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Fatigue mediates the relationship between physical fitness and quality of life in cancer survivors
Journal of Science and Medicine in Sport 16 (2013) 99–104
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Original research
Fatigue mediates the relationship between physical fitness and quality of life in cancer survivors Laurien M. Buffart a,∗ , Ingrid C. De Backer b , Goof Schep b , Art Vreugdenhil d , Johannes Brug a , Mai J.M. Chinapaw c a
Department of Epidemiology and Biostatistics, VU University Medical Center, The Netherlands Department of Sports Medicine, Máxima Medical Center, The Netherlands c Department of Internal Medicine, Máxima Medical Center, The Netherlands d Department of Public and Occupational Health, VU University Medical Center, The Netherlands b
a r t i c l e
i n f o
Article history: Received 29 September 2011 Received in revised form 20 February 2012 Accepted 30 May 2012 Keywords: Physical endurance Exercise Value of life Asthenia Neoplasms Mediation analysis
a b s t r a c t Objectives: This study aims to investigate whether fatigue mediates the association between physical fitness and quality of life. Design: Uncontrolled pre–post intervention design. Methods: Pre- and post-intervention measurements were conducted in 119 patients who completed chemotherapy treatment for various types of cancer. The intervention was an 18-week exercise programme consisting of high-intensity resistance and interval training. We assessed physical fitness – peak oxygen uptake and peak power output – self-reported fatigue (Multidimensional Fatigue Inventory – subscales general fatigue, physical fatigue, reduced activity, reduced motivation, and mental fatigue-, and fatigue symptom scale of EORTC QLQ-C30) and quality of life (EORTC QLQ-C30, subscale global quality of life). Linear regression analyses were conducted on the residual change scores of the variables. The mediated effect of fatigue on the association between physical fitness and quality of life was examined using the products of coefficient method. Bootstrapping was used to calculate the confidence intervals. Results: We found significant associations between changes in physical fitness and global quality of life, between physical fitness and fatigue, and between fatigue and global quality of life. General fatigue mediated the positive association between peak power output and global quality of life, accounting for 82% of the total association. Physical fatigue, reduced activity, reduced motivation, and fatigue symptom were also mediators of this association. The mediation effects accounted for 91%, 76%, 38% and 71% of the total association, respectively. Reduced activity and reduced motivation mediated the association between peak oxygen uptake and global quality of life. Multiple mediation analyses showed that physical aspects of fatigue were stronger mediators than mental aspects. Conclusions: General fatigue and physical aspects of fatigue mediate the relationship between physical fitness and quality of life in cancer survivors. We found no mediating effect of mental fatigue. © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
1. Introduction Survival after cancer has improved substantially due to advances in early detection and treatment of cancer. In the Netherlands, 5year cancer survival rates have improved up to 52% for male and 61% for female patients across all cancers.1 However, cancer and its treatment are often associated with prolonged adverse psychosocial and physical symptoms including increased risk of anxiety, depression, fatigue, and reduced physical fitness and quality of life (QoL).2–4
∗ Corresponding author. E-mail address: [email protected] (L.M. Buffart).
Several literature reviews have reported that physical exercise may improve the QoL of cancer patients.2,5 In a previous study, we evaluated the effects of an 18-week high intensity resistance exercise programme on physical fitness, fatigue and QoL in 57 cancer patients who completed chemotherapy.6 We found significant improvements in patients’ global QoL after completion of the intervention (effect size = 0.82; 95% confidence interval (CI) = 0.53; 1.11),6 and these improvements persisted to 1 year follow up.7 However, the mechanism (i.e. mediators) underlying improvements in QoL are unclear. A possible mediator of exercise-induced improvements in QoL is fatigue (Supplement 1). Fatigue has been identified as one of the most common and distressing symptoms of cancer patients,8,9 having a profound effect on QoL.9,10 Previous meta-analyses have shown that physical exercise may reduce fatigue.5,11,12 Schwartz13 evaluated the
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Table 1 Characteristics of patients who did and did not complete the exercise program and of those with complete and incomplete data. Variable
Age, mean (SD) years Gender, n (%) male Type of cancer, n (%) Breast Colorectal Genital organs Haematological Other Treatment, n (%) Chemotherapy Radiotherapy Surgery Time between last chemotherapy and start training, n (SD) weeks
Exercise program
Measurements
Completers (n = 179)
Drop-out (n = 48)
p-Value
Complete (n = 119)
Incomplete (n = 60)
p-Value
49.5 (10.1) 39 (20%)
50.0 (9.8) 13 (27%)
0.722 0.325 0.289
50.3 (9.1) 25 (21%)
48.0 (11.7) 11 (18%)
0.148 0.844 0.950
111 (62%) 19 (11%) 21 (12%) 25 (14%) 3 (1%) N/A
27 (56%) 6 (13%) 3 (1%) 9 (19%) 3 (1%) N/A
74 (62%) 14 (12%) 13 (11%) 16 (13%) 2 (2%)
37 (62%) 5 (8%) 8 (13%) 9 (15%) 1 (2%)
119 (100%) 68 (57%) 102 (86%) 17.2 (9.5)
60 (100%) 31 (52%) 52 (87%) 22.8 (13.6)
N/A
N/A
