Fatigue After Treatment in Breast Cancer Survivors: Prevalence, Determinants And Impact On Health-related Quality Of Life

Abstract

Purpose

Fatigue is a phenomenon that may persist for years after the completion of adjuvant therapy and is one of the most frequent symptoms associated with breast cancer survivors. The purposes of this study were to investigate the occurrence of fatigue in disease-free breast cancer survivors after treatment, to identify variables associated with fatigue, and to evaluate the impact of fatigue on health-related quality of life.

Methods

A cross-sectional study was conducted on 202 consecutive women diagnosed with in-situ to Stage III breast cancer attending in outpatient facilities of two large hospitals, one year or more after diagnosis. They completed the Piper Fatigue Scale-Revised and the European Organization for Research and Treatment of Cancer QLQ-C30. Multiple logistic regression models were used to identify predictive factors associated with fatigue. EORTC QLQC-30 scores for fatigued survivors were compared to non-fatigued survivors. 

Results

The prevalence of fatigue reported by breast cancer survivors was 37.6%. Multiple logistic regression analysis revealed that predictive factors for fatigue included younger age (odds ratio [OR]=2.23, 95% confidence interval [CI]=1.11–4.45, p=0.024); presence of pain (OR=3.87, 95% CI=1.88-7.98, p=0.000); dyspnea (OR=3.72, 95% CI= 1.46–9.50, p=0.006); insomnia (OR=2.40, 95% CI=1.19– 4.86, p=0.015); and nausea and vomiting (OR=12.25, 95% CI=1.18–126.75, p=0.036). Fatigued women had the poorer health-related quality of life than non-fatigued women in all domains. 

Conclusion 

Our results suggest that many disease-free breast cancer survivors after treatment experience fatigue that compromises their health-related quality of life. Keywords Breast cancer. Fatigue. Quality of life. Survivors. Predictors.Prevalence

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Introduction

Breast cancer is the most prevalent cancer in the world, and its incidence rate has been, in overall, increased [1]. In Brazil, about 49.240 new cases of breast cancer are expected for 2010 [2]. In the USA, about 209.060 new cases of breast cancer are expected for the year 2010 [3]. As the number of breast cancer survivors has increased as a result of improvements in diagnosis and treatment [3], more attention has been directed to late effects of cancer-related treatment as well as their effects on the well-being in this population. Studies suggest that many breast cancer survivors experience a number of symptoms and late effects after treatment, including fatigue [4–19]. 

Although fatigue is a phenomenon that occurs during breast cancer treatment, it may persist for years after completion of adjuvant therapy [20], and it is one of the most frequent symptoms associated with adult cancer survivors [21]. Despite the occurrence of fatigue and its negative effect on the quality of life of cancer patients, little is known about the mechanisms underlying this symptom, or how to prevent it and treat it appropriately [22]. Fatigue may involve subjective sensations of tiredness, weakness, and/or lack of energy [6], and must be understood in terms of a multidimensional concept with physical, psychological, social, and spiritual components [23]. Unlike normal or everyday fatigue, cancer-related fatigue persists despite an adequate amount of sleep and rest periods [24]. There is some controversy in the literature regarding the factors associated with fatigue in breast cancer survivors. Some studies have identified demographic characteristics associated with fatigue such as age and employment [12], or cancer therapies [7]. However, fatigue in these patients has been related most frequently to pain, dyspnea, sleeping problems [15], depression, physical activity, causal attributions [16], cognitive problems, weight gain/personal appearance [13], and comorbidities, such as arthritis, high blood pressure [6], and presence of gastrointestinal disease [12]. There is some evidence in some studies that persistent inflammatory or immune response may be one biological mechanism to evoke post-treatment fatigue [4, 25]. More recently, gene expression of blood cells [26] and cytokine gene polymorphisms [27] in breast cancer survivors with fatigue have been investigated. Although the interest for fatigue in breast cancer survivors has increased in recent decades, most studies have been conducted in developed countries with specific cultural and socioeconomic contexts. To date, little is known about the prevalence, causes, or characteristics of fatigue experienced by breast cancer survivors from developing countries, and this situation makes it difficult to manage the problem. Considering these aspects, the aims of this study were to estimate the occurrence of fatigue in disease-free breast cancer survivors more than 1 year post-diagnosis, as well as to identify variables associated with fatigue and their impact on health-related quality of life. 

