The relationship between personality and stress and resilience has been relatively underexplored among patients undergoing chemotherapy (CTX). This study investigated these associations in adults undergoing CTX for solid tumors. In this observational study, 1,248 patients receiving CTX for breast, gastrointestinal, gynecological, or lung cancer, completed the NEO Five-Factor Inventory (NEO-FFI) measures of life stress (Life Stressor Checklist–Revised; LSC-R; exposure and affected scores), cancer-related distress (Impact of Event Scale–Revised; IES-R), perceived stress (Perceived Stress Scale; PSS), and resilience (Connor-Davidson Resilience Scale; CD-RISC-10). Differences among three (previously described) latent personality profiles (i.e., Distressed, Normative, Resilient) in stress and resilience characteristics were examined using ANOVA, Kruskal–Wallis, or chi‐square tests. The Distressed class reported significantly higher IES-R total and subscale scores, higher PSS scores, and greater affected (but not total) LSC-R scores than both other classes (all p < .001). The Resilient class demonstrated the lowest cancer‐related distress and perceived stress, and the highest CD-RISC-10 scores, compared to Normative and Distressed classes (all p < .001). Although total number of life stressors differed only between Distressed and Resilient groups, the perceived impact of specific stressors (e.g., childhood abuse, financial hardship) was greater in the Distressed class. Distinct personality profiles, as defined by Big Five dimensions, are strongly associated with differential levels of cancer‐related distress, perceived stress, and resilience among CTX patients. Identification of individuals with “Distressed” personality profiles may facilitate early identification of patients who could benefit from early psychosocial assessment or interventions.

PurposeIdentify subgroups of oncology patients with distinct joint chemotherapy-induced nausea (CIN) AND morning fatigue profiles and distinct joint CIN AND evening fatigue profiles, as well as modifiable and non-modifiable risk factors.MethodsOncology patients receiving chemotherapy completed self-report questionnaires that provided information on demographic and clinical characteristics, as well as on CIN and morning and evening fatigue. The three symptoms were assessed six times over two cycles of chemotherapy. Joint latent class profile analyses (LCPA) were performed to identify subgroups of patients with distinct joint symptom profiles. Parametric and non-parametric tests were used to evaluate for differences in modifiable and non-modifiable risk factors among the profiles.ResultsFive and four subgroups were identified with distinct joint CIN and morning fatigue and distinct joint CIN and evening fatigue profiles, respectively. Risk factors associated with membership in the worse profiles included younger age, lower annual household income, high comorbidity burden, lower functional status, self-reported diagnosis of depression, and higher levels of neuropsychological and gastrointestinal symptoms.ConclusionsAcross both LCPAs, 60% of the sample reported CIN with occurrence rates that ranged from approximately 30% to 90%. In addition, wide variations were found in both morning and evening fatigue severity scores depending on the distinct profile. These initial findings suggest that CIN co-occurs with both morning and evening fatigue. The co-occurrence of CIN and fatigue may be related to shared biological mechanisms that warrant evaluation in future studies.

Purpose Chemotherapy-induced peripheral neuropathy (CIPN) is associated with a large amount of interindividual variability in signs and symptoms. The purposes were to use latent profile analysis to identify subgroups of survivors with distinct lower extremity (LE) loss-of-function CIPN profiles; evaluate for differences in demographic, clinical, and pain characteristics between the profiles and characteristics associated with membership in the more severe profile; and examine relationships between the profiles and measures of large fiber loss and C-tactile fiber function. Methods LE loss-of-function CIPN profiles were created using measures of worst pain, loss of light touch sensation, loss of cold sensation, loss of pain sensation, vibration threshold, and two balance measures. Results Of the 405 survivors evaluated, two distinct profiles were identified: less severe loss of LE function (76.5%) and more severe loss of LE function (23.5%). Risk factors for membership in the more severe profile included being older, male, and having lower functional status. In terms of the loss of large fiber function, survivors in the more severe class had four more sites on average that lost light touch sensation; their vibration thresholds were 1.5 times higher; and their ratings of numbness were significantly higher. For C-tactile fiber function, significant between-group differences were found in survivors' ratings of the severity of sensitive skin and unpleasantness. Conclusions Findings suggest that distinct "CIPN phenotypes" can be identified in cancer survivors. Detailed phenotyping and molecular characterization of various CIPN phenotypes will lead to the development and testing of targeted and personalized interventions.

