Psychoneurological symptom cluster trajectories in individuals treated for early-stage breast cancer.

BACKGROUND/PURPOSE: The psychoneurological (PN) symptom cluster has been defined in the literature as anxiety, depression, fatigue, sleep disturbance, and pain. PN symptoms are influenced by cancer and its treatment as well as biological and psychosocial factors. The purpose of this analysis was to describe temporal patterns of the PN symptom cluster severity in breast cancer survivors over the year following initial surgical intervention and investigate the time-dependent effect of treatment modality on symptom severity. METHODS: In a prospective longitudinal study, symptom data were collected from individuals with early-stage breast cancer 48 h after initial surgery and at monthly intervals for the subsequent 12 months using the PROMIS®-29 subscales for anxiety, depression, fatigue, sleep disturbance, and pain. Applying group-based trajectory modeling, we classified participants into subgroups with similar temporal patterns of PN symptom cluster severity and included treatment modality as a time-dependent covariate. RESULTS: Across 353 participants (mean age 60.10 ± 11.9 years, 88.95% white, 66.57% undergoing segmental mastectomies), four distinct trajectory subgroups (mild [47.6%; n = 168], moderate [28.3%; n = 100], severe [15.9%; n = 56], and most severe increasing [8.2%; n = 29]) were revealed for PN symptom cluster severity. Chemotherapy was associated with greater severity in all symptom severity subgroups, while radiation was associated with greater symptom severity in the mild and most severe increasing subgroups. CONCLUSIONS AND IMPLICATIONS: A subgroup of individuals with early-stage breast cancer experienced persistent severe PN symptoms. Future research should focus on psychosocial, biological, and disease-related characteristics of individuals in the most severe symptom group to inform preventative treatments and effective interventions.

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

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

Postdischarge Nausea and Vomiting and Co-occurring Symptoms in Women Following Breast Cancer Surgery.

PURPOSE: The purpose of this study was to investigate the influence of potential co-occurring symptoms, including fatigue, sleep disturbance, anxiety, depressive symptoms, and pain, on the incidence of postdischarge nausea (PDN) measured two days following discharge to home after surgery for breast cancer. DESIGN: This study used a prospective, cross-sectional, observational design. METHODS: The sample was 334 women aged 27 to 88 years of age. Demographic data were collected from the patient and the medical record before surgery. Symptom data were collected 48 hours following surgery using the Patient Reported Outcome Measurement System (PROMIS) and numerical nausea and pain scales. FINDINGS: Eighty-five (25.4%) of study participants reported some nausea two days after discharge. Study participants who experienced PDN frequently described that it occurred after they left the hospital to drive home following their surgery. Unadjusted odds ratios showed the presence of co-occurring symptoms of anxiety, fatigue, sleep disturbance, and pain were all significantly associated with the presence of nausea 48 hours following surgery. Other significant factors associated with (PDN) were history of motion sickness, history of pregnancy-induced nausea, use of opioids, and type of surgery. CONCLUSIONS: Same-day surgery nurses providing postoperative education for women following surgery for breast cancer should explain to patients that nausea may occur after they are discharged, especially those with known motion sickness. In addition, patients should be informed that other symptoms, especially fatigue, sleep disturbance, and anxiety, may co-occur.

Factors associated with sleep disturbances in women undergoing treatment for early-stage breast cancer.