effects of an 8-week home-based, low-to-moderate intensity aerobic exercise programme on fatigue and QoL in a small sample of 27 women who received chemotherapy for breast cancer. She reported that functional ability and energy expenditure were associated with QoL, and that these associations were mediated by fatigue.13 However, it is unclear whether these findings are valid for other parameters of physical fitness, for patients who are in a different phase of cancer treatment, or for other types of exercise programmes. More insight into the mechanisms of how exercise improves QoL is necessary for the systematic progression of research in this field and to better inform future exercise-based cancer rehabilitation. Therefore, the current study aims to investigate whether changes in fatigue mediate the association between changes in physical fitness and changes in QoL in a relatively large sample of patients who completed a high-intensity exercise programme after completion of chemotherapy for various types of cancer. 2. Methods We conducted an uncontrolled clinical trial with a pre–post-test design in the Maxima Medical Centre, Veldhoven, the Netherlands. From March 2002 to January 2007, patients enrolled in an 18-week high-intensity exercise programme that was implemented as part of usual care for cancer survivors. Patients with histological confirmed cancer with no indication of recurrent or progressive disease and who had completed chemotherapy with curative intention were eligible. Exclusion criteria were: (1) not capable of performing basic skills like sitting or lying down, (2) cognitive disorders or severe emotional instability, and (3) other serious diseases that might hamper physical performance (e.g., heart failure, chronic obstructive pulmonary disease). All patients signed an informed consent statement prior to participation. The Medical Ethics Committee of the Maxima Medical Centre approved the study. Patients started training at a minimum of 6 weeks after completing chemotherapy to a maximum of 52 weeks. From March 2002 until January 2007, 227 patients were included in the study, of whom 48 did not complete the training programme; there were five deaths during the exercise programme due to the cancer, fourteen patients had recurrence or metastasis of cancer, sixteen patients had other medical reasons for which they were not capable to continue the programme, nine had personal or work-related problems, the programme was too strenuous for two patients, and for a further two patients the cause of non-completion is unknown. In total, 179 patients completed the exercise programme. Complete data regarding physical fitness, fatigue and HRQoL were available of 119 patients. Demographic and
1.00 0.526 1.00 0.002
clinical characteristics did not differ between patients who completed the exercise program (n = 179) and those who did not (n = 48) and between patients who had complete data on the outcome measures (n = 119) and those who did not (n = 60), see Table 1. However, patients who completed all measurements started sooner after completion of therapy compared to patients with incomplete measurements (p = 0.002). The 18-week exercise programme consisted of high-intensity resistance and interval training. Six resistance exercises targeting the large muscle groups were performed at 65–80% of onerepetition maximum and consisted of two sets of 10 repetitions. The interval training consisted of cycling two times for 8 min, before and after the resistance exercises at alternating workloads. The patients trained in groups of 6–8 on specialised resistance training equipment and on bicycle ergometers under the supervision of physical therapists. During the first 12 weeks, patients trained twice a week. In the last 6 weeks, patients trained once a week. Detailed descriptions of the training programme can be found elsewhere.6 Measures of body composition, physical fitness, fatigue and health-related quality of life were assessed before (T0) and after the 18-week exercise programme (T1). Body mass index (BMI) was calculated from height and weight. Percentage body fat was determined from body weight and measurements of skinfold thickness at biceps, triceps, subscapular and suprailiac using the equation of Durnin and Womersley.14 Physical fitness was assessed during a maximum exercise test performed on a cycle ergometer (Corival, Lode, The Netherlands). Expired gases were collected and analysed breath by breath for O2 , CO2 , and flow and volume indices (Jaeger Oxycon Alpha, Jaeger, Hoechberg, Germany). Volumes and gas analyzers were calibrated before each test. Electrocardiogram was continuously monitored. Patients were instructed and encouraged to continue exercise until exhaustion. The test ended when patients were unable to maintain the required pedalling frequency of 70 rpm. At the end of the test, peak power output (PeakPO) and peak oxygen consumption (peakVO2 ) were registered. This test was performed according to the standard protocol as described previously.6 Fatigue was assessed using the Multidimensional Fatigue Inventory (MFI).15 This questionnaire consists of 20 statements for which the person indicates on a 7-point scale the extent to which the particular statement applies to him or her. The statement refers to aspects of fatigue experienced during the previous few days. Higher scores indicate a higher degree of fatigue. This self-report instrument consists of five subscales based on different dimensions: general fatigue, physical fatigue, reduced activity, reduced motivation, and mental fatigue. The MFI subscales have good internal consistency (average Cronbach’s alpha = 0.84).15
L.M. Buffart et al. / Journal of Science and Medicine in Sport 16 (2013) 99–104
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Table 2 Pre- and post-intervention results of body composition, physical fitness, fatigue and health-related quality of life (HRQoL). n = 119
Body composition Body mass (kg) Body mass index (kg/m2 ) Body fat (%)b Physical Fitness PeakPO (W) PeakPO (W/kg) PeakVO2 (l/min)a PeakVO2 (ml/kg/min)a Fatigue (MFI) General Fatigue Physical Fatigue Reduced Activity Reduced Motivation Mental Fatigue HRQoL (EORTC-QLQ-C30) Physical functioninga Role functioninga Emotional functioning Cognitive functioning Social functioning Global quality of life Symptoms Fatiguea Nausea Pain a b
Pre-intervention
Post-intervention
Difference
Mean (SD)
Mean (SD)
Mean (SD)
p-Value
−1.5 (3.2) −0.5 (1.1) −0.8 (3.7)
<0.001 <0.001 0.043
22.9 (18.9) 0.3 (0.2) 0.23 (0.26) 2.4 (3.4)
<0.001 <0.001 <0.001 <0.001
75.7 (15.0) 26.2 (4.5) 35.3 (6.6)
77.2 (15.0) 26.7 (4.4) 36.1 (6.2)
150.8 (44.7) 2.0 (0.5) 1.99 (0.53) 26.6 (5.8)
173.8 (54.5) 2.3 (0.6) 2.23 (0.58) 29.0 (6.0)
13.9 (4.1) 14.0 (4.1) 12.0 (3.8) 8.6 (3.1) 11.2 (4.7)
10.5 (3.9) 9.2 (3.4) 8.6 (3.4) 7.9 (2.8) 10.8 (6.1)
−3.3 (4.2) −4.8 (4.4) −3.4 (4.1) −0.7 (2.9) −0.4 (5.6)
<0.001 <0.001 <0.001 0.008 0.388
72.3 (18.5) 55.9 (23.2) 75.4 (20.1) 73.3 (24.4) 70.7 (24.4) 63.6 (16.4)
86.4 (15.4) 76.6 (23.4) 81.8 (18.0) 77.9 (22.1) 83.5 (19.2) 75.1 (15.1)
14.1 (18.0) 20.6 (26.0) 6.4 (19.6) 4.6 (19.6) 12.7 (25.6) 11.5 (16.8)
<0.001 <0.001 0.001 0.012 <0.001 <0.001
43.0 (23.0) 7.3 (15.7) 21.7 (22.6)
25.7 (20.5) 2.8 (7.6) 20.7 (23.0)
−17.3 (22.7) 4.5 (16.9) 1.0 (22.4)
<0.001 0.005 0.633
n−1 n = 98.
