John Merriman

Abstract

Objective: Seriously ill adults with multiple chronic conditions (MCC) who receive palliative care may benefit from improved symptom burden, health care utilization and cost, caregiver stress, and quality of life. To guide research involving serious illness and MCC, palliative care can be integrated into a conceptual model to develop future research studies to improve care strategies and outcomes in this population. Methods: The adapted conceptual model was developed based on a thorough review of the literature, in which current evidence and conceptual models related to serious illness, MCC, and palliative care were appraised. Factors contributing to patients’ needs, services received, and service-related variables were identified. Relevant patient outcomes and evidence gaps are also highlighted. Results: Fifty-eight articles were synthesized to inform the development of an adapted conceptual model including serious illness, MCC, and palliative care. Concepts were organized into 4 main conceptual groups, including Factors Affecting Needs (sociodemographic and social determinants of health), Factors Affecting Services Received (health system; research, evidence base, dissemination, and health policy; community resources), Service-Related Variables (patient visits, service mix, quality of care, patient information, experience), and Outcomes (symptom burden, quality of life, function, advance care planning, goal-concordant care, utilization, cost, death, site of death, satisfaction). Discussion: The adapted conceptual model integrates palliative care with serious illness and multiple chronic conditions. The model is intended to guide the development of research studies involving seriously ill adults with MCC and aid researchers in addressing relevant evidence gaps.

Abstract

Purpose: Women with breast cancer report varying frequencies of cognitive problems during adjuvant systemic therapy. This variability suggests latent subgroups. Therefore, we identified latent subgroups of self-reported cognitive problems among postmenopausal women with and without breast cancer. We explored associations between membership in these subgroups and (a) demographic, clinical, and symptom characteristics and (b) variations in candidate gene polymorphisms. Methods: We evaluated frequency of cognitive problems using the Patient Assessment of Own Functioning Inventory. Growth mixture modeling identified latent subgroups over 18 months of adjuvant systemic therapy and at matched time points for women without cancer (N = 331). We evaluated for differences among subgroups in demographic, clinical, and symptom characteristics and in 41 single nucleotide polymorphisms in 10 candidate genes involved in DNA repair and oxidative stress pathways (n = 199). We modeled associations between genotypes and subgroup membership using multinomial logistic regression. Results: We identified three latent subgroups: more frequent, persistent, and almost never. Receipt of chemotherapy plus anastrozole, depressive symptoms, and baseline neuropathic symptoms increased the odds of belonging to the more frequent subgroup. Anxiety and depressive symptoms increased the odds of belonging to the persistent subgroup. With covariates controlled for, carrying the ERCC5 rs873601 G minor allele increased the odds of reporting more frequent cognitive problems. Conclusions: Chemotherapy plus anastrozole, depressive symptoms, and presence of neuropathic symptoms may predict more frequent cognitive problems during systemic therapy that later resolve. Mood dysregulation before therapy may predict persistent cognitive problems during therapy. ERCC5 genotype may influence frequency of cognitive problems after controlling for these risk factors.

Abstract

Incorporating biologically based data into symptom science research can contribute substantially to understanding commonly experienced symptoms across chronic conditions. The purpose of this literature review was to identify functional polymorphisms associated with common symptoms (i.e., pain, sleep disturbance, fatigue, affective and cognitive symptoms) with the goal of identifying a parsimonious list of functional genetic polymorphisms with evidence to advocate for their inclusion in symptom science research. PubMed was searched to identify genes and functional polymorphisms associated with symptoms across chronic conditions, revealing eight functional genetic polymorphisms in seven different genes that showed evidence of association with at least three or more symptoms and/or symptom clusters: BDNF rs6265, COMT rs4680, FKBP5 rs3800373, IL-6 rs1800795, NFKB2 rs1056890, SLC6A4 5-HTTLPR+rs25531, and TNFA rs1799964 and rs1800629. Of these genes, three represent protein biomarkers previously identified as common data elements for symptom science research (BDNF, IL-6, and TNFA), and the polymorphisms in these genes identified through the search are known to impact secretion or level of transcription of these protein biomarkers. Inclusion of genotype data for polymorphisms offers great potential to further advance scientific knowledge of the biological basis of individual symptoms and symptom clusters across studies. Additionally, these polymorphisms have the potential to be used as targets to optimize precision health through the identification of individuals at risk for poor symptom experiences as well as the development of symptom management interventions.