Methods

Study setting, subject, and data collection This is a cross-sectional study that involved post-treatment breast cancer survivors 1 year or more after diagnosis. Breast cancer survivors were selected among women who consecutively attended in outpatient facilities in two large hospitals: Erasto Gaertner Hospital (a specialist cancer hospital) and Hospital de Clínicas at Universidade Federal do Paraná (a tertiary care teaching hospital), Curitiba, Brazil. Eligible criteria included: (1) female patients with primary breast cancer, whose diagnosis has been made more than 1 year before data collection and treated at one of the two largest hospitals in Curitiba, Brazil, (2) 18 years of age or older, and (3) those with cognitive function and communication preserved. Women with evidence of meta-static or recurrent cancer or those with a history of other types of cancer were excluded. Medical records were reviewed prior to selecting the potentially eligible patients. Among 217 women, five women refused to participate (allegedly due to lack of time) and six could not be contacted. Four participants were excluded from the analyses (two incomplete questionnaires and two women were undergoing radiotherapy or chemotherapy). Thus, data from 202 (93.1%) patients were included in this study (102 patients from Erasto Gaertner Hospital and 100 patients from Hospital de Clínicas at Universidade Federal do Paraná). These participants were not receiving any cancer therapy other than hormone therapy. Data were collected after medical appointments from December 2008 to September 2009 by one of the investigators. Information on clinical variables was obtained from each medical record. These data were part of a doctorate project about quality of life and fatigue in breast cancer survivors compared with control groups, and only sociodemographic, clinical, and symptom variables, as well as measures about fatigue and health-related quality of life in breast cancer survivors were included in this report. The study was approved by the ethics committees of both participating institutions, and all subjects signed the study’s informed consent. 

Measures

Piper Fatigue Scale-Revised (PFS-R) The PFS-R is a multidimensional fatigue assessment tool that consists of 22 items and four subscales: behavioral/severity, affective meaning, sensory, and cognitive/mood. The psychometric properties were evaluated in a sectional study in women survivors of breast cancer [23]. The Brazilian version of the PFS-R contains 22 items that loaded well (factor loading >0.35) on three dimensions identified by factor analysis (behavioral, affective, and sensory/psychological) and provides an overall total fatigue score [28]. Items are listed in a numerical scale ranging from 0 to 10 (higher scores indicating greater fatigue), and the individual chooses a number that best describes the current fatigue experience. The Brazilian version of the PFS-R has been previously validated, and psychometric properties were considered satisfactory for use in the oncology Brazilian population [28]. In this study, internal consistency was very good for the total scale and its subscales (Cronbach’s alphas ranged from 0.98 to 0.94). 

The European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30) 

The EORTC QLQ-C30 is a cancer-specific questionnaire for assessing the quality of life of cancer patients. The questionnaire is composed of five functioning scales (physical, role, emotional, cognitive, and social functioning), a global health status/quality of life (QOL) scale, three multi-item symptom scales (fatigue, nausea/vomiting, and pain), single items for the assessment of symptoms (dyspnea, insomnia, appetite loss, constipation, and diarrhea), and financial impact of disease and treatment [29]. The EORTC QLQ-C30 is widely used, available in several languages, and shows acceptable psychometric properties [30]. The Brazilian version of the EORTC QLQ-C30 has been used in Brazilian cancer patients [31–33], and our own analyses indicate high internal consistency for the total scale and its subscales (Cronbach’s alphas ranged from 0.88 to 0.84). 

Statistical analysis

Descriptive statistics were conducted to present the prevalence of fatigue and the characteristics of the participants. The Piper total fatigue score is obtained by the final average of all items of the instrument. It can also be used as a categorical variable, with the cutoff score ≥4 for assessing clinically significant fatigue. Thus, participants were classified as fatigued (moderate and intense fatigue) if their total fatigue score was four or higher, according to other authors’ suggestions [13, 34, 35]. Scoring procedures to the EORTC QLQ-C30 items were used according to the EORTC scoring manual [29]. Scores were transformed into a 0 to 100 scale. A higher functional score represented a better level of functioning/quality of life, whereas a higher symptom score represented more severe level of symptoms. For symptom variables on the EORTC QLQ-C30 (such as pain, nausea/vomiting, dyspnea, insomnia, appetite loss, constipation, and diarrhea), scores of 66 or higher on a scale from 0 to 100 were considered indicative of clinically significant symptoms [12, 36, 37]. 