ABSTRACT Context Limited information is available on the symptom burden and symptom clusters in cancer survivors. Objectives Describe the occurrence, severity, and distress of 44 symptoms; determine risk factors associated with a higher symptom burden; and evaluate for symptom clusters using symptom occurrence rates. Methods Survivors (n = 1147) were recruited using an online survey. Symptom burden and symptom clusters were assessed using the Memorial Symptom Assessment Scale that included 44 symptoms and evaluated occurrence, severity, and distress. Simultaneous multivariable linear regression analysis was performed to determine risk factors associated with a higher symptom burden. Exploratory factor analysis was used to identify symptom clusters using ratings of symptom occurrence. Results Survivors reported an average ten concurrent symptoms. Survivors who are younger, female, with a higher comorbidity burden, evidence of metastatic disease, and a poorer functional status were at increased risk for a higher symptom burden. Six symptom clusters were identified (i.e., psychological cluster, cancer and treatment‐related cluster, respiratory cluster, pain cluster, weight loss cluster, epithelial cluster). Conclusion Additional research is warranted to confirm the prevalence rates for the various symptoms and symptom clusters; identify additional risk factors for a higher symptom burden; and determine the underlying mechanisms for the symptom clusters. Future studies need to develop and test targeted interventions for each of the symptom clusters within and across various types of cancer.

ABSTRACT Background Compared to younger patients, older patients report differences in the occurrence, severity, and distress of common symptoms associated with cancer and its treatment. Purpose Identify subgroups of younger and older patients with distinct symptom burden profiles and evaluate for risk factors associated with these profiles. Methods Oncology outpatients (n = 1329) were dichotomized into younger (< 60 years) and older (≥ 60 years) groups. Data included demographic and clinical questionnaires and measures of global, cancer‐specific, and cumulative life stress, resilience, and coping. Memorial Symptom Assessment Scale evaluated the occurrence of 38 common symptoms. Separate latent class analyses were done within each age group to identify distinct symptom profiles. Differences among latent classes in demographic and clinical characteristics, stress, resilience, and coping were evaluated. Results In younger group (n = 730), four profiles were identified (i.e., All Low (28.8%), Moderate Physical and Lower Psychological (21.9%), Moderate Physical and Higher Psychological (34.6%), All High (14.7%)). Compared to All Low class, All High class was younger, more likely to be female, had a higher comorbidity burden, and a lower functional status, as well as higher stress and lower resilience scores. In the older group (n = 599), three profiles were identified (i.e., Low (34.4%), Moderate (47.9%), High (17.7%)). Compared to Low class, High class was more likely to be female, had a higher comorbidity burden and lower functional status, and received a more toxic chemotherapy regimen, as well as higher stress and lower resilience scores. Conclusion Study is the first to use latent class analysis to identify distinct symptom burden profiles in younger versus older oncology patients. In the younger group, differences in the occurrence of psychological symptoms differentiated among the symptom burden profiles. While some of the risk factors were similar, within the older group, patients in the High symptom burden class used a higher number of disengagement coping strategies.