Health-related quality of life (HRQoL) was assessed using the European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire C30 (EORTC QLQ-C30). This questionnaire has high reliability and validity.16,17 The EORTC QLQ-C30 encompasses 30 items divided into six functional scales (physical, role, cognitive, emotional and social functioning, and a global QoL scale), three symptom scales (fatigue, nausea, and pain), and six individual items. Since this study focused on the underlying mediating associations, all analyses were based on complete cases, and conducted using SPSS 15. We calculated mean and standard deviations (SD) or numbers and percentages of patient characteristics, and preand post-intervention values of body composition, physical fitness, fatigue and QoL. Pre- and post-intervention values were compared using a paired sample T-test. We calculated residual change scores of the independent variable (physical fitness: peakPO and peakVO2 ), the dependent variable (global QoL scale of the EORTC-QLQ-C30) and the mediator variable (fatigue: MFI subscales and the fatigue symptom scale of the EORTC-QLQ-C30), by regressing the post-test values onto their pre-test values. Residual change scores represent the amount of change in the variables independent of pre-test values. Since we were interested in changes in physical fitness over time within patients, we used absolute values of peakPO and peakVO2 as these are not influenced by changes in body mass. A series of linear regression analyses were conducted on the residual change scores according to the product of coefficient method described by MacKinnon.18 First, we calculated the total association between physical fitness and global QoL (main effect, c-path). Second, we calculated the association between physical fitness and the potential mediator fatigue (a-path). Third, we calculated the association between the potential mediators and global QoL, controlled for physcial fitness (b-path). The final regression model provided estimates for the b-values and for the direct association (c -path). All regression models were adjusted for
relevant patient and clinical characteristics: sex, age and tumour type (breast cancer vs other), and time between last chemotherapy. The product of coefficients (a × b) provides an estimate of the relative strength of the mediation effect (Supplement 1).18 The proportion mediated is estimated by dividing the mediation effect (a × b) by the total effect (c-path). Subsequently, a bootstrapping method (with n = 5000 bootstrap resamples) was used to calculate the bias corrected confidence intervals (CI) around the mediated and direct effects using the SPSS macro suggested by Preacher and Hayes.19 In contrast to Baron and Kenny,20 the product of coefficient method suggests that potential mediating effects should also be analysed if the c-coefficient (total association between the independent and dependent variable) is not significant. Therefore, we also conducted mediating analyses in case the association between change in physical fitness and change in QoL was not significant. In case both physical and mental aspects of fatigue (physical fatigue, mental fatigue, reduced activity or reduced motivation) significantly mediated the association between physical fitness and global QoL, we conducted multiple mediation analyses to identify the strongest mediator (Supplement 2). 3. Results Table 2 presents pre- and post-intervention results on physical fitness, fatigue and HRQoL. At post-intervention, significant improvements were found for physical fitness, fatigue and HRQoL compared with pre-intervention, except for mental fatigue and pain, which remained unchanged. In the first step of the mediation analyses the associations between change in physical fitness and change in global QoL (path c, total effect) were examined (Table 3). Change in peakPO was associated with change in global QoL (c = 0.16, 95% CI = 0.02; 0.30). In contrast, there was no association between peakVO2 and global QoL (c = 2.97, 95% CI = −6.68; 12.62).
102 Table 3 The total association (c), direct association (c ) between physical fitness and global QoL, the association between physical fitness and the potential mediators (a-path), associations between mediators and global QoL (b-path), and mediation effect (a × b). Independent variable
Mediator variable
Estimate (95% CI) PeakPO (W) Single mediation
Multiple mediation
0.16 (0.02; 0.30)*
General fatigue Physical fatigue Reduced activity Reduced motivation Mental fatigue Fatigue symptoma
0.16 (0.02; 0.30)*
Direct association between physical fitness and global QoL, adjusted for mediators (path c’) Estimate (95% CI) 0.03 (−0.11; 0.16) 0.01 (−0.11; 0.14) 0.04 (−0.09; 0.17) 0.10 (−0.05; 0.25) 0.17 (0.02; 0.31)* 0.05 (−0.08; 0.17)
2.97 (−6.68; 12.62)
Multiple mediation
2.97 (−6.68; 12.62)
General fatigue Physical fatigue Reduced activity Reduced motivation Mental fatigue Fatigue symptoma
*
Mediation effect: (a × b)
Estimate (95% CI)
Estimate (95% CI)
Estimate (95% CI)
−0.07 (−0.11; −0.04)* −0.06 (−0.09; −0.03)* −0.06 (−0.09; −0.03)* −0.05 (−0.08; −0.03)* −0.03 (−0.08; 0.03) −0.28 (−0.47; −0.08)*
−1.90 (−2.58; −1.22)* −2.52 (−3.19; −1.86)* −2.08 (−2.80; −1.37)* −1.18 (−2.23; −0.08)* 0.15 (−0.30; 0.61) −0.41 (−0.53; −0.30)*
0.13 (0.06; 0.24)* 0.15 (0.06; 0.25)* 0.12 (0.04; 0.24)* 0.06 (0.01; 0.13)* 0.00 (−0.04; 0.03) 0.11 (0.04; 0.21)*
−0.06 (−0.09; −0.03)* −0.06 (−0.09; −0.03)* −0.05 (−0.08; −0.03)*
−2.05 (−2.92; −1.18)* −0.78 (−1.69; 0.14) 0.11 (−0.89; 1.11)
0.16 (0.07; 0.27)*
0.65 (−7.78; 9.08) 0.39 (−8.16; 7.37) −2.90 (−11.43; 5.63) −0.43 (−10.01; 9.23) 2.91 (−6.78; 12.60) 1.18 (−6.85; 9.20)
−1.18 (−3.64; 1.27) −1.32 (−3.53; 1.00) −2.64 (−4.86; −0.42)* −2.24 (−3.88; −0.60)* 0.56 (−3.32; 4.44) −4.30 (−17.68; 9.07)
−1.96 (−2.60; −1.32)* −2.56 (−3.19; −1.92)* −2.22 (−2.93; −1.52)* −1.52 (−2.59; −0.45)* 0.11 (−0.36; 0.57) −0.42 (−0.54; −0.31)*
2.32 (−2.71; 8.63) 3.36 (−2.38; 10.07) 5.87 (1.37; 12.22)* 3.40 (0.68; 8.88)* 0.06 (−1.01; 2.28) 1.82 (−4.91; 8.55)
−2.64 (−4.86; −0.42)* −2.24 (−3.88; −0.60)*
−2.16 (−2.95; −1.37)* −0.21 (−1.28; 0.86)
6.15 (1.05; 12.60)*
−3.18 (−11.87; 5.51) Reduced activity Reduced motivation
a
Association between mediators and global QoL (path b)
0.003 (−0.10; 0.17) Physical fatigue Reduced activity Reduced motivation
PeakVO2 (l/min) Single mediation
Association between physical fitness and the potential mediators (path a)
Fatigue as measured with the fatigue symptom scale of the EORTC-QLQ-C30. p < 0.05. Significant mediation effects are presented in bold. The analyses were adjusted for gender, age, and tumour type (breast vs other), and number of weeks between last chemotherapy and start training.