Abstract

OBJECTIVES: This study identified women with unique trajectories of executive function, concentration, and visual working memory before and during adjuvant therapy for breast cancer, and examined phenotypic and genotypic predictors associated with subgroups. SAMPLE & SETTING: 399 postmenopausal women, of whom 288 were women with early-stage breast cancer and 111 were women without breast cancer, matched on age and years of education to the women with breast cancer, and all at an urban cancer center. METHODS & VARIABLES: A repeated-measures design was used; assessments occurred before adjuvant therapy and every six months post-therapy initiation. Group-based trajectory modeling determined subgroups. Multinomial logistic regression identified phenotypic and genotypic characteristics. RESULTS: Three executive function and concentration trajectory subgroups were identified: low, moderate, and high; two visual working memory subgroups were identified: low and high. IMPLICATIONS FOR NURSING: Advancing age, greater pretherapy fatigue, and poorer pretherapy cognitive function are associated with the low subgroups. DNA repair and oxidative stress mechanisms may be involved in the cognitive changes that women experience.

Abstract

Objective: In a sample of 368 postmenopausal women, we (1) determined within-cohort and between-cohort relationships between adjuvant systemic therapy for breast cancer and self-reported cognitive function during the first 18 months of therapy and (2) evaluated the influence of co-occurring symptoms, neuropsychological function, and other covariates on relationships. Methods: We evaluated self-reported cognitive function, using the Patient Assessment of Own Functioning Inventory (PAOFI), and potential covariates (e.g., co-occurring symptom scores and neuropsychological function z-scores) in 158 women receiving aromatase inhibitor (AI) therapy alone, 104 women receiving chemotherapy followed by AI therapy, and 106 non-cancer controls. Patients were assessed before systemic therapy and then every 6 months, for a total of four assessments over 18 months. Controls were assessed at matched time points. Mixed-effects modeling was used to determine longitudinal relationships. Results: Controlling for covariates, patients enrolled before chemotherapy reported poorer global cognitive function (p < 0.001), memory (p < 0.001), language and communication (p < 0.001), and sensorimotor function (p = 0.002) after chemotherapy. These patients reported poorer higher-level cognitive and intellectual functions from before chemotherapy to 12 months after initiation of AI therapy (p < 0.001). Higher levels of depressive symptoms (p < 0.001), anxiety (p < 0.001), and fatigue (p = 0.040) at enrollment were predictors of poorer cognitive function over time. PAOFI total score was a predictor of executive function (p = 0.048) and visual working memory (p = 0.005) z-scores, controlling for covariates. Conclusions: Findings provide further evidence of poorer self-reported cognitive function after chemotherapy and of relationships between co-occurring symptoms and cognitive changes. AI therapy alone does not have an impact on self-reported cognitive function.

Abstract

Purpose: Previous research has explored occupational activity of breast cancer survivors but has not examined the influence of occupational level on symptoms prospectively. The purpose of this study was to examine the relationship between occupational classification and changes in mood and symptom burden for postmenopausal breast cancer survivors during the first year of anastrozole therapy. Methods: This was an exploratory secondary analysis in 49 postmenopausal women receiving anastrozole therapy for early-stage breast cancer. Participants reported their occupation at baseline and completed self-report questionnaires measuring mood and symptom burden at baseline, 6 months, and 12 months. Occupation was classified according to four major skill levels delineated by the International Standard Classification of Occupations (ISCO). Results: Breast cancer survivors employed at occupational skill levels 1 through 3 reported significantly higher depressive symptoms, fatigue, and total symptoms on average than those employed at ISCO skill level 4. After adjusting for multiple comparisons, this pattern remained for the musculoskeletal, vasomotor, and gastrointestinal symptom subscales. Conclusions: Breast cancer survivors employed at lower skill levels (i.e., ISCO 1–3) reported poorer mood and greater symptom burden than breast cancer survivors employed at a higher skill level (i.e., ISCO 4). Assessing baseline occupation of occupationally active breast cancer survivors may improve understanding of the association between types of occupations and mood and symptom trajectories and may inform development of interventions to mitigate symptom severity in order to help breast cancer survivors maintain optimal occupational function and adherence to therapy.

