Fatigue and Quality of Life of Women Undergoing Chemotherapy or Radiotherapy for Breast Cancer

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1 DOI /s Fatigue and Quality of Life of Women Undergoing Chemotherapy or Radiotherapy for Breast Cancer Winnie K.W. So 1 Gene Marsh 2 W.M. Ling 3 F.Y. Leung 4 Joe C.K. Lo 5 Maggie Yeung 6 George K.H. Li 7 1 Department of Nursing Studies, The University of Hong Kong, Hong Kong SAR, China. 2 School of Nursing, University of Colorado Health Science Center, USA. 3 Nurse Specialist, Department of Clinical Oncology, Pamela Youde Nethersole Eastern Hospital Hong Kong SAR, China. 4 Infection Control Unit, Princess Margaret Hospital, Hong Kong SAR, China. 5 Oncology Department, Princess Margaret Hospital, Hong Kong SAR, China. 6 Clinical Oncology Department, Tuen Mun Hospital, Hong Kong SAR, China. 7 Department of Surgery, Queen Mary Hospital, Hong Kong SAR, China. Correspondence to: Winnie K.W. So Tel: Fax: wkw@hku.hk This work was supported by grants from the University of Hong Kong and School of Nursing of University of Colorado. Received February 1, 2009; accepted April 22, cocr@gmail.com Tel (Fax): OBJECTIVE To examine fatigue and quality of life (QOL) in breast cancer patients undergoing chemotherapy or radiotherapy. METHODS A self-report survey derived from the Chinese version of Brief Fatigue Inventory, the Functional Assessment of Chronic Illness Therapy for Breast Cancer, and the Medical Outcomes Study Social Support Survey. Descriptive statistics was used to examine the intensity of fatigue and the prevalence of severe fatigue. Multivariate analysis of variance was used to determine factors that affect the five domains of QOL among the participants. RESULTS The majority of the participants (n = 261) perceived a mild level of fatigue, but 35.6% of them suffered severe fatigue. Fatigue had a significantly negative association with all domains of QOL except social/family wellbeing. The participants who were receiving chemotherapy, undergoing curative treatment and having inadequate social support were more likely to have poorer QOL in all five domains (after adjustment for age). CONCLUSION Although the majority of the participants experienced a mild level of fatigue, there was a substantial group of breast cancer patients who perceived their fatigue as severe. The findings of this study showed that fatigue had a detrimental effect on the various aspects of the participants QOL. Demographic and clinical characteristics of breast cancer patients who were at risk of getting poorer QOL were identified. The results of the study demonstrate that we should enhance healthcare professionals awareness of the importance of symptom assessment, and provide them with information for planning effective symptommanagement strategies among this study population. KEY WORDS: breast neoplasm, fatigue, quality of life, drug therapy. Copyright 2009 by Tianjin Medical University Cancer Institute & Hospital and Springer Introduction Fatigue can be defined as a feeling of physical and/or mental tiredness, usually caused by prolonged or intense activity. It is also one of the symptoms commonly experienced by cancer patients. Different from fatigue experienced by the healthy population, cancer-related fatigue (CRF) is a more distressing symptom, which creates an unrelenting condition that interferes with individuals ability to carry out normal activities [1]. The prolonged experience of CRF may cause patients to withdraw from the treatment, or to limit doses of chemotherapy and experience considerable interference with their daily functioning and quality of life (QOL) [2]. CRF is the most common side-effect of the treatment and the most

2 180 common symptom of cancer itself. Research studies have reported that about 90% of the patients undergoing cancer treatment experience fatigue [3]. CRF is one of the most frequent and distressing symptoms for patients with breast cancer [4]. High and fluctuating prevalence rates of fatigue have been found in women with breast cancer, ranging from 50%-99% [2,5-10]. Previous studies reported that patients with breast cancer experienced a mild to moderate level of fatigue [5,11-15]. However, studies that focused on subjects receiving treatment for breast cancer are limited. To the best of the authors knowledge, only one study done by Donovan et al. [6] has examined fatigue in subjects undergoing chemotherapy and/or radiotherapy for early-stage breast cancer. Further research is essential to close the knowledge gap related to this population. Numerous studies have examined the QOL and predictors of QOL among patients with breast cancer in Western populations. Studies of QOL in the Chinese breast cancer population, however, are limited [16-18]. Cui et al. [16] investigated the long-term effects of medical and demographic factors on the QOL of 1,065 Chinese breast cancer survivors. They found that recurrence rate and time, marital status, income and education were significantly related to the overall QOL. Sun et al. [17] and Wong-Kim et al. [18] used a qualitative method to explore the QOL in 30 Chinese patients with breast cancer, 15 foreign-born and 15 American-born Chinese women. Although family relationships and support were included when describing a good QOL in both groups, more American-born women used words like independence, freedom, friendships when describing a good QOL. To the best of the authors knowledge, there has been no research investigating the QOL of Chinese women receiving treatment for chemotherapy or radiotherapy. The purpose of this study was to examine fatigue and QOL in Chinese patients undergoing chemotherapy or radiotherapy for breast cancer. The following specific research questions were investigated. 