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Total association between physical fitness and global QoL (path c)
L.M. Buffart et al. / Journal of Science and Medicine in Sport 16 (2013) 99–104
The associations between change in physical fitness and fatigue (path a) were examined in the second step of the mediation analyses (Table 3). Change in PeakPO was associated with changes in general fatigue (a = −0.07, 95% CI = −011; −0.04), physical fatigue (a = −0.06, 95% CI = −0.09; −0.03), reduced activity (a = −0.06, 95% CI = −0.09; −0.03), reduced motivation (−0.05, 95% CI = −0.08; 0.03), and the fatigue symptom scale (a = −0.28, 95% CI = −0.47; −0.08). Change in PeakPO was not associated with change in mental fatigue. Change in PeakVO2 was associated with changes in reduced activity (a = −2.64, 95% CI = −4.86; −0.42) and reduced motivation (a = −2.24, 95% CI = −3.88; −0.60), but not with general fatigue, physical fatigue, mental fatigue and the fatigue symptom scale. In the third step of the mediation analyses, the associations between potential mediators and global QoL (path b) were examined (Table 3). For peakPO, the following mediators were associated with global QoL: general fatigue (b = −1.90, 95% CI = −2.58; −1.22), physical fatigue (b = −2.52, 95% CI = −3.19; −1.86), reduced activity (b = −2.08, 95% CI = −2.80; −1.37), reduced motivation (b = −1.18, 95% CI = −2.23; −0.08), and the fatigue symptom scale (b = −0.41, 95% CI = −0.53; −0.30). When physical (physical fatigue and reduced activity) and mental aspects (reduced motivation) were both added in the multiple mediation model (Supplement 2), only the association between physical fatigue and global QoL remained significant (b = −2.05, 95% CI = −2.92; −1.18; Table 3). For PeakVO2 , the mediators general fatigue (b = −1.96, 95% CI = −2.60; −1.32), physical fatigue (b = −2.56, 95% CI = −3.19; −1.92), reduced activity (b = −2.22, 95% CI = −2.93; −1.52), reduced motivation (b = −1.52, 95% CI = −2.59; −0.45), and the fatigue symptom scale (b = −0.42, 95% CI = −0.54; −0.31) were associated with global QoL (Table 3). In the multiple mediation model, the association between reduced activity and global QoL remained significant (b = −2.10, 95% CI = −2.95; −1.37). Finally, the mediation effects and direct effects (path c ) were examined. The mediation effect of change in general fatigue in the association between change in PeakPO and change in global QoL was significant (a × b = 0.13, 95% CI = 0.06; 0.24, see Table 2), and accounted for 82% of the total association. This resulted in an insignificant direct association (path c ) of 0.03 (95% CI = −0.11; 0.16). Also the MFI subscales physical fatigue (a × b = 0.15, 95% CI = 0.06; 0.25), reduced activity (a × b = 0.12, 95% CI = 0.04; 0.24), reduced motivation (a × b = 0.06, 95% CI = 0.01; 0.13) and the fatigue symptom scale of the EORTC-QLQ-C30 (a × b = 0.11, 95% CI = 0.04; 0.21) mediated the association between PeakPO and global QoL. The mediation effects accounted for 91%, 76%, 38% and 71% of the total associations, respectively. In the multiple mediation model, the mediation effect of physical fatigue was the strongest. Together with reduced activity and reduced motivation, the mediation effect was 0.16 (95% CI = 0.07; 0.27), accounting for 84% of the total association between PeakPO and global QoL (Table 3). Changes in reduced activity (a × b = 5.87, 95% CI = 1.37; 12.22) and reduced motivation (a × b = 3.40, 95% CI = 0.68; 8.88) significantly mediated the association between change in peakVO2 and change in global QoL (Table 3). No single mediation effect was found for general fatigue, physical fatigue, mental fatigue and fatigue symptom scale. The mediation effect of reduced activity and reduced motivation together was 6.15 (95% CI = 1.05; 12.60), but reduced motivation became insignificant, see Table 3.