Background: Treatment of patients with stages IIB to IV cutaneous melanoma with immune checkpoint inhibitors (ICIs) have resulted in dramatic improvements in mortality rates. With this rapid shift in treatment, significant gaps in knowledge exist regarding the effect of ICIs on patients’ symptom experiences. An in-depth characterization of inter-individual differences in symptom experiences and the identification of risk factors associated with a worse symptom experience will fill this gap and assist with early detection of ICI toxicity, guide symptom management, inform treatment decision-making, and refine ICI-symptom instrument development. Objectives: Across four ICI cycles for patients with stage IIB to IV cutaneous melanoma, study objectives are to describe the occurrence, severity, and distress of 53 symptoms; identify symptom clusters based on symptom dimensions (i.e., occurrence, severity, distress); evaluate the stability and consistency of symptom clusters across symptom dimensions and time; identify subgroups of patients with distinct symptom profiles; and evaluate for differences among the symptom profiles in demographic and clinical characteristics and levels of cancer-related stress, financial toxicity, and quality of life (QOL). Methods: This longitudinal, descriptive study is recruiting 300 adults with stage IIB to IV cutaneous melanoma who will start an ICI regimen and following them for four cycles. Participants complete demographic, stress, financial toxicity, and QOL questionnaires prior to their first and fourth ICI cycles. Prior to each cycle, participants report the occurrence, severity, and distress of 53 symptoms using a modified version of the Memorial Symptom Assessment Scale. Symptom clusters will be identified using exploratory factor analysis. Subgroups of participants with distinct symptom profiles will be identified across the ICI cycles using latent class and latent profile analysis. Differences among the latent classes will be evaluated using parametric and nonparametric tests. Results: Participant recruitment began in October 2025 and will be completed in June 2027. Discussion: This study will fill important knowledge gaps about inter-individual differences in risk factors for a worse symptom experience in adults with cutaneous melanoma receiving ICIs. This knowledge is critical to inform clinical assessment and monitoring of high-risk patients and to inform future biomarker research and intervention development.

BACKGROUND:Recent work suggests age discrimination can increase the risk for chronic pain among older adults. This study's aim was to examine the prevalence of exposure to ageism and its impact on chronic pain. METHODS:A nationally representative sample of 2029 adults ≥ 65 years old was recruited from the AmeriSpeak Panel. Participants were asked about five experiences of ageism. Older adults with chronic pain (pain on most/nearly every day in the past 3 months) reported pain self-efficacy, barriers to treatment, and use of specific therapies. Exposure to ageism was examined as a function of chronic pain status. Adjusted logistic and linear regressions were used to test associations between exposure to ageism and pain self-efficacy, likelihood of endorsing barriers to care, and use of pain treatments. RESULTS:More than half of older adults reported at least one prior exposure to ageism. Older adults with (vs. without) chronic pain were more likely to report exposure to ageism (OR: 1.62; 95% CI: 1.28-2.06). Among older adults with chronic pain, exposure to ageism was associated with lower pain self-efficacy and more perceived barriers to care (all p < 0.05). Finally, more exposure to ageism was associated with lower odds of using tai chi (OR: 0.89; 0.79-0.99), massage (OR: 0.93; 95% CI: 0.87-0.99), and cannabis (OR: 0.87; 95% CI: 0.77-0.99), though these associations did not remain statistically significant after correction for multiple testing. CONCLUSIONS:Participants with chronic pain were more likely than those without to report exposure to ageism. Among older adults with chronic pain, greater exposure to ageism was associated with less confidence in one's ability to manage pain, more barriers to treatment, and lower odds of using certain therapies. These results suggest that exposure to ageism may represent a barrier to successful chronic pain management in older adults.

OBJECTIVES:Shortness of breath is a common symptom in patients with cancer. However, the mechanisms that underlie this troublesome symptom are poorly understood. Therefore, this study aimed to determine the prevalence of and associated risk factors for shortness of breath in women prior to breast cancer surgery and identify associations between shortness of breath and polymorphisms for potassium channel genes. METHODS:Patients were recruited prior to breast cancer surgery and completed a self-report questionnaire on the occurrence of shortness of breath. Genotyping of single nucleotides polymorphism (SNPs) in potassium channel genes was performed using a custom array. Multiple logistic regression analyses were done to identify associations between the occurrence of shortness of breath and SNPs in ten candidate genes. RESULTS:Of the 398 patients, 11.1% reported shortness of breath. These patients had a lower annual household income, a higher comorbidity burden, and a lower functional status. After controlling for functional status, comorbidity burden, genomic estimates of ancestry and self-reported race and ethnicity, the genetic associations that remained significant in the multiple regression analyses were for potassium voltage-gated channel subfamily D (KCND2) rs12673992, potassium voltage-gated channel modifier subfamily S (KCNS1) rs4499491, and potassium two pore channel subfamily K (KCNK2) rs4411107. CONCLUSIONS:While these findings warrant replication, they suggest that alterations in potassium channel function may contribute to the occurrence of shortness of breath in women prior to breast cancer surgery.