1. What is the level of intensity of fatigue in Chinese patients undergoing chemotherapy or radiotherapy for breast cancer? 2. What is the prevalence of severe fatigue in these patients? 3. Does the level of fatigue in this population affect their QOL? 4. What demographic and clinical factors affect QOL? Materials and Methods Setting and sample Potential subjects were recruited from the outpatient sections of the Department of Clinical Oncology or the Breast Center in the four local public hospitals. Eligible criteria included Chinese women who (a) were 18 years old or older; (b) having undergone surgery for breast cancer; (c) being midway in their course of chemotherapy or radiotherapy; and (d) being able to communicate in Cantonese. Those who had one of the following conditions, (a) having a history of a psychiatric disorder; (b) having metastatic brain disease; or (c) having had a recurrence of breast cancer were excluded from the study. Instruments The original self-report survey consisted of 6 parts. Details of the survey are described elsewhere [19]. In this paper, 4 parts of the survey were described as these parts were used for analysis and discussion: 1) demographic and clinical characteristics; 2) fatigue; 3) quality of life; and 4) social support. Demographic and clinical characteristics The demographic data consisted of age, income, marital status, educational level, social support, stage of cancer, comorbidity, duration of illness, intent of current treatment modality, type of current treatment, time since breast cancer diagnosis and history of surgery received. Fatigue Brief Fatigue Inventory Chinese version (BFI-C) was used to measure the level of fatigue. Wang et al. [20] developed the BFI-C which was translated from the original version developed by Mendoza et al. [21] The tool consists of nine items including both fatigue severity and interference items. An 11-point Likert-type scale was used to measure both parts (0 = no fatigue/does not interfere to 10 = fatigue as bad as you can imagine/ completely interferes). Good internal consistency and external validity had been demonstrated in a sample of 249 Chinese cancer patients [20]. In this study, the BFI-C was used for measuring the severity of fatigue in all participants over the past week. The Cronbach s alpha coefficient for the entire scale was Quality of life Functional Assessment of Cancer Therapy for Breast Cancer (FACT-B) Chinese version was used to assess the degree of the QOL of the participants [22]. The scale consists of 36 items divided into 5 domains: physical, emotional, social and functional well-being and breast cancer subscales. Each item was rated on a 5-point rating scale (0 = not at all; 1 = a little bit; 2 = somewhat; 3 = quite a bit; 4 = very much). Therefore, the total score and the subscale scores for the dimension of well-being were measured. Higher scores indicate better functional status. Adequate internal consistency and content validity had been demonstrated in the sample of 60 Chinese patients with breast cancer [23]. In this study, the Cronbach s alpha coefficient for the subscales ranged between 0.52 and 0.87 and the entire scale was Social support Medical Outcomes Study Social Support Survey Chi-

3 181 nese version (MOS-SSS-C) was used to examine social support of the participants. Yu et al. [24] translated the MOS-SSS into the Chinese version, which was developed by Sherbourne and Stewart [25]. This survey consists of 20 items which are divided into structural support (1 item) and functional support (19 items). The functional support items are categorized into 4 dimensions: (a) emotional/informational support, (b) tangible support, (c) affectionate support, and (d) positive social interaction. Each item is rated on a 5-point, rating scale to indicate how often the respondent receives the support (1 = none of the time, 2 = a little of the time, 3 = some of the time, 4 = most of the time, and 5 = all of the time). The individual subscale score is calculated from the summation of all items, and the total score is calculated from the mean of the subscale scores. These subscales and total scores are rescaled ranging from A higher score indicates better-perceived social support. Good internal consistency and external validity had been demonstrated in 110 Chinese patients diagnosed with