4. Discussion This study provides further insight into mechanisms to improve QoL of cancer patients who completed chemotherapy. Similar to previous studies,5,21,22 the present study showed that increased physical fitness was significantly associated with improved global
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QoL. Furthermore, we found that this association was mediated by fatigue, suggesting that improved fitness improves global QoL by reducing fatigue. This mediation effect of fatigue is consistent with the previous finding of Schwartz13 who reported that improvements in functional ability and increases in energy expenditure were associated with improvements in QoL, and that these associations were mediated by their effects on fatigue. Thus, to improve QoL, it is important to reduce fatigue, which can be accomplished by improving levels of physical activity and fitness. Fatigue is a multidimensional concept covering both physical and mental aspects.23 In this study, we evaluated general fatigue, as well as physical and mental aspects, as potential mediators in the association between physical fitness and global QoL. Results of the present study indicate that the association between physical fitness and global QoL is mainly mediated by physical aspects of fatigue. However, although the single mediation analyses showed a mediating effect of reduced motivation, this effect disappeared in the multiple mediation analyses. This suggests that the mediating effects of physical fatigue are stronger. Although the general fatigue scale encompasses both physical and mental aspects, the current study did not provide support for mediation by mental fatigue. Mental aspects of fatigue are perhaps more likely to be influenced by concepts other than physical fitness, as targeted by, for example, psychosocial interventions.24 On the other hand, physical exercise may also have beneficial effects on psychological well-being,5,25,26 suggesting that it has the potential to improve mental aspects of fatigue as well. In addition to mental and physical aspects, inflammatory processes may also be involved in cancer-related fatigue.27 In the current study, we evaluated both peakPO and PeakVO2 as measures of physical fitness. Results showed that the association between change in peakPO and global QoL was significant, while this was not the case for change in peakVO2 . Also Herrero et al.21 reported a significant association between QoL and PeakPO in a small sample of breast cancer survivors, but not between QoL and peakVO2 . Although both variables are indicators of physical fitness, they are slightly different concepts. PeakVO2 is considered to be a measure of general fitness whereas peakPO is a measure of functional capacity, determined not only by peakVO2 , but also by mechanical efficiency and anaerobic power production.28 This may explain the stronger relationship between peakPO and global QoL. The lack of association with peakVO2 may also have a statistical cause due to relatively high standard deviations compared to peakPO. Several limitations of this study should be taken into account when interpreting the results. The first limitation is related to the study design. This study was not a randomised controlled trial and lacked a non-exercise control group. Therefore, we were unable to establish true causal pathways, the reverse relation may also be present: patients may have improved global QoL over time, causing less feelings of fatigue, and consequently be more physically active resulting in larger improvements in physical fitness. Future randomised controlled trials should confirm whether fatigue mediates the effect of exercise interventions on global QoL. Another limitation is related to the drop-out and missing data. Of the 227 patients who started with the exercise programme, 48 (21%) were unable to complete it, mostly due to cancer-recurrence or other diseases (63%). As a result, absolute values of QoL may be overestimated, since more healthy patients completed the intervention. Furthermore, of the 179 patients who completed the high intensity exercise programme, 119 patients (66%) had complete data for physical fitness, fatigue and HRQoL. The pre- and postintervention data was collected in a clinical setting rather than a research setting. This may have introduced a larger number of missing values for logistical reasons, limiting the power of the study. Nevertheless, performing analyses on complete cases is unlikely to have affected the mediation analyses presented.
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A third limitation is the lack of valid information regarding muscle strength. Thus the effect of changes in muscle strength on fatigue and QoL could not be examined. Finally, the present study is based on a heterogeneous group of cancer survivors. Future studies with larger samples are needed to investigate whether the mediators differ between types of cancer. Taking into account the abovementioned limitations, this study provides valuable insight into potential working mechanisms of improved global QoL after improving physical fitness in cancer survivors. Studies evaluating the mediators of the relationship between fitness and global QoL are scarce. Results from this study indicate that reducing fatigue is important to improve global QoL, and improving physical fitness (peakPO) may be effective in improving global QoL by reducing fatigue. Future studies should provide more insight into the most important parameters of physical fitness, e.g. aerobic fitness, or muscle strength, with respect to fatigue reduction, and the most optimal exercise intensity. 5. Conclusion Results showed that general fatigue and physical aspects of fatigue mediate the relationship between physical fitness and global QoL. We found no mediating effect of mental fatigue. Cancer rehabilitation programmes should also aim to improve physical fitness, since it may reduce fatigue and improve QoL. Practical implications • Improving physical fitness in cancer patients improves their quality of life. • Improving physical fitness in cancer patients reduces their level of fatigue. • Decreasing fatigue in cancer patients improves their quality of life. • Physical fitness-induced improvements in quality of life can be explained by improvements in fatigue. Conflicts of interest None. Financial support This research was funded by Alpe d’HuZes/KWF fund, provided by the Dutch Cancer Society, and the research foundation of Máxima Medical Center. The contribution of L.M. Buffart was further supported by a fellowship granted by the EMGO Institute for Health and Care Research. Acknowledgements The authors thank all patients for participating in this study. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.jsams.2012.05.014.