PURPOSE: The purpose of this study was to examine factors associated with sleep disturbance in women receiving adjuvant therapy for breast cancer. METHODS: This study employed a cross-sectional design using data collected at 3 months post-surgery from an ongoing longitudinal parent study. Participant data were divided into adjuvant treatment groups (chemotherapy, radiation, and aromatase inhibitors) and no adjuvant treatment groups. Symptoms were measured using patient self-report measures. Analysis of variance was used to assess between adjuvant treatment group differences in sleep disturbance. Regression analysis was performed to assess the relationship between sleep disturbance and other symptoms within adjuvant treatment groups. RESULTS: The sample included 156 women diagnosed with early-stage breast cancer. There were significant differences in levels of reported sleep disturbance between treatment groups (p = 0.049), with significantly higher levels of sleep disturbances in those receiving radiation compared to those receiving no adjuvant treatment (p = 0.038) and in those receiving chemotherapy and those receiving no adjuvant treatment (p = 0.027). Increased sleep disturbance was found to be a significant predictor for increased pain severity, nausea severity, anxiety, depressive symptoms, fatigue, decreased physical function, and decreased ability to participate in social roles and activities. Co-occurring symptoms with sleep disturbance differed between adjuvant treatment groups. Sleep disturbance was also associated with younger age (p = 0.008). CONCLUSIONS: Patients undergoing chemotherapy or radiation for breast cancer report higher levels of sleep disturbance than those not receiving adjuvant therapy. Sleep disturbance is associated with other symptoms experienced by patients with cancer and thus requires continual assessment and future research into effective interventions.

The Psychoneurologic Symptom Cluster and Its Association With Breast Cancer Genomic Instability.

OBJECTIVES: To phenotype the psychoneurologic (PN) symptom cluster in individuals with metastatic breast cancer and associate those phenotypes with individual characteristics and cancer genomic variables from circulating tumor DNA. SAMPLE & SETTING: This study included 201 individuals with metastatic breast cancer recruited in western Pennsylvania. METHODS & VARIABLES: A descriptive, cross-sectional design was used. Symptom data were collected via the MD Anderson Symptom Inventory, and cancer genomic data were collected via ultra-low-pass whole-genome sequencing of circulating tumor DNA from participant blood. RESULTS: Three distinct PN symptom phenotypes were described in a population with metastatic breast cancer: mild symptoms, moderate symptoms, and severe mood-related symptoms. Breast cancer TP53 deletion was significantly associated with membership in a moderate to severe symptoms phenotype (p = 0.013). IMPLICATIONS FOR NURSING: Specific cancer genomic changes associated with increased genomic instability may be predictive of PN symptoms. This finding may enable proactive treatment or reveal new therapeutic targets for symptom management.

The Cancer Genomic Integration Model for Symptom Science (CGIMSS): A Biopsychosocial Framework.

Current nursing research has characterized symptom clusters and trajectories in individuals with breast cancer. The existing literature describes the relationship between symptoms and biological variables and the potential moderating effects of individual and social factors. The genomic profiling of breast cancer has also been an area of much recent research. Emerging evidence indicates that incorporating cancer genomics into symptom science research can aid in the prognostication of symptoms and elucidate targets for symptom management interventions. The aim of this paper is to outline a model to integrate cancer genomics into symptom science research, illustrated using breast cancer and psychoneurological (PN) symptoms as an example. We present a review of the current literature surrounding breast cancer genomics (specifically cancer genomic instability) and the biological underpinnings of the PN symptom cluster. Advances in both of these areas indicate that inflammation may serve as the bridge between cancer genomics and the PN symptom cluster. We also outline how the integration of cancer genomics into symptom science research synergizes with current research of individual and social factors in relation to symptoms. This model aims to provide a framework to guide future biopsychosocial symptom science research that can elucidate new predictive methods and new targets for intervention.

Epigenomic Links Between Social Determinants of Health and Symptoms: A Scoping Review.