Abstract

Purpose of the research: Evaluate for associations between variations in genes involved in catecholaminergic, gamma-aminobutyric acid (GABA)-ergic, and serotonergic mechanisms of neurotransmission and attentional function latent classes. Patients and methods: This descriptive, longitudinal study was conducted at two radiation therapy departments. The sample included three latent classes of individuals with distinct trajectories of self-reported attentional function during radiation therapy, who were previously identified using growth mixture modeling among 167 oncology patients and 85 of their family caregivers. Multivariable models were used to evaluate for genotypic associations of neurotransmission genes with attentional function latent class membership, after controlling for covariates. Results: Variations in catecholaminergic (i.e., ADRA1D rs4815675, SLC6A3 rs37022), GABAergic (i.e., SLC6A1 rs2697138), and serotonergic (i.e., HTR2A rs2296972, rs9534496) neurotransmission genes were significant predictors of latent class membership in multivariable models. Conclusions: Findings suggest that variations in genes that encode for three distinct but related neurotransmission systems are involved in alterations in attentional function. Knowledge of both phenotypic and genetic markers associated with alterations in attentional function can be used by clinicians to identify patients and family caregivers who are at higher risk for this symptom. Increased understanding of the genetic markers associated with alterations in attentional function may provide insights into the underlying mechanisms for this significant clinical problem.

Abstract

Pain, fatigue, sleep disturbance, and depression are common and frequently co-occurring symptoms in oncology patients. This symptom cluster is often attributed to the release of proinflammatory cytokines. The purposes of this study were to determine whether distinct latent classes of patients with breast cancer (n = 398) could be identified based on their experience with this symptom cluster, whether patients in these latent classes differed on demographic and clinical characteristics and whether variations in cytokine genes were associated with latent class membership. Three distinct latent classes were identified: “all low” (61.0%), “low pain and high fatigue” (31.6%), “all high” (7.1%). Compared to patients in the all low class, patients in the all high class were significantly younger, had less education, were more likely to be non-White, had a lower annual income, were more likely to live alone, had a lower functional status, had a higher comorbidity score, and had more advanced disease. Significant associations were found between interleukin 6 (IL6) rs2069845, IL13 rs1295686, and tumor necrosis factor alpha rs18800610 and latent class membership. Findings suggest that variations in pro- and anti-inflammatory cytokine genes are associated with this symptom cluster in breast cancer patients.

Abstract

The purpose of this study was to evaluate for differences in variations in pro- and anti-inflammatory cytokine genes between participants who were classified as having low and high levels of morning and evening fatigue and to evaluate for differences in phenotypic characteristics between these two groups. In a sample of 167 oncology outpatients with breast, prostate, lung, or brain cancer and 85 of their family caregivers, growth mixture modeling was used to identify latent classes of individuals based on ratings of morning and evening fatigue obtained prior to, during, and for 4 months following completion of radiation therapy. Differences in single nucleotide polymorphisms and haplotypes in 15 cytokine genes were evaluated between the latent classes. Multiple logistic regression was used to assess the effect of phenotypic and genotypic characteristics on morning and evening fatigue class membership. Associations were found between morning fatigue and number of comorbidities as well as variations in tumor necrosis factor alpha (TNFA) rs1800629 and rs3093662. Evening fatigue was associated with caring for children at home and variations in interleukin 4 (IL4) rs2243248 and TNFA rs2229094. Younger age and lower performance status were associated with both morning and evening fatigue. These findings suggest that inflammatory mediators are associated with the development of morning and evening fatigue. However, because different phenotypic characteristics and genomic markers are associated with diurnal variations in fatigue, morning and evening fatigue may be distinct but related symptoms.

Abstract

Purpose: Anxiety is common among cancer patients and their family caregivers (FCs) and is associated with poorer outcomes. Recently, associations between inflammation and anxiety were identified. However, the relationship between variations in cytokine genes and anxiety warrants investigation. Therefore, phenotypic and genotypic characteristics associated with trait and state anxiety were evaluated in a sample of 167 oncology patients with breast, prostate, lung, or brain cancer and 85 of their FCs. Methods: Using multiple regression analyses, the associations between participants’ demographic and clinical characteristics as well as variations in cytokine genes and trait and state anxiety were evaluated. Results: In the bivariate analyses, a number of phenotypic characteristics were associated with both trait and state anxiety (e.g., age, functional status). However, some associations were specific only to trait anxiety (e.g., number of comorbid conditions) or state anxiety (e.g., participation with a FC). Variations in three cytokine genes (i.e., interleukin (IL) 1 beta, IL1 receptor 2 (IL1R2), nuclear factor kappa beta 2 (NFKB2)) were associated with trait anxiety, and variations in two genes (i.e., IL1R2, tumor necrosis factor alpha (TNFA)) were associated with state anxiety. Conclusions: These findings suggest that both trait and state anxiety need to be assessed in oncology patients and their FCs. Furthermore, variations in cytokine genes may contribute to higher levels of anxiety in oncology patients and their FCs.