heart failure [26]. In this study, the Cronbach s alpha coefficient for the subscales ranged between and the entire scale was Procedure The study was approved by the ethical committees of the institutions concerned in the study, and conducted in Potential subjects were approached by research nurses midway through their regime of chemotherapy or in their third to sixth week of radiotherapy. Data were collected by face-to-face interview. The medical records were reviewed by trained research nurses for the purpose of recording socio-demographic and clinical variables that might affect QOL. Statistical analysis Descriptive analysis was performed on all variables. Subjects were then grouped according to the perceived fatigue severity on the worst fatigue item: Group 1 (none), group 2 (mild to moderate), and Group 3 (severe). Multivariate analysis of variance (MANOVA) was used to determine factors affecting the 5 domains of QOL among the subjects. A P-value of 0.05 or less was regarded as statistically significant. Prior to computing the MANOVA, univariate analysis was used to identify the potential correlates that demonstrated a significant relationship with 1 of the 5 domains of QOL. The Pearson product-moment correlation was used for the continuous potential correlates, while independent t tests or one-way analysis of variance (ANOVA) were used for nominal potential correlates. Any variables that significantly correlated with 1 of the 5 domains were included in the multivariate analyses. A P-value of 0.25 was treated as statistically significant to avoid inadvertently eliminating potentially important variables [27]. The 5 dependent variables were physical well-being (PWB), social/family well-being (SFWB), emotional well-being (EWB), functional well-being (FWB) and breast cancer subscale (BCS). The 11 independent variables were age (continuous), monthly household income (< 10000, , > 30000), occupation (employed or unemployed), religion (yes or no), intent of current treatment modality (curative or palliative), Chalson index (continuous), type of treatment (chemotherapy or radiotherapy), received surgery (yes or no), duration of illness (continuous), overall social support index (continuous) and global fatigue score (GFS) (continuous). Results Recruitment and response During the data collection period, 381 women from the 4 public hospitals were approached. Of these, 71 refused to participate in the study and 40 were excluded because they did not fulfill the inclusion criteria or met at least one exclusion criterion (two suffering from mental illness, 22 experiencing a recurrence of breast cancer, and 18 being less than half-way through chemotherapy); and 9 women completed the questionnaire twice but only the one completed while they were actually receiving radiotherapy was used for analysis. Overall, 332 eligible women were approached and 261 met the criteria and agreed to participate in the study, a response rate of 78.61%. Participants characteristics Table 1 shows the demographic and clinical characteristics of the sample, grouped by types of cancer treatment. The total social support and 4 subscale scores are reported in Table 2. Prevalence and intensity of fatigue The BFI-C was used to measure the prevalence and intensity of fatigue. The global fatigue score (GFI) and all items of the entire BFI-C scale are presented in Table 3. The worst fatigue item was used to examine the prevalence of severe fatigue among the participants. Comparing the mean scores of the 6 fatigue interference items, the most interference item was general activity, whereas the least interference item was relations with other people. The sample was then grouped into the 3 levels of fatigue (scores of 0 = no fatigue group; scores of 1 to 6 = mild/moderate fatigue group; scores higher than 6 = severe fatigue group). The prevalence of no fatigue, mild/moderate and severe fatigue was 12.6%, 51.7% and 35.6%, respectively. Factors influencing the 5 domains of QOL of participants MANOVA was performed to identify the correlates of the 5 domains of QOL in patients undergoing chemotherapy or radiotherapy for breast cancer. Statistically significant difference was reported in 4 independent

4 182 Table 1. Participants demographic and clinical characteristics (n = 261). Characteristics Mean SD Age (years) Time since breast cancer diagnosis (months) Time since current treatment started (weeks) Comorbidity (Charlson Index) Characteristics n (%) % Marital status Single/divorced/widowed Cohabiting/married Educational level No formal education/primary Secondary Tertiary Occupation Employed Unemployed Monthly household income (HK$) < 10, ,001-30, >30, Religious belief Yes No Stage of cancer Stage Stage I Stage II Stage III Stage IV Type of current treatment Chemotherapy Radiotherapy Intent of current treatment modality Curative Palliative Received surgery Yes No 21 8 Clinical site Site Site Site Site Note: Education levels: Primary education = Grade 1-6; Secondary education = Grade 7-12; Tertiary education = University