Fatigue after breast cancer treatment: Biobehavioral predictors of fatigue trajectories.
ABSTRACT: OBJECTIVE:Fatigue is a common side effect of cancer treatment, but there is considerable variability in fatigue severity and persistence among survivors. This study aimed to characterize longitudinal trajectories of fatigue after breast cancer treatment and to identify predictors of varying fatigue trajectories. METHODS:Women (N = 191) from the Mind-Body Study completed assessments after primary treatment for early stage breast cancer and at regular follow-ups that occurred up to 6 years after treatment (M = 4.3 years). Growth mixture models were used to characterize fatigue trajectories, and demographic, medical, and biobehavioral risk factors were examined as predictors of trajectory group. RESULTS:Five trajectories were identified, characterized as High, Recovery, Late, Low, and Very Low fatigue. The High and Recovery groups (40% of sample) evidenced elevated fatigue at posttreatment that declined in Recovery but persisted in the High group. In bivariate analyses, trajectory groups differed significantly on depressive symptoms, sleep disturbance, childhood adversity, body mass index, and the inflammatory marker soluble TNF receptor type II, which were higher in the High and/or Recovery groups. In multivariate models, depressive symptoms and childhood adversity distinguished High and Recovery from other groups. Rates of chemotherapy were higher in the Recovery than in the High or Late group, whereas rates of endocrine therapy were higher in the High than in the Recovery group. CONCLUSIONS:There are distinct longitudinal trajectories of fatigue after breast cancer treatment. Psychological factors are strongly associated with adverse fatigue trajectories, and together with treatment exposures may increase risk for cancer-related fatigue. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Project description:Cancer-related fatigue is one of the most frequent complaints among breast cancer survivors, with a major negative impact on general life. However, the etiology behind this syndrome is still unraveled. Gene expression analysis was performed on whole blood samples from breast cancer survivors classified as either fatigued or non-fatigued at two consecutive time points. The analysis identified several gene sets concerning plasma and B cell pathways as different between the fatigue and non-fatigue groups, suggesting that a deregulation in these pathways might underlie the fatigue syndrome. The fatigue group also showed a higher mean level of leucocytes, lymphocytes and neutrophiles compared with the non-fatigue group, thus further implicating the immune system in the biology behind the fatigue syndrome. Keywords: Blood RNA and late side effects Breast cancer survivors treated with adjuvant radiotherapy at The Norwegian Radium Hospital between 1998 and 2002 were invited to participate in a study assessing late treatment effects in breast cancer survivors. In the present study, gene expression analysis was performed on whole blood samples from breast cancer survivors with and without persistent fatigue, to look for different expression patterns that might shed light on the biology behind cancer-related fatigue.
Project description:Cancer-related fatigue is one of the most frequent complaints among breast cancer survivors, with a major negative impact on general life. However, the etiology behind this syndrome is still unraveled. Gene expression analysis was performed on whole blood samples from breast cancer survivors classified as either fatigued or non-fatigued at two consecutive time points. The analysis identified several gene sets concerning plasma and B cell pathways as different between the fatigue and non-fatigue groups, suggesting that a deregulation in these pathways might underlie the fatigue syndrome. The fatigue group also showed a higher mean level of leucocytes, lymphocytes and neutrophiles compared with the non-fatigue group, thus further implicating the immune system in the biology behind the fatigue syndrome. Keywords: Blood RNA and late side effects Overall design: Breast cancer survivors treated with adjuvant radiotherapy at The Norwegian Radium Hospital between 1998 and 2002 were invited to participate in a study assessing late treatment effects in breast cancer survivors. In the present study, gene expression analysis was performed on whole blood samples from breast cancer survivors with and without persistent fatigue, to look for different expression patterns that might shed light on the biology behind cancer-related fatigue.
Project description:Fatigue is the most common symptom in oncology patients during chemotherapy. Little is known about the predictors of interindividual variability in initial levels and trajectories of morning fatigue severity in these patients.An evaluation was done to determine which demographic, clinical, and symptom characteristics were associated with initial levels as well as the trajectories of morning fatigue and to compare findings with our companion paper on evening fatigue.A sample of outpatients with breast, gastrointestinal, gynecological, and lung cancer (n = 586) completed demographic and symptom questionnaires a total of six times over two cycles of chemotherapy. Fatigue severity was evaluated using the Lee Fatigue Scale. Hierarchical linear modeling was used to answer the study objectives.A large amount of interindividual variability was found in the morning fatigue trajectories. A piecewise model fit the data best. Patients with higher body mass index, who did not exercise regularly, with a lower functional status, and who had higher levels of state anxiety, sleep disturbance, and depressive symptoms reported higher levels of morning fatigue at enrollment. Variations in the trajectories of morning fatigue were predicted by the patients' ethnicity and younger age.The modifiable risk factors that were associated with only morning fatigue were body mass index, exercise, and state anxiety. Modifiable risk factors that were associated with both morning and evening fatigue included functional status, depressive symptoms, and sleep disturbance. Using this information, clinicians can identify patients at higher risk for more severe morning fatigue and evening fatigue, provide individualized patient education, and tailor interventions to address the modifiable risk factors.