Study purposes were to identify subgroups of patients with distinct co-occurring pain AND sleep disturbance profiles and evaluate for differences in demographic, clinical, pain, and sleep characteristics between the subgroups. Oncology outpatients receiving chemotherapy (n = 972) completed self-report questionnaires on various demographic and clinical characteristics. Pain and sleep disturbance were assessed six times over two cycles of chemotherapy, using the Brief Pain Inventory and the General Sleep Disturbance Scale, respectively. A joint latent profile analysis was performed using the six ratings of worst pain severity and sleep disturbance. Parametric and non-parametric tests were used to evaluate for differences in modifiable and non-modifiable risk factors between the profiles. Two subgroups of patients with distinct joint pain and sleep disturbance profiles were identified (i.e., Moderate Pain and Sleep Disturbance (Both Moderate, 53.4

[This corrects the article DOI: 10.1016/j.conctc.2018.09.004.].

The primary aims of this four week pilot randomized clinical trial (RCT) involving a targeted cognitive intervention (TCI, n = 25) compared to an expectancy matched active control intervention (EMACI, n = 24), in a sample of cancer survivors were to: determine recruitment and retention rates; evaluate preliminary efficacy to improve three objective measures of cognitive function (i.e., attention, working memory, multi-tasking); evaluate adherence rates for and satisfaction with the interventions, and evaluate for treatment-related adverse events (e.g., nausea, motion sickness). Cancer survivors were recruited from previous studies through email. Following a screening call, survivors who consented to participate were oriented to the study measures and procedures via Zoom. Survivors were randomized to the TCI or EMACI and mailed an iPad with the software for their specific intervention and the Adaptive Cognitive Evaluation Explorer (ACE-X, the objective measure of cognitive function). Survivors used the intervention for 25 min per day at least 5 days per week. Differences in objective measures of attention, working memory, and multi-tasking were evaluated using multilevel regression analyses. For the sustained attention measure, a significant cross-level interaction was found in favor of the TCI group. While improvements in multi-tasking occurred in both groups, while not statistically significant, the trend was larger for the TCI group. Equally important, in both groups, adherence with the intervention was high and adverse effects were minimal. These preliminary findings provide promising evidence of feasibility, acceptability, and efficacy that warrant evaluation in a RCT with a larger sample of cancer survivors.

Objectives Anxiety and depression are common symptoms in oncology patients undergoing chemotherapy. Study purpose was to evaluate for differences in severity of common symptoms (ie, fatigue, energy, sleep disturbance, cognitive function, pain) and quality of life (QOL) outcomes among three subgroups of oncology outpatients with distinct joint anxiety and depression profiles. Methods Oncology outpatients (N = 1328) completed measures of state anxiety and depression, six times over two cycles of chemotherapy. Latent profile analysis was done to identify subgroups of patients with distinct joint state anxiety AND depression profiles. Patients completed measures of trait anxiety, morning and evening fatigue, morning and evening energy, sleep disturbance, cognitive function, and pain, as well as generic and disease-specific measures of QOL at enrollment. Differences among the classes in symptom severity scores and QOL scores were evaluated using parametric and non-parametric tests. Results Three distinct joint anxiety AND depression profiles were identified and named: Low Anxiety and Low Depression (57.5%, Both Low), Moderate Anxiety and Moderate Depression (33.7%, Both Moderate), and High Anxiety and High Depression (8.8%, Both High). All of the symptom severity scores showed a “dose-response effect” (ie, as the joint anxiety AND depression profiles worsened, the severity of all of the symptoms increased). Likewise, for both the general and disease-specific QOL (except spiritual well-being) measures, all of the scores decreased as the joint anxiety AND depression profiles worsened. Compared to the Both Low classes, the other two classes reported lower scores for the spiritual well-being domain. Conclusions More than 40% of patients receiving chemotherapy experience moderate to high levels of both anxiety AND depression. These patients report an extremely high symptom burden and significant decrements in all domains of QOL. Implications for Nursing Practice Clinicians need to perform comprehensive assessments of depression and anxiety and other common symptoms and QOL outcomes during chemotherapy. In addition, referrals for targeted interventions are needed to manage multiple symptoms and improve patients’ QOL.

