these analyses are limited by the information contained within a specific omics domain (e.g., genomics and inherited variations, transcriptomics and gene function). A multi-staged data-integrated multi-omics (MS-DIMO) analysis integrates multiple types of omics data in a single study. With this integration, a MS-DIMO analysis can provide a more comprehensive picture of the complex biological mechanisms that underlie symptoms. The results of a MS-DIMO analysis can be used to refine mechanistic hypotheses and/or discover therapeutic targets for specific symptoms. The purposes of this paper are to: (1) describe a MS-DIMO analysis using "Symptom X" as an example; (2) discuss a number of challenges associated with specific omics analyses and how a MS-DIMO analysis can address them; (3) describe the various orders of omics data that can be used in a MS-DIMO analysis; (4) describe omics analysis tools; and (5) review case exemplars of MS-DIMO analyses in symptom science. This paper provides information on how a MS-DIMO analysis can strengthen symptom science research through the prioritization of functional genes and biological processes associated with a specific symptom.

Cancer-related fatigue is common in head and neck cancer patients. This complex, multidimensional patient-reported outcome has quality of life and cancer treatment implications.

BackgroundLoneliness and social isolation are significant public health problems that are being exacerbated during the coronavirus disease 2019 pandemic. Little is known about the associations between loneliness and symptom burden in oncology patients before and during the pandemic. Study purposes include determining the prevalence of loneliness in a sample of oncology patients; evaluating for differences in demographic, clinical, and symptom characteristics between lonely and nonlonely patients; and determining which demographic, clinical, and symptom characteristics were associated with membership in the lonely group.MethodsA convenience sample (n = 606) completed online surveys that evaluated the severity of loneliness, social isolation, and common symptoms (ie, anxiety, depression, fatigue, sleep disturbance, cognitive dysfunction, and pain) in oncology patients. Parametric and nonparametric tests were used to evaluate for differences in scores between the lonely and nonlonely groups. Logistic regression analysis was used to determine risk factors for membership in the loneliness group.ResultsOf the 606 patients, 53.0% were categorized in the lonely group. The lonely group reported higher levels of social isolation, as well as higher symptom severity scores for all of the symptoms evaluated. In the multivariate model, being unmarried, having higher levels of social isolation, as well as higher levels of anxiety and depressive symptoms were associated with membership in the lonely group.ConclusionsStudy findings suggest that a significant number of oncology patients are experiencing loneliness, most likely as a result of mandate social distancing and isolation procedures. The symptom burden of these patients is extremely high and warrants clinical evaluation and interventions.