Social determinants of health (SDoH) impact health and wellness. The link between SDoH and adverse health outcomes, including symptom occurrence and severity, may be explained by an individual's physiologic response to one or more SDoH. One potential mechanism underlying this physiologic response linking SDoH and symptoms is the dynamic epigenome. The purpose of this scoping review of the literature was to examine differential susceptibility for symptoms by identifying and summarizing research linking SDoH and symptoms through epigenomic mechanisms. PubMed was searched to identify empirical research where at least one SDoH was an independent or dependent variable, at least one symptom was investigated, and the investigation included an epigenomic measure. Of the 484 articles initially retrieved, after thorough vetting, 41 articles met eligibility. The most studied symptom was depressive symptoms followed by anxiety, cognitive function, sleep dysfunction, and pain. The most frequently studied SDoH were: 1) stress, particularly early life stress and acculturative stress; and 2) trauma, predominantly childhood trauma. DNA methylation and telomere length were the most studied epigenomic measures. Four genes (SLC6A4, BDNF, NR3C1, OXTR) had evidence from multiple studies and across methodological approaches linking SDoH to symptoms. This review supports the inclusion of epigenomic approaches to better understand the link between SDoH and symptoms and provides evidence that SDoH impact telomere length and the methylation of genes involved in neurotransmitter signaling, neuronal survival, behavior, inflammation and stress response.

Operationalising the Family-Friendly Medical Workplace and the Development of FAM-MED, a Family-Friendly Self-Audit Tool for Medical Systems: A Delphi Consensus.

Globally, the call for Family-Friendly (FF) workplaces is loud and clear. However, this call is inaudible in medical workplaces, despite both well-established benefits of FF workplaces across businesses and well-known effects of work-family conflict on the well-being and practice of doctors. We aimed to use the Delphi consensus methodology to: (i) operationalise the Family-Friendly medical workplace and (ii) develop a Family-Friendly Self-Audit tool for medical workplaces. The expert medical Delphi panel was deliberatively recruited to capture a breadth of professional, personal, and academic expertise, diversity of age (35-81), life stage, family contexts and lived experience of dual commitments to work and family, and diversity of work settings and positions. Results reflected the inclusive and dynamic nature of the doctor's family and the need to adopt a family life cycle approach to FF medical workplaces. Key processes for implementation include holding firms to zero discrimination; flexibility and openness to dialogue and feedback; and a mutual commitment between the doctor and the department lead to best meet the doctor's individualised needs while still ensuring optimal patient care and team support and cohesion. We hypothesise that the Department Head may be the key to implementation but recognise the workforce constraints to realising these aspirational systemic shifts. It is time we acknowledge that doctors have families, to narrow the gap between identifying as a partner, mother, father, daughter, son, grandparent, and identifying as a doctor. We affirm the right to be both good doctors and good family members.

Predictors of Unrelieved Symptoms in All of Us Research Program Participants With Chronic Conditions.

CONTEXT: Over half of American adults are diagnosed with a chronic condition, with an increasing prevalence being diagnosed with multiple chronic conditions. These adults are at higher risk for having unrelieved, co-occurring symptoms, known as symptom clusters. OBJECTIVES: To identify symptom phenotypes of patients diagnosed with four common chronic conditions, specifically, cancer, chronic obstructive pulmonary disease, heart failure, and/or type 2 diabetes mellitus, and to understand factors that predict membership in symptomatic phenotypes. METHODS: We conducted a retrospective, cross-sectional analysis using participant responses (N=14,127) to All of Us Research Program, a National Institutes of Health biomedical database, survey questions. We performed hierarchical clustering to generate symptom phenotypes of fatigue, emotional distress, and pain and used multinomial regression to determine if demographic, healthcare access and utilization, and health-related variables predict symptom phenotype. RESULTS: Four phenotypes, one asymptomatic or mildly symptomatic and three highly symptomatic (characterized by severe symptoms, severe pain, and severe emotional distress), were identified. The percentage of participants belonging to the severe symptoms phenotype increased with the number of chronic conditions. Most notably, foregoing or delaying medical care and rating mental health as poor or fair increased the odds of belonging to a highly symptomatic phenotype. CONCLUSION: We found meaningful relationships between demographic, healthcare access and utilization, and health-related factors and symptom phenotypes. With the increasing trends of American adults with one or more chronic conditions and a demand to individualize care in the precision health era, it is critical to understand the factors that lead to unrelieved symptoms.