Participants were classified as having the symptom if the symptom scale score was 66 or higher. In this case, symptoms were established as causal variables because their occurrence can affect health-related quality of life, as suggested in a previous study [38]. The fatigue subscale was excluded from the EORTC QLQC-30 because of its overlap with the PFS-R, and one item (financial difficulties) was excluded from the analysis because it was not considered as a symptom variable [12]. In addition, we compared the scores of the global health status/ QOL scale and functioning domains in EORTC QLQ-C30 for fatigued breast cancer survivors and non-fatigued breast cancer survivors. The EORTC QLQ-C30 scores presented an asymmetrical distribution, therefore, the Mann–Whitney test was used to determine group differences in global health status/QOL scale and functioning domains of the EORTC QLQ-C30 between fatigued and non-fatigued survivors. The chi-square test was used to assess the association of sociodemographic, clinical, and symptom variables with the dependent variable fatigue. To identify sociodemographic, clinical, and symptom variables that were independently associated with fatigue, multivariate logistic regression models were used. Because of multiple comparisons, Bonferroni correction was performed. Each independent factor found to be significant after Bonferroni correction at the univariate level was entered into the final multivariate logistic regression model. It was used stepwise, forward elimination procedure, calculating odds ratio, and corresponding 95% confidence intervals. In the statistical analyses, a significance level of 0.05 and two-tailed tests were used. The STATA 9.0 (STATA Corporation College Station, EUA) was used to analyze the data. 

Results

Characteristics of fatigued and non-fatigued breast cancer survivors Using the dichotomous cutoff (total fatigue score ≥4), 76 (37.6%) survivors were classified as fatigued. The average scores were 6.1 (standard deviation (sd) = 1.35; median = 5.97) and 0.83 (sd=1.33; median = 0.0) for fatigued and non-fatigued survivors, respectively. The fatigued breast cancer survivors in this study were 35–74 years of age (average age = 51.1 years old, sd=9.0). The non-fatigued breast cancer survivors in this study were 31–85 years of age (average age=56.5 years old, sd=10.7). Table 1 describes the sociodemographic variables in detail for fatigued and non-fatigued women. The mean age at diagnosis of the fatigued survivors was 46.2 years old (sd=8.4), and the average time since diagnosis was 4.9 years (sd=4.7). The mean age at diagnosis of the non-fatigued survivors was 51.0 years old (sd=10.6), and the average time since diagnosis was 5.4 years (sd=4.5). Univariate analyses of fatigue The association between fatigued and non-fatigued women and variables of interest (i.e., sociodemographic, clinical, and symptom variables) was examined. Younger women (≤50 years) suffered more fatigue than those older ones. 

Table 1 Distribution of breast cancer survivors according to sociodemographic variables and their association with fatigue 

On the other hand, ethnicity, educational level, marital status, number of children, employment status, and individual income per month were not related to fatigue (Table 1). Women diagnosed at a younger age (≤50 years) suffered more fatigue than those diagnosed at an older age. Neither the time since diagnosis nor the menopausal status or laterality were correlated with fatigue. Stage of disease, lymph node status, type of surgery, and breast reconstruction surgery were not associated with fatigue. No differences were observed between the two groups with regard to radiotherapy and current hormone therapy, but differences were observed for women who received chemotherapy (Table 2). Fatigue was not significantly associated with time since last surgery (p=0.616), time since last chemotherapy (p=0.876), time since last radiotherapy (p=0.223), number of comorbidities (p=0.349), and type of comorbidity (hypertension, musculoskeletal disease, gastrointestinal disease, diabetes mellitus, dyslipidemia, thyroid disease, cardiac disease, hematologic disease, and kidney disease, all p values<0.05). Fatigue was significantly more frequent (p=0.039) in women who had a diagnosis of depression (data not shown). Higher rates for pain, nausea/vomiting, dyspnea, insomnia, appetite loss, and constipation in the EORTC QLQC30 were associated with fatigue, but diarrhea was not associated (Table 3). Multivariate logistic regression models of fatigue Because multiple comparisons were considered, the Bonferroni correction was used to maintain an overall error rate of 0.05. The Bonferroni correction divides the level of significance (0.05) by the number of comparisons being made within a similar set of comparisons. The single chi-square analysis of the sociodemographic, clinical, and symptom variables identifies some variables withp values lower than 0.05 and age at interview, age at diagnosis, pain, dyspnea, insomnia, constipation, appetite loss, and nausea and vomiting remained significant after Bonferroni correction. Using logistic regression procedures and the Piper total fatigue scores as a dichotomous variable, our predictive model of fatigue yielded five significant correlates. Results for the individual predictor variables are shown in Table 4. Younger age, pain, dyspnea, insomnia, and nausea/vomiting were associated with an increased risk of fatigue. The final multivariate model did not include any clinical variables. 