Project description:The aim of this study is to use functional magnetic resonance imaging (fMRI) to prospectively examine pre-treatment predictors of post-treatment fatigue and cognitive dysfunction in women treated with adjuvant chemotherapy for breast cancer. Fatigue and cognitive dysfunction often co-occur in women treated for breast cancer. We hypothesized that pre-treatment factors, unrelated to chemotherapy per se, might increase vulnerability to post-treatment fatigue and cognitive dysfunction. Patients treated with (n = 28) or without chemotherapy (n = 37) and healthy controls (n = 32) were scanned coincident with pre- and one-month post-chemotherapy during a verbal working memory task (VWMT) and assessed for fatigue, worry, and cognitive dysfunction. fMRI activity measures in the frontoparietal executive network were used in multiple linear regression to predict post-treatment fatigue and cognitive function. The chemotherapy group reported greater pre-treatment fatigue than controls and showed compromised neural response, characterized by higher spatial variance in executive network activity, than the non-chemotherapy group. Also, the chemotherapy group reported greater post-treatment fatigue than the other groups. Linear regression indicated that pre-treatment spatial variance in executive network activation predicted post-treatment fatigue severity and cognitive complaints, while treatment group, age, hemoglobin, worry, and mean executive network activity levels did not predict these outcomes. Pre-treatment neural inefficiency (indexed by high spatial variance) in the executive network, which supports attention and working memory, was a better predictor of post-treatment cognitive and fatigue complaints than exposure to chemotherapy per se. This executive network compromise could be a pre-treatment neuromarker of risk, indicating patients most likely to benefit from early intervention for fatigue and cognitive dysfunction.
Project description:Fatigue is a common adverse effect of cancer treatment and may persist for years after treatment completion. However, risk factors for post-treatment fatigue have not been determined. On the basis of studies suggesting an inflammatory basis for fatigue, this study tested the hypothesis that expression-regulating polymorphisms in proinflammatory cytokine genes would predict post-treatment fatigue in breast cancer survivors.Women diagnosed with early-stage breast cancer (n = 171) completed questionnaires to assess fatigue and other behavioral symptoms (ie, depressive symptoms, memory complaints, sleep disturbance) and provided blood for genotyping within 3 months after primary treatment. Genomic DNA was extracted from peripheral-blood leukocytes and assayed for single nucleotide polymorphisms (SNPs) in the promoter regions of three cytokine genes: ILB -511 C>T (rs16944), IL6 -174 G>C (rs1800795), and TNF -308 G>A (rs1800629). An additive genetic risk score was computed by summing the number of high-expression alleles (zero, one, or two) across all three polymorphisms.The genetic risk index was significantly associated with fatigue; as the number of high-expression alleles increased, so did self-reported fatigue severity (P = .002). Analyses of individual SNPs showed that TNF -308 and IL6 -174 were independently associated with fatigue (P = .032). The genetic risk index was also associated with depressive symptoms (P = .007) and memory complaints (P = .016).These findings further implicate inflammatory processes as contributors to cancer-related fatigue and suggest a new strategy for identifying and treating patients at risk for this symptom based on genetic variants in proinflammatory cytokine genes.
Project description:Little is known about the phenotypic and molecular characteristics associated with changes over time in fatigue and lack of energy in patients with breast cancer.The aim of this study was to identify subgroups (i.e., latent classes) of women with distinct fatigue and energy trajectories; evaluate for differences in phenotypic characteristics between the latent classes for fatigue and energy; and evaluate for associations between polymorphisms in genes for pro- and anti-inflammatory cytokines, their receptors, and their transcriptional regulators and latent class membership.Patients were enrolled before and followed for six months after breast cancer surgery. Latent class analyses were done to identify subgroups of patients with distinct fatigue and energy trajectories. Candidate gene analyses were done to identify cytokine genes associated with these two symptoms.For both fatigue and lack of energy, two distinct latent classes were identified. Phenotypic characteristics associated with the higher fatigue class were younger age, higher education, lower Karnofsky Performance Status score, higher comorbidity, higher number of lymph nodes removed, and receipt of chemotherapy (CTX). Polymorphisms in interleukin (IL) 1? and IL10 were associated with membership in the higher fatigue class. Phenotypic characteristics associated with the lower energy class included: a lower Karnofsky Performance Status score and a higher comorbidity score. A polymorphism in IL1R1 was associated with membership in the lower energy class.Within each latent class, the severity of fatigue and decrements in energy were relatively stable over the first six months after breast cancer surgery. Distinct phenotypic characteristics and genetic polymorphisms were associated with membership in the higher fatigue and lower energy classes.