OBJECTIVES:The purposes were to identify subgroups of patients (n = 1324) with distinct quality of life (QOL) profiles and evaluate for differences among these subgroups in demographic and clinical characteristics, as well as levels of global, cancer-related, and cumulative life stress; resilience; and mental adjustment to cancer. METHODS:Prior to their second or third cycle of chemotherapy, patients completed a demographic questionnaire, measures of stress (Perceived Stress Scale, global stress), Impact of Event Scale-Revised (IES-R, cancer-related distress), Life Stressor Checklist-Revised (LSC-R, cumulative life stress); resilience (Connor-Davidson Resilience Scale [CDRS]), and mental adjustment (Mental Adjustment to Cancer Scale [MAC]). In addition, they completed the Multidimensional QOL Scale-Patient Version six times over two cycles of chemotherapy. Latent profile analysis was used to identify the distinct QOL profiles. Parametric and nonparametric tests were used to evaluate for differences in risk factors among the QOL profiles. RESULTS:Three distinct QOL profiles were identified (Low, 26.9%; Moderate, 44.7%; and High, 28.4%). Compared to the High QOL class, the other two classes were younger and more likely to be female and had a higher comorbidity burden and lower functional status. Differences among the QOL classes in PSS, IES-R, and LSC-R scores followed a similar pattern (Low > Moderate > High). Differences were found among the QOL classes in CDRS (Low < Moderate < High) and MAC (Low > Moderate > High) scores. CONCLUSIONS:This study is the first to describe interindividual variability in QOL outcomes among patients receiving chemotherapy. Levels of cancer-related stress reported by Low and Moderate QOL classes suggest that these patients meet the diagnostic criteria for posttraumatic stress and have levels of resilience below the normative score for the general population. IMPLICATIONS FOR NURSING PRACTICE:Given that stress and resilience are modifiable risk factors, this information can be used by clinicians to design tailored interventions to improve patients' QOL.

Significance: Evening fatigue and depressive symptoms are associated with several negative outcomes for patients with cancer. However, the contribution of BOTH fatigue and depressive symptoms to patient outcomes remains unknown. This study identified subgroups of patients with distinct joint evening fatigue AND depressive symptom profiles and evaluated for differences in demographic and clinical characteristics, levels of stress (i.e., global, cancer‐specific, and cumulative life) and resilience, and the severity of common symptoms. Methods: Outpatients ( n = 1334) completed the Lee Fatigue Scale and Center for Epidemiological Studies‐Depression scale six times over two cycles of chemotherapy. Demographic and clinical characteristics, stress and resilience, and other common symptoms were assessed at enrollment. Joint evening fatigue and depressive symptom profiles were identified using latent profile analysis. Profile differences were assessed using parametric and nonparametric tests. Results: Five profiles were identified (i.e., Low Evening Fatigue and Low Depression [Both Low: 20.0%], Moderate Evening Fatigue and Low Depression [Moderate Fatigue and Low Depression: 39.3%], Increasing and Decreasing Evening Fatigue and Depression [Both Increasing–Decreasing: 5.3%], Moderate Evening Fatigue and Moderate Depression [Both Moderate: 27.6%], High Evening Fatigue and High Depression [Both High: 7.8%]). Compared to the Both Low and Moderate Fatigue and Low Depression classes, the Both Moderate and Both High classes were less likely to be married, more likely to report depression, had a lower functional status, and had worse comorbidity profile. Both Moderate and Both High classes had higher levels of global, cancer‐specific, and cumulative life stress and lower resilience. Conclusions: Multiple risk factors for higher levels of evening fatigue AND depressive symptoms during chemotherapy were identified, including lower functional status, higher comorbidity burden, lower levels of resilience, and higher global, cancer‐specific, and cumulative life stress. These risk factors may be used to identify patients at greatest risk for poorer outcomes and to prescribe interventions to decrease these symptoms.