education; Religious belief = participants who were Catholic, Christian or Buddhist, or worshipped their ancestors. Table 2. The mean social support score and the mean score of each subscale (n = 261). Mean SD Social support a (Mean of total score) Emotion & information support Tangible support Affectionate support Positive social interaction Note: a Medical Outcomes Study Social Support Survey Chinese version (MOS-SSS-C) was used to obtain the findings. Table 3. Individual items of the BFI a (n = 261). Mean SD Fatigue (GFS) Fatigue right now Usual fatigue Worst fatigue Fatigue interfering with General activity Mood Walking ability Normal work Relations with other people Enjoyment of life Note: a Brief Fatigue Inventory Chinese version (BFI-C) was used to obtain the findings. variables after being adjusted for age: GFS (Wilks lambda = 0.604, P < 0.001, partial Eta squared = 0.396), type of treatment (Wilks lambda=0.881, P < 0.001, partial Eta squared = 0.119), intent of current treatment modality (Wilks lambda = 0.975, P = 0.287, partial Eta squared = 0.025) and total social support index (Wilks lambda = 0.531, P < 0.001, partial Eta squared = 0.469). The severity of fatigue has a significant adverse effect on all QOL domains except social/family wellbeing (SFWB). Chemotherapy being given the participants were significantly associated with poorer physical (PWB) and functional wellbeing (FWB) compared with radiotherapy being given the other participants. Higher scores on the overall social support index were associated with better SFWB, EWB and FWB. The curative treatment being given the participants were significantly associated with poorer PWB compared with palliative treatment being given the other participants. Table 4 shows the factors affecting the 5 domains of QOL.

5 183 Table 4. Factors that affect the five domains of QOL 1 using MANOVA test. QOL Domain Factor β SE t P Physical wellbeing a GFS <0.001 Emotional wellbeing c <0.001 Functional wellbeing d <0.001 Breast cancer subscale e <0.001 Physical wellbeing a Type of treatment: Chemotherapy <0.001 Functional wellbeing d Physical wellbeing a Intent of current treatment modality: Curative Social / family wellbeing b Overall support index <0.001 Emotional wellbeing c Functional wellbeing d <0.001 Note: 1 Functional Assessment of Cancer Therapy for Breast Cancer (FACT-B) Chinese version, 2 Brief Fatigue Inventory Chinese version (BFI-C) and 3 Medical Outcomes Study Social Support Survey Chinese version (MOS-SSS-C) were used to obtain the findings. Influence of significance variables on QOL domains after adjusted for age. a R squared = 0.436; b R squared = 0.468; c R squared = 0.203; d R squared = 0.354; e R squared = Discussion Prevalence and intensity of fatigue The majority of participants experienced mild to moderate levels of fatigue and the GFS among the participants were at a mild level. Compared with previous studies using other fatigue measurement tool to determine fatigue in the majority of patients undergoing chemotherapy or radiotherapy reported significant fatigue during the course of treatment [4], and the present study found that the prevalence of severe fatigue and the overall level of fatigue among breast cancer patients were lower. Possible reasons include the different types of treatment patients received and the period of data collection. In general, breast cancer patients receive radiation treatment 5 days per week for 4-6 consecutive weeks. Lower levels of fatigue in the group of patients receiving radiotherapy might have affected the overall mean score of fatigue among all participants. Also, patients undergoing chemotherapy for breast cancer usually receive 4-8 courses, with each course of treatment occurring once every three weeks. If responses at the time of data collection were not at the peak level of symptom experience, the severity of fatigue experienced by participants might have been underestimated. Despite this possible underestimation of the prevalence and severity of fatigue, more than 1/3 of the participants were found to experience severe fatigue. This provides evidence that fatigue continues to be a significant problem in patients undergoing cancer treatment. Assessment of the symptom of fatigue and the provision of effective symptom management strategies are essential for this study population. Factors influencing the 5 domains of QOL of participants The findings of the study revealed that the severity of fatigue has a significantly negative association with the 4 domains of QOL (physical, emotional, functional and breast cancer subscale) after controlling for type of treatment, intent of treatment modality, age and overall social support index. The findings provide evidence that the severity of fatigue could have profound effects on the physio-psychological wellbeing of the patients during the cancer treatment. Also, a positive association between the level of fatigue and the BCS may imply that fatigue has an adverse effect on other breast-cancerrelated symptoms. Further studies are necessary to