Fatigue and health-related quality of life

The EORTC QLQ-C30 scores can be found in Table 5. The quality of life scores were significantly lower for fatigued survivors than for non-fatigued survivors in all domains (all p values = 0.000). The highest scores were observed in the social functioning, the median of 100.0 for both non-fatigued and fatigued women, while the lowest scores were found in the emotional functioning, with medians of 66.7 and 25.0 for non-fatigued and fatigued patients, respectively. Discussion The aims of this study were to investigate the prevalence of fatigue in Brazilian disease-free breast cancer survivors (n= 202), to identify variables associated with fatigue and their impact on health-related quality of life. The patients were breast cancer survivors after treatment with more than 1 year post-diagnosis because at this time, probably, acute side effects of treatment would have decreased. The occurrence of fatigue found in breast cancer survivors in this study was 37.6%. This prevalence was slightly lower than that experienced by breast cancer survivors in a large multicenter, multi-ethnic cohort study of disease-free breast cancer survivors (n=800) in the USA [13]. Using PFS-R, the prevalence of fatigue was 41%. This difference may, in part, be due to differences in geographic locations from which the samples were drawn and because the authors used an adapted version of the PFS-R that assesses fatigue over the past month. In addition, it is possible that differences in the recruitment of the participants may have influenced the results of the two studies. In the present study, the participants recruited were more than 1 year post-diagnosis (36% of women had five or more years after diagnosis) while in the study of Meeske et al. [13] the participants were recruited 2 to 5 years post-diagnosis. 

Table 2 Distribution of breast cancer survivors according to clinical variables (cancer-related and treatment) and their association with fatigue

Discussion

The aims of this study were to investigate the prevalence of fatigue in Brazilian disease-free breast cancer survivors (n= 202), to identify variables associated with fatigue and their impact on health-related quality of life. The patients were breast cancer survivors after treatment with more than 1 year post-diagnosis because at this time, probably, acute side effects of treatment would have decreased. The occurrence of fatigue found in breast cancer survivors in this study was 37.6%. This prevalence was slightly lower than that experienced by breast cancer survivors in a large multicenter, multi-ethnic cohort study of disease-free breast cancer survivors (n=800) in the USA [13]. Using PFS-R, the prevalence of fatigue was 41%. This difference may, in part, be due to differences in geographic locations from which the samples were drawn and because the authors used an adapted version of the PFS-R that assesses fatigue over the past month. In addition, it is possible that differences in the recruitment of the participants may have influenced results from the two studies. In the present study, the participants recruited were more than 1 year post-diagnosis (36% of women had five or more years after diagnosis) while in the study of Meeske et al. [13] the participants were recruited 2 to 5 years post-diagnosis. 

Table 3 Distribution of breast cancer survivors according to symptom variables and their association with fatigue

All tests were performed using χ2 analysis a Cutoff score for symptoms in EORTC QLQ-C30 is ≥66 on a scale from 0 to 100

To increase knowledge about potential predictive factors for fatigue among breast cancer survivors, fatigued and non-fatigued survivors on a variety of sociodemographic, clinical, and symptom variables were compared. Results showed one sociodemographic characteristic and four symptoms that were associated with an increased risk of fatigue. Younger women were associated with an increased risk of fatigue in this study. Age was not significantly related to fatigue on multivariate models of fatigue in 69 disease-free breast cancer patients (at least 6 months post-treatment) [19], but younger women were identified as at risk for fatigue in a large-scale examination among disease-free breast cancer survivors post-treatment (stage 0–III, mean time since diagnosis of 4.6 years) [12]. Similarly, younger women were more likely to be classified as fatigued in disease-free breast cancer survivors after treatment for early-stage breast cancer recruited from two large metropolitan cities in the USA, 1 to 5 years after initial breast cancer diagnosis [6]. Therefore, health professionals should be alert to the possibility of greater fatigue in young survivors. In this study, an association of higher rates for pain with an increased risk for fatigue was found. Among the symptoms studied, the pain was most often reported by survivors (Table 3). Similarly, many previous studies of breast cancer survivors reported a significant association of pain and fatigue. According to these previous findings, pain may persist after treatment and may affect the fatigue experienced. Pain in breast cancer survivors can occur secondary to cancer treatment, such as surgery [39] or radiotherapy [40], or the presence of lymphedema [39]. However, other comorbidities reported by a number of breast cancer survivors in this study also cause pain, especially musculoskeletal diseases, so differentiating cancer and non-cancer pain is still very complex. Further studies are required to identify the relationship between fatigue and pain, and concentrate on examining cancer- and non-cancer-related pain. Thus, more information about pain in post-treatment breast cancer survivors might provide better understanding and development of specific prevention and treatment. Other symptom predictor of fatigue was dyspnea. The link between fatigue in disease-free breast cancer survivors 