BackgroundDetailed information on patient characteristics and symptom burden associated with multimorbidity in oncology patients is extremely limited. Purposes were to determine the prevalence of low (<= 2) and high (>= 3) multimorbidity in a sample of oncology outpatients (n = 1343) undergoing chemotherapy and evaluate for differences between the two multimorbidity groups in demographic and clinical characteristics; the occurrence, severity, and distress of 38 symptoms; and the stability and consistency of symptom clusters.MethodsUsing the Self-Administered Comorbidity Questionnaire, patients were classified into low and high multimorbidity groups. Memorial Symptom Assessment Scale was used to assess the occurrence, severity, and distress of 38 symptoms prior to the patients' second or third cycle of chemotherapy. For each multimorbidity group, symptom clusters based on occurrence rates were identified using exploratory factor analysis.ResultsCompared to the low group (61.4%), patients in the high group (38.6%) were older, had fewer years of education, were less likely to be married or partnered, less likely to be employed, and had a lower annual income. In addition, they had a higher body mass index, poorer functional status, were a longer time since their cancer diagnosis, and were more likely to have received previous cancer treatments and have metastatic disease. Patients in the low and high groups reported 12.7 (+/- 6.7) and 15.9 (+/- 7.5) concurrent symptoms, respectively. Eight and seven symptom clusters were identified for the low and high groups, respectively. Psychological, gastrointestinal, weight gain, hormonal, and respiratory clusters were stable across multimorbidity groups. Weight gain and respiratory clusters were consistent. Three unstable clusters were identified in the low group and two in the high group.ConclusionsFindings suggest that higher multimorbidity is associated with various social determinants of health and a higher symptom burden. Differences between multimorbidity groups may be related to aging, treatments, and/or comorbid conditions.

OBJECTIVES:To identify distinct morning and evening fatigue profiles in patients with gynecologic cancers and evaluate for differences in demographic and clinical characteristics, common symptoms, and quality-of-life outcomes. SAMPLE & SETTING:Outpatients with gynecologic cancers (N = 233) were recruited before their second or third cycles of chemotherapy at four cancer centers in San Francisco Bay and New York. METHODS & VARIABLES:The Lee Fatigue Scale was completed six times over two cycles of chemotherapy in the morning and in the evening. Latent profile analysis was used to identify distinct morning and evening fatigue profiles. RESULTS:Four distinct morning and two distinct evening fatigue classes were identified. Common risk factors for morning and evening fatigue included younger age, higher body mass index, lower functional status, and higher comorbidity burden. Patients in the worst morning and evening fatigue classes reported higher levels of anxiety, depression, and sleep disturbance; lower levels of energy and cognitive function; and poorer quality of life. IMPLICATIONS FOR NURSING:Clinicians can use this information to identify higher-risk patients and develop individualized interventions for morning and evening fatigue.

Background Decrements in energy are a significant problem associated with chemotherapy. To date, no study examined the variability of energy in patients with gynecologic cancers. Objective To identify distinct morning and evening energy profiles in patients with gynecologic cancers and evaluate for differences in demographic and clinical characteristics, other common symptoms, and quality-of-life (QOL) outcomes. Methods A sample of 232 patients with gynecologic cancers completed questionnaires 6 times over 2 cycles of chemotherapy. Latent profile analysis was used to identify distinct morning and evening energy profiles. Differences in demographic and clinical characteristics, other common symptoms, and QOL outcomes were evaluated using parametric and nonparametric tests. Results Three distinct morning (ie, high [9.2%], low [63.1%], very low [27.1%]) and 2 distinct evening (moderate [30.6%], very low [69.4%]) energy classes were identified. Clinical risk factors associated with the worst morning energy profiles included lower functional status and a higher comorbidity burden. Less likely to exercise on a regular basis was the only characteristic associated with the worst evening energy profile. For both symptoms, the worst profiles were associated with higher levels of depression and sleep disturbance, lower levels of cognitive function, and poorer QOL. Conclusions Approximately 70% of patients with gynecologic cancers experienced decrements in morning and evening energy. The study identified modifiable risk factors associated with more decrements in morning and evening energy. Implications for Practice Clinicians can use these findings to identify higher-risk patients and develop individualized energy conservation interventions for these vulnerable patients.