investigate the relationships between fatigue and other symptoms experienced by the same study population. The results of this study show that fatigue did not have a significant adverse effect on the social/family wellbeing of the participants. The finding is consistent with the results of the 6 fatigue-interference items in the BFI-C. Participants perceived relations with other people as the least fatigue-interference item compared with the other such items. This may be due to the provision of social and family support not being affected by the symptom of fatigue itself. In other words, when cancer patients have adequate support from their family and friends, healthcare professionals and the society, their social/family wellbeing can be maintained regardless of the intensity of fatigue they experience. In this study, a positive association was found between the overall social support index and SFWB, which further supports the significant effects of social support on maintaining the patient s SFWB. The study also identified several demographic and clinical variables as possible factors affecting various aspects of QOL. Type of treatment was one of these factors to affect PWB and FWB. Adjuvant chemotherapy had a greater negative impact on the PWB and FWB of participants than radiotherapy. One possible reason for this may be the more severe side-effects of chemothera-

6 184 py. Also, patients who were receiving curative treatment reported poorer PWB than those who were undergoing palliative treatment. Possible reasons here may be the purpose and side-effects of the treatment. The main purpose of palliative treatment is to relieve patients physical discomfort due to cancer. However, the main purpose of curative treatment is to eliminate cancer cells. The patients PWB may be affected by side-effects of the treatment. Since this study did not collect the baseline data of the participants QOL, further research is needed to compare changes in QOL between cancer patients undergoing curative treatment and those receiving palliative treatment. Social support was significantly associated with the SFWB, EWB and FWB of the participants. These findings were consistent with those of previous studies [28,29]. In a study exploring the QOL of Chinese women with breast cancer, Wong-Kim et al. [18] found that the significant others was a source of primary support and an important factor when assessing QOL. Family members also played a significant role in a patient s decisionmaking process. Those who were single identified their extended family and friends as their primary support system [18]. Limitations The study reported here has several limitations. The cross-sectional design provided information about the symptom levels of the participants at only one point in time. The pattern, consistency and intensity of the symptom over time were not evaluated. The results of the study revealed that fatigue and other demographic and clinical covariates explained 20%-47% of the variance in different domains of QOL. The remaining variance indicates the existence of unexplored factors such as other cancer- or treatment-related symptoms. These factors should be included in future research. Implications The findings of the study show that fatigue is a common symptom in patients with breast cancer and a substantial group of these patients perceived their fatigue as severe. Thus, incorporation of measurement of fatigue into nursing assessment charts is essential so that healthcare professionals are able to detect patients who experience fatigue. The findings demonstrated factors that affect various aspects of QOL of breast cancer patients undergoing chemotherapy or radiotherapy. These results enhance healthcare professionals clinical sensitivity in identifying the high risk of developing fatigue among the group of patients who are scheduled for curative chemotherapy or have inadequate social support. Once the high-risk group of patients is identified, appropriate advice and instructions regarding effective symptom management strategies could be provided to them. For example, healthcare professionals could educate the patients about the importance of balancing rest and exercise which have been evaluated and found to be effective in relieving fatigue and improving the QOL of cancer patients. [30] Since these factors affect various aspects of QOL of the patients, evaluation of the symptom management strategies should examine the effects on the physiopsychosocial wellbeing of the patients. Modifications of nursing assessment procedures and implementation of effective symptom management strategies based on the results of this research study could be a good foundation of developing evidence-based practice in care of women in treatment for breast cancer. Conclusion Most participants perceived a mild level of fatigue, but more than 1/3 experienced severe fatigue. Results of MANOVA showed that fatigue has a detrimental effect on the various aspects of QOL of the participants. 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