Project description:Moderate-to-severe fatigue occurs in up to 94% of oncology patients undergoing active treatment. Current interventions for fatigue are not efficacious. A major impediment to the development of effective treatments is a lack of understanding of the fundamental mechanisms underlying fatigue. In the current study, differences in phenotypic characteristics and gene expression profiles were evaluated in a sample of breast cancer patients undergoing chemotherapy (CTX) who reported low (n = 19) and high (n = 25) levels of evening fatigue. Compared to the low group, patients in the high evening fatigue group reported lower functional status scores, higher comorbidity scores, and fewer prior cancer treatments. One gene was identified as upregulated and 11 as downregulated in the high evening fatigue group. Gene set analysis found 24 downregulated and 94 simultaneously up- and downregulated pathways between the two fatigue groups. Transcript origin analysis found that differential expression (DE) originated primarily from monocytes and dendritic cell types. Query of public data sources found 18 gene expression experiments with similar DE profiles. Our analyses revealed that inflammation, neurotransmitter regulation, and energy metabolism are likely mechanisms associated with evening fatigue severity; that CTX may contribute to fatigue seen in oncology patients; and that the patterns of gene expression may be shared with other models of fatigue (e.g., physical exercise and pathogen-induced sickness behavior). These results suggest that the mechanisms that underlie fatigue in oncology patients are multifactorial.
Project description:Although breast cancer mortality is decreasing, morbidity following treatment remains a significant issue, as patients face symptoms such as cancer-related fatigue (CRF). The aim of the present study is to develop a classification system that monitors fatigue via integration of an objective clinical assessment with patient self-report. Forty-three women participated in this research. Participants were post-treatment breast cancer survivors who had been surgically treated for their primary tumour with no evidence of neoplastic disease at the time of recruitment. Self-perceived fatigue was assessed with the Spanish version of the Piper Fatigue Scale-Revised (R-PFS). Objective fatigue was assessed by the 30 second Sit-to-Stand (30-STS) test. Confirmatory factor analysis was done with Maximum Likelihood Extraction (MLE). Internal consistency was obtained by Cronbach's ? coefficients. Bivariate correlation showed that 30-STS performance was negatively-inversely associated with R-PFS. The MANOVA model explained 54.3% of 30-STS performance variance. Using normalized scores from the MLE, a classification system was developed based on the quartiles. This study integrated objective and subjective measures of fatigue to better allow classification of patient CRF experience. Results allowed development of a classification index to classify CRF severity in breast cancer survivors using the relationship between 30-STS and R-PFS scores. Future research must consider the patient-perceived and clinically measurable components of CRF to better understand this multidimensional issue.
Project description:BACKGROUND:Fatigue is one of the most common and disabling side effects of cancer and its treatment. Although research typically has focused on fatigue that occurs during and after treatment, patients may experience fatigue even before treatment onset. The current study was designed to identify biobehavioral risk factors associated with fatigue before adjuvant therapy in women with early-stage breast cancer. METHODS:Patients with stage 0 to stage IIIA breast cancer (270 women) were recruited before the onset of adjuvant or neoadjuvant therapy with radiotherapy, chemotherapy, and/or endocrine therapy. Host factors that may influence fatigue were identified from an empirically based, biobehavioral model and assessed using self-report questionnaires, medical record review, and blood collection (for genetic data). Fatigue was assessed by questionnaire. Linear regression analyses were used to evaluate the association between host factors and dimensions of fatigue, with general fatigue as the primary dimension of interest. RESULTS:Fatigue was elevated at the pretreatment assessment compared with published controls. Bivariate analyses identified demographic, cancer-related, and biobehavioral correlates of fatigue. In the multivariable model, predictors of general fatigue included younger age, lower educational level, lower cancer stage, and history of childhood maltreatment (all P values <.05), with the full model accounting for approximately 18.4% of the variance in fatigue. Secondary analyses identified common and specific predictors of emotional, mental, and physical dimensions of fatigue. CONCLUSIONS:Among women who have not yet initiated treatment of breast cancer, demographic and psychosocial factors are associated with elevated fatigue and could be used to identify at-risk patients for early intervention.
Project description:Supervised exercise dietary programs are recommended to relieve cancer-related fatigue and weight increase induced by adjuvant treatment of early breast cancer (EBC). As this recommendation lacks a high level of evidence, we designed a multicenter randomized trial to evaluate the impact of an Adapted Physical Activity Diet (APAD) education program on fatigue. We randomized 360 women with EBC who were receiving adjuvant chemotherapy and radiotherapy to APAD or usual care at eight French cancer institutions. Data were collected at baseline, end of chemotherapy, end of radiotherapy, and 6 months post-treatment. The primary endpoint was the general cancer-related fatigue score using the MFI-20 questionnaire. Fatigue correlated with the level of precariousness, but we found no significant difference between the two groups in terms of general fatigue (p = 0.274). The APAD arm has a smaller proportion of patients with confirmed depression at the end of follow-up (p = 0.052). A transient modification in physical activity levels and dietary intake was reported in the experimental arm. However, a mixed hospital- and home-based APAD education program is not enough to improve fatigue caused by adjuvant treatment of EBC. Cancer care centers should consider integrating more proactive diet-exercise supportive care in this population, focusing on precarious patients.