OBJECTIVES: To evaluate for associations between the occurrence of palpitations reported by women prior to breast cancer surgery and single nucleotide polymorphisms (SNPs) for neurotransmitter genes. SAMPLE & SETTING: A total of 398 women, who were scheduled for unilateral breast cancer surgery, provided detailed information on demographic and clinical characteristics and the occurrence of palpitations prior to breast cancer surgery. METHODS & VARIABLES: The occurrence of palpitations was assessed using a single item (i.e., "heart races/pounds" in the past week ["yes"/"no"]). Blood samples were collected for genomic analyses. Multiple logistic regression analyses were used to identify associations between the occurrence of palpitations and variations in neurotransmitter genes. RESULTS: Nine SNPs and two haplotypes among 11 candidate genes were associated with the occurrence of palpitations. These genes encode for a number of neurotransmitters and/or their receptors, including serotonin, norepinephrine, dopamine, gamma- amino butyric acid, Substance P, and neurokinin. IMPLICATIONS FOR NURSING: These findings suggest that alterations in a variety of neurotransmitters contribute to the development of this symptom.

Background: Interindividual variability in oncology patients' symptom experiences poses significant challenges in prioritizing symptoms for targeted intervention(s). In this study, computational approaches were used to unbiasedly characterize the heterogeneity of the symptom experience of oncology patients to elucidate symptom patterns and drivers of symptom burden. Methods: Severity ratings for 32 symptoms on the Memorial Symptom Assessment Scale from 3088 oncology patients were analyzed. Gaussian Graphical Model symptom networks were constructed for the entire cohort and patient subgroups identified through unsupervised clustering of symptom co-severity patterns. Network characteristics were analyzed and compared using permutation-based statistical tests. Differences in demographic and clinical characteristics between subgroups were assessed using multinomial logistic regression. Results: Network analysis of the entire cohort revealed three symptom clusters: constitutional, gastrointestinal-epithelial, and psychological. Lack of energy was identified as central to the network which suggests that it plays a pivotal role in patients' overall symptom experience. Unsupervised clustering of patients based on shared symptom co-severity patterns identified six patient subgroups with distinct symptom patterns and demographic and clinical characteristics. The centrality of individual symptoms across the subgroup networks differed which suggests that different symptoms need to be prioritized for treatment within each subgroup. Age, treatment status, and performance status were the strongest determinants of subgroup membership. Conclusions: Computational approaches that combine unbiased stratification of patients and in-depth modeling of symptom relationships can capture the heterogeneity in patients' symptom experiences. When validated, the core symptoms for each of the subgroups and the associated clinical determinants may inform precision-based symptom management.

Subgroup analyses conducted among U.S. national survey data have estimated that 27 to 34% of adults aged ≥65 years have chronic pain. However, none of these studies focused specifically on older adults or examined disparities in chronic pain in those aged ≥65 years. To obtain current information on the prevalence and sociodemographic correlates of chronic pain in U.S. older adults, a cross-sectional analysis was conducted of data collected from 3,505 older adults recruited from the AmeriSpeak Panel. Chronic pain was defined as pain on most or every day in the last 3 months. Nationally representative chronic pain prevalence estimates were computed by incorporating study-specific survey design weights. Logistic regression analyses evaluated differences in chronic pain status as a function of sociodemographic characteristics (eg, gender, race/ethnicity, and socioeconomic status). The results indicated that 37.8% of older adults reported chronic pain. Compared with White older adults, Black (odds ratio [OR] = .6, 95% CI: .4-.8) and Asian (OR = .2, 95% CI: .1-.8) older adults were less likely to report chronic pain. The prevalence of chronic pain was also lower among those who reported the highest (vs lowest) household income (OR = .6, 95% CI: .4-.8). Those who were not working due to disability (vs working as a paid employee) were more likely to report chronic pain (OR = 3.2, 95% CI: 2.1-5.0). This study was the first to recruit a large, representative sample of older adults to estimate the prevalence of chronic pain and extends prior work by identifying subgroups of older adults that are disproportionately affected. PERSPECTIVE: This study was the first to estimate the prevalence and sociodemographic correlates of chronic pain among a large, representative sample of U.S. older adults. The findings underscore the high prevalence of chronic pain and highlight disparities in chronic pain prevalence rates among this historically understudied population.