References 1. Integraal Kanker Centrum Nederland. 2011. Cijfers over kanker. Overleving| Alle tumoren; geslacht. Available at: http://www.cijfersoverkanker.nl. Accessed 29 September 2011. 2. Courneya KS, Friedenreich CM. Physical exercise and quality of life following cancer diagnosis: a literature review. Ann Behav Med 1999; 21(2):171–179. 3. Courneya KS. Exercise in cancer survivors: an overview of research. Med Sci Sports Exerc 2003; 35(11):1846–1852. 4. Lucia A, Earnest C, Perez M. Cancer-related fatigue: can exercise physiology assist oncologists? Lancet Oncol 2003; 4(10):616–625. 5. Speck RM, Courneya KS, Masse LC et al. An update of controlled physical activity trials in cancer survivors: a systematic review and meta-analysis. J Cancer Surviv 2010; 4:87–100. 6. De Backer I, van Breda E, Vreugdenhil A et al. High-intensity strength training improves quality of life in cancer survivors. Acta Oncol 2007; 46(8):1143–1151. 7. De Backer I, Vreugdenhil G, Nijziel MR et al. Long-term follow-up after cancer rehabilitation using high-intensity resistance training: persistent improvement of physical performance and quality of life. Br J Cancer 2008; 99(1):30–36. 8. Ahlberg K, Ekman T, Gaston-Johansson F et al. Assessment and management of cancer-related fatigue in adults. Lancet 2003; 362(9384):640–650. 9. Curt GA, Breitbart W, Cella D et al. Impact of cancer-related fatigue on the lives of patients: new findings from the fatigue coalition. Oncologist 2000; 5(5):353–360. 10. Curt GA. Impact of fatigue on quality of life in oncology patients. Semin Hematol 2000; 37(4 Suppl 6):14–17. 11. Cramp F, Daniel J. Exercise for the management of cancer-related fatigue in adults. Cochrane Database Syst Rev 2008;(2):CD006145. 12. Arnold M, Taylor NF. Does exercise reduce cancer-related fatigue in hospitalised oncology patients? A systematic review. Onkologie 2010; 33(11):625–630. 13. Schwartz AL. Fatigue mediates the effects of exercise on quality of life. Qual Life Res 1999; 8(6):529–538. 14. Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 1974; 32(1):77–97. 15. Smets EM, Garssen B, Bonke B et al. The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue. J Psychosom Res 1995; 39(3):315–325. 16. Aaronson NK, Ahmedzai S, Bergman B et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 1993; 85(5): 365–376. 17. Groenvold M, Klee MC, Sprangers MA et al. Validation of the EORTC QLQ-C30 quality of life questionnaire through combined qualitative and quantitative assessment of patient-observer agreement. J Clin Epidemiol 1997; 50(4):441–450. 18. MacKinnon DP. Introduction to Statistical Mediation Analysis, New York, Lawrence Erlbaum Associates, Taylor & Francis Group, 2008. 19. Preacher KJ, Hayes AF. SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav Res Methods Instrum Comput 2004; 36(4):717–731. 20. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986; 51(6):1173–1182. 21. Herrero F, Balmer J, San Juan AF et al. Is cardiorespiratory fitness related to quality of life in survivors of breast cancer? J Strength Cond Res 2006; 20(3):535–540. 22. Jones LW, Courneya KS, Vallance JK et al. Association between exercise and quality of life in multiple myeloma cancer survivors. Support Care Cancer 2004; 12(11):780–788. 23. Zwarts MJ, Bleijenberg G, van Engelen BG. Clinical neurophysiology of fatigue. Clin Neurophysiol 2008; 119(1):2–10. 24. Goedendorp MM, Gielissen MF, Verhagen CA, Bleijenberg G. Psychosocial interventions for reducing fatigue during cancer treatment in adults. Cochrane Database Syst Rev 2009; 1:CD006953. 25. Blacklock R, Rhodes R, Blanchard C, Gaul C. Effects of exercise intensity and selfefficacy on state anxiety with breast cancer survivors. Oncol Nurs Forum 2010; 37(2):206–212. 26. Dimeo F, Stieglitz RD, Novelli-Fischer U, Fetscher S, Mertelsmann R, Keul J. Correlation between physical performance and fatigue in cancer patients. Ann Oncol 1997; 8(12):1251–1255. 27. Bower JE. Cancer-related fatigue: links with inflammation in cancer patients and survivors. Brain Behav Immun 2007; 21(7):863–871. 28. van der Woude LH, Bouten C, Veeger HE, Gwinn T. Aerobic work capacity in elite wheelchair athletes: a cross-sectional analysis. Am J Phys Med Rehabil 2002; 81(4):261–271.
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Journal of Science and Medicine in Sport journal homepage: www.elsevier.com/locate/jsams
Original research
Fatigue mediates the relationship between physical fitness and quality of life in cancer survivors Laurien M. Buffart a,∗ , Ingrid C. De Backer b , Goof Schep b , Art Vreugdenhil d , Johannes Brug a , Mai J.M. Chinapaw c a
Department of Epidemiology and Biostatistics, VU University Medical Center, The Netherlands Department of Sports Medicine, Máxima Medical Center, The Netherlands c Department of Internal Medicine, Máxima Medical Center, The Netherlands d Department of Public and Occupational Health, VU University Medical Center, The Netherlands b
a r t i c l e
i n f o
Article history: Received 29 September 2011 Received in revised form 20 February 2012 Accepted 30 May 2012 Keywords: Physical endurance Exercise Value of life Asthenia Neoplasms Mediation analysis
a b s t r a c t Objectives: This study aims to investigate whether fatigue mediates the association between physical fitness and quality of life. Design: Uncontrolled pre–post intervention design. Methods: Pre- and post-intervention measurements were conducted in 119 patients who completed chemotherapy treatment for various types of cancer. The intervention was an 18-week exercise programme consisting of high-intensity resistance and interval training. We assessed physical fitness – peak oxygen uptake and peak power output – self-reported fatigue (Multidimensional Fatigue Inventory – subscales general fatigue, physical fatigue, reduced activity, reduced motivation, and mental fatigue-, and fatigue symptom scale of EORTC QLQ-C30) and quality of life (EORTC QLQ-C30, subscale global quality of life). Linear regression analyses were conducted on the residual change scores of the variables. The mediated effect of fatigue on the association between physical fitness and quality of life was examined using the products of coefficient method. Bootstrapping was used to calculate the confidence intervals. Results: We found significant associations between changes in physical fitness and global quality of life, between physical fitness and fatigue, and between fatigue and global quality of life. General fatigue mediated the positive association between peak power output and global quality of life, accounting for 82% of the total association. Physical fatigue, reduced activity, reduced motivation, and fatigue symptom were also mediators of this association. The mediation effects accounted for 91%, 76%, 38% and 71% of the total association, respectively. Reduced activity and reduced motivation mediated the association between peak oxygen uptake and global quality of life. Multiple mediation analyses showed that physical aspects of fatigue were stronger mediators than mental aspects. Conclusions: General fatigue and physical aspects of fatigue mediate the relationship between physical fitness and quality of life in cancer survivors. We found no mediating effect of mental fatigue. © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
1. Introduction Survival after cancer has improved substantially due to advances in early detection and treatment of cancer. In the Netherlands, 5year cancer survival rates have improved up to 52% for male and 61% for female patients across all cancers.1 However, cancer and its treatment are often associated with prolonged adverse psychosocial and physical symptoms including increased risk of anxiety, depression, fatigue, and reduced physical fitness and quality of life (QoL).2–4
∗ Corresponding author. E-mail address: [email protected] (L.M. Buffart).
Several literature reviews have reported that physical exercise may improve the QoL of cancer patients.2,5 In a previous study, we evaluated the effects of an 18-week high intensity resistance exercise programme on physical fitness, fatigue and QoL in 57 cancer patients who completed chemotherapy.6 We found significant improvements in patients’ global QoL after completion of the intervention (effect size = 0.82; 95% confidence interval (CI) = 0.53; 1.11),6 and these improvements persisted to 1 year follow up.7 However, the mechanism (i.e. mediators) underlying improvements in QoL are unclear. A possible mediator of exercise-induced improvements in QoL is fatigue (Supplement 1). Fatigue has been identified as one of the most common and distressing symptoms of cancer patients,8,9 having a profound effect on QoL.9,10 Previous meta-analyses have shown that physical exercise may reduce fatigue.5,11,12 Schwartz13 evaluated the
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Table 1 Characteristics of patients who did and did not complete the exercise program and of those with complete and incomplete data. Variable
Age, mean (SD) years Gender, n (%) male Type of cancer, n (%) Breast Colorectal Genital organs Haematological Other Treatment, n (%) Chemotherapy Radiotherapy Surgery Time between last chemotherapy and start training, n (SD) weeks
Exercise program
Measurements
Completers (n = 179)
Drop-out (n = 48)
p-Value
Complete (n = 119)
Incomplete (n = 60)
p-Value
49.5 (10.1) 39 (20%)
50.0 (9.8) 13 (27%)
0.722 0.325 0.289
50.3 (9.1) 25 (21%)
48.0 (11.7) 11 (18%)
0.148 0.844 0.950
111 (62%) 19 (11%) 21 (12%) 25 (14%) 3 (1%) N/A
27 (56%) 6 (13%) 3 (1%) 9 (19%) 3 (1%) N/A
74 (62%) 14 (12%) 13 (11%) 16 (13%) 2 (2%)
37 (62%) 5 (8%) 8 (13%) 9 (15%) 1 (2%)
119 (100%) 68 (57%) 102 (86%) 17.2 (9.5)
60 (100%) 31 (52%) 52 (87%) 22.8 (13.6)
N/A
N/A
effects of an 8-week home-based, low-to-moderate intensity aerobic exercise programme on fatigue and QoL in a small sample of 27 women who received chemotherapy for breast cancer. She reported that functional ability and energy expenditure were associated with QoL, and that these associations were mediated by fatigue.13 However, it is unclear whether these findings are valid for other parameters of physical fitness, for patients who are in a different phase of cancer treatment, or for other types of exercise programmes. More insight into the mechanisms of how exercise improves QoL is necessary for the systematic progression of research in this field and to better inform future exercise-based cancer rehabilitation. Therefore, the current study aims to investigate whether changes in fatigue mediate the association between changes in physical fitness and changes in QoL in a relatively large sample of patients who completed a high-intensity exercise programme after completion of chemotherapy for various types of cancer. 2. Methods We conducted an uncontrolled clinical trial with a pre–post-test design in the Maxima Medical Centre, Veldhoven, the Netherlands. From March 2002 to January 2007, patients enrolled in an 18-week high-intensity exercise programme that was implemented as part of usual care for cancer survivors. Patients with histological confirmed cancer with no indication of recurrent or progressive disease and who had completed chemotherapy with curative intention were eligible. Exclusion criteria were: (1) not capable of performing basic skills like sitting or lying down, (2) cognitive disorders or severe emotional instability, and (3) other serious diseases that might hamper physical performance (e.g., heart failure, chronic obstructive pulmonary disease). All patients signed an informed consent statement prior to participation. The Medical Ethics Committee of the Maxima Medical Centre approved the study. Patients started training at a minimum of 6 weeks after completing chemotherapy to a maximum of 52 weeks. From March 2002 until January 2007, 227 patients were included in the study, of whom 48 did not complete the training programme; there were five deaths during the exercise programme due to the cancer, fourteen patients had recurrence or metastasis of cancer, sixteen patients had other medical reasons for which they were not capable to continue the programme, nine had personal or work-related problems, the programme was too strenuous for two patients, and for a further two patients the cause of non-completion is unknown. In total, 179 patients completed the exercise programme. Complete data regarding physical fitness, fatigue and HRQoL were available of 119 patients. Demographic and
1.00 0.526 1.00 0.002
clinical characteristics did not differ between patients who completed the exercise program (n = 179) and those who did not (n = 48) and between patients who had complete data on the outcome measures (n = 119) and those who did not (n = 60), see Table 1. However, patients who completed all measurements started sooner after completion of therapy compared to patients with incomplete measurements (p = 0.002). The 18-week exercise programme consisted of high-intensity resistance and interval training. Six resistance exercises targeting the large muscle groups were performed at 65–80% of onerepetition maximum and consisted of two sets of 10 repetitions. The interval training consisted of cycling two times for 8 min, before and after the resistance exercises at alternating workloads. The patients trained in groups of 6–8 on specialised resistance training equipment and on bicycle ergometers under the supervision of physical therapists. During the first 12 weeks, patients trained twice a week. In the last 6 weeks, patients trained once a week. Detailed descriptions of the training programme can be found elsewhere.6 Measures of body composition, physical fitness, fatigue and health-related quality of life were assessed before (T0) and after the 18-week exercise programme (T1). Body mass index (BMI) was calculated from height and weight. Percentage body fat was determined from body weight and measurements of skinfold thickness at biceps, triceps, subscapular and suprailiac using the equation of Durnin and Womersley.14 Physical fitness was assessed during a maximum exercise test performed on a cycle ergometer (Corival, Lode, The Netherlands). Expired gases were collected and analysed breath by breath for O2 , CO2 , and flow and volume indices (Jaeger Oxycon Alpha, Jaeger, Hoechberg, Germany). Volumes and gas analyzers were calibrated before each test. Electrocardiogram was continuously monitored. Patients were instructed and encouraged to continue exercise until exhaustion. The test ended when patients were unable to maintain the required pedalling frequency of 70 rpm. At the end of the test, peak power output (PeakPO) and peak oxygen consumption (peakVO2 ) were registered. This test was performed according to the standard protocol as described previously.6 Fatigue was assessed using the Multidimensional Fatigue Inventory (MFI).15 This questionnaire consists of 20 statements for which the person indicates on a 7-point scale the extent to which the particular statement applies to him or her. The statement refers to aspects of fatigue experienced during the previous few days. Higher scores indicate a higher degree of fatigue. This self-report instrument consists of five subscales based on different dimensions: general fatigue, physical fatigue, reduced activity, reduced motivation, and mental fatigue. The MFI subscales have good internal consistency (average Cronbach’s alpha = 0.84).15
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101
Table 2 Pre- and post-intervention results of body composition, physical fitness, fatigue and health-related quality of life (HRQoL). n = 119
Body composition Body mass (kg) Body mass index (kg/m2 ) Body fat (%)b Physical Fitness PeakPO (W) PeakPO (W/kg) PeakVO2 (l/min)a PeakVO2 (ml/kg/min)a Fatigue (MFI) General Fatigue Physical Fatigue Reduced Activity Reduced Motivation Mental Fatigue HRQoL (EORTC-QLQ-C30) Physical functioninga Role functioninga Emotional functioning Cognitive functioning Social functioning Global quality of life Symptoms Fatiguea Nausea Pain a b
Pre-intervention
Post-intervention
Difference
Mean (SD)
Mean (SD)
Mean (SD)
p-Value
−1.5 (3.2) −0.5 (1.1) −0.8 (3.7)
<0.001 <0.001 0.043
22.9 (18.9) 0.3 (0.2) 0.23 (0.26) 2.4 (3.4)
<0.001 <0.001 <0.001 <0.001
75.7 (15.0) 26.2 (4.5) 35.3 (6.6)
77.2 (15.0) 26.7 (4.4) 36.1 (6.2)
150.8 (44.7) 2.0 (0.5) 1.99 (0.53) 26.6 (5.8)
173.8 (54.5) 2.3 (0.6) 2.23 (0.58) 29.0 (6.0)
13.9 (4.1) 14.0 (4.1) 12.0 (3.8) 8.6 (3.1) 11.2 (4.7)
10.5 (3.9) 9.2 (3.4) 8.6 (3.4) 7.9 (2.8) 10.8 (6.1)
−3.3 (4.2) −4.8 (4.4) −3.4 (4.1) −0.7 (2.9) −0.4 (5.6)
<0.001 <0.001 <0.001 0.008 0.388
72.3 (18.5) 55.9 (23.2) 75.4 (20.1) 73.3 (24.4) 70.7 (24.4) 63.6 (16.4)
86.4 (15.4) 76.6 (23.4) 81.8 (18.0) 77.9 (22.1) 83.5 (19.2) 75.1 (15.1)
14.1 (18.0) 20.6 (26.0) 6.4 (19.6) 4.6 (19.6) 12.7 (25.6) 11.5 (16.8)
<0.001 <0.001 0.001 0.012 <0.001 <0.001
43.0 (23.0) 7.3 (15.7) 21.7 (22.6)
25.7 (20.5) 2.8 (7.6) 20.7 (23.0)
−17.3 (22.7) 4.5 (16.9) 1.0 (22.4)
<0.001 0.005 0.633
n−1 n = 98.
Health-related quality of life (HRQoL) was assessed using the European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire C30 (EORTC QLQ-C30). This questionnaire has high reliability and validity.16,17 The EORTC QLQ-C30 encompasses 30 items divided into six functional scales (physical, role, cognitive, emotional and social functioning, and a global QoL scale), three symptom scales (fatigue, nausea, and pain), and six individual items. Since this study focused on the underlying mediating associations, all analyses were based on complete cases, and conducted using SPSS 15. We calculated mean and standard deviations (SD) or numbers and percentages of patient characteristics, and preand post-intervention values of body composition, physical fitness, fatigue and QoL. Pre- and post-intervention values were compared using a paired sample T-test. We calculated residual change scores of the independent variable (physical fitness: peakPO and peakVO2 ), the dependent variable (global QoL scale of the EORTC-QLQ-C30) and the mediator variable (fatigue: MFI subscales and the fatigue symptom scale of the EORTC-QLQ-C30), by regressing the post-test values onto their pre-test values. Residual change scores represent the amount of change in the variables independent of pre-test values. Since we were interested in changes in physical fitness over time within patients, we used absolute values of peakPO and peakVO2 as these are not influenced by changes in body mass. A series of linear regression analyses were conducted on the residual change scores according to the product of coefficient method described by MacKinnon.18 First, we calculated the total association between physical fitness and global QoL (main effect, c-path). Second, we calculated the association between physical fitness and the potential mediator fatigue (a-path). Third, we calculated the association between the potential mediators and global QoL, controlled for physcial fitness (b-path). The final regression model provided estimates for the b-values and for the direct association (c -path). All regression models were adjusted for
relevant patient and clinical characteristics: sex, age and tumour type (breast cancer vs other), and time between last chemotherapy. The product of coefficients (a × b) provides an estimate of the relative strength of the mediation effect (Supplement 1).18 The proportion mediated is estimated by dividing the mediation effect (a × b) by the total effect (c-path). Subsequently, a bootstrapping method (with n = 5000 bootstrap resamples) was used to calculate the bias corrected confidence intervals (CI) around the mediated and direct effects using the SPSS macro suggested by Preacher and Hayes.19 In contrast to Baron and Kenny,20 the product of coefficient method suggests that potential mediating effects should also be analysed if the c-coefficient (total association between the independent and dependent variable) is not significant. Therefore, we also conducted mediating analyses in case the association between change in physical fitness and change in QoL was not significant. In case both physical and mental aspects of fatigue (physical fatigue, mental fatigue, reduced activity or reduced motivation) significantly mediated the association between physical fitness and global QoL, we conducted multiple mediation analyses to identify the strongest mediator (Supplement 2). 3. Results Table 2 presents pre- and post-intervention results on physical fitness, fatigue and HRQoL. At post-intervention, significant improvements were found for physical fitness, fatigue and HRQoL compared with pre-intervention, except for mental fatigue and pain, which remained unchanged. In the first step of the mediation analyses the associations between change in physical