Table 4 Multivariate logistic regression model for fatigue in breast cancer survivors

and dyspnea has been reported in the literature by other authors [12, 15]. The determination of the etiology of dyspnea is very complex and is often multifactorial, including physiological, psychological, and social elements. Although it is a devastating symptom, it is usually poorly assessed, underdiagnosed, and inadequately treated [41]. Furthermore, it was reported that cancer patients often describe their dyspnea with terms such as tired or fatigued [42], which makes it more difficult to understand these two symptoms. Future research is needed to better understand the relationship between fatigue and dyspnea. 

As also found in the analyses of this study, previous research reported the association between insomnia and fatigue. Insomnia was the second most frequent symptom reported by fatigued patients (Table 3), reinforcing the importance of sleep disorders in relation to fatigue in this population. However, this relationship remains not well understood. These two terms are often used as synonyms, despite significant differences between their concepts. In addition, to determine the relationship between sleep and fatigue is difficult because both symptoms may occur because of many factors (e.g., humor, pain, inflammation, hot flashes, other diseases, and drugs). 

Moreover, these multiple factors hinder the establishment of causal relationships [43]. Determining the cause of patients’ sleep disorders and their relationship to fatigue among breast cancer survivors requires further characterization, to better understand the link between these symptoms, and implement appropriate clinical treatment. The significant association of nausea/vomiting and fatigue was an unexpected result in the current investigation because among possible symptoms related to fatigue, nausea and vomiting appear to be one of the least reported symptoms. These symptoms were not associated with fatigue in a study with disease-free breast cancer survivors [12], but gastrointestinal symptoms (appetite loss or constipation) and having a gastrointestinal disease (such as gastric or duodenal ulcers) were significantly associated with fatigue. For the authors, it is possible that these symptoms and diseases contribute to fatigue via malnutrition or anemia. Nausea and vomiting are often found in cancer patients as a result of treatment or complications related directly or indirectly to the disease. Anyway, nausea and vomiting can affect the nutritional status of patients and also their food, with an impact on their quality of life [44]. Therefore, prevention and treatment of nausea and vomiting should be incorporated into routine care for patients with breast cancer, and these interventions could be effective in preventing or decreasing fatigue. As expected, fatigued women had poorer health-related quality of life than non-fatigued women in all domains. Recent studies have demonstrated the great impact of fatigue on the quality of life for survivors of breast cancer. A large study [12] with disease-free breast cancer survivors (n=1.933) found significant reductions in mean scores for all functioning subscales (EORTC QLQ-C30) between the fatigued and non-fatigued groups (p<0.001). 

Recently, Alexander et al. [4], in a study with disease-free breast cancer survivors with or without cancer-related fatigue syndrome and without psychiatric comorbidity, reported significant differences in all domains in EORTC QLQ-C30, except for the cognitive functioning. Women with cancer-related fatigue reported lower levels of functioning and higher levels of symptom severity. These findings reinforce the need for providers to use evidence-based recommendations for cancer fatigue to monitor survivors of breast cancer and to establish strategies to improve quality of life. Limitations in the present study were related to the study design (cross-sectional). No causal relations among the variables and fatigue can be established. The study was conducted at two medical centers, and the findings cannot be generalized. A specific instrument to assess depression, psychosocial, or biological factors was not used. Despite these limitations, this study may contribute to the management of fatigue in breast cancer survivors, directing innovative interventions to prevent and treat fatigue. The strengths of this study were its focus on fatigue in Brazilian disease-free breast cancer survivors, identifying predictive factors for fatigue and its impact on health-related quality of life. Moreover, another important aspect of this study was the use of two standardized and internationally validated cancer-specific questionnaires to evaluate fatigue and health-related quality of life.

This current examination found that many disease-free breast cancer survivors experienced fatigue after treatment. Fatigue was influenced by age and symptoms, and had a high impact on health-related quality of life, with poorer scores in all domains for fatigued patients. Thus, for breast cancer survivors, healthcare professionals should pay more attention to the possibility of fatigue in younger women and those with symptoms (such as pain, dyspnea, insomnia, and nausea/vomiting) because these symptoms are undervalued at times. Future research should evaluate additional variables related to fatigue following breast cancer treatment and their impact on quality of life over time. Acknowledgments We thank all the women who took part in this research. Conflicts of interest The authors of this study did not receive any financial support for this study and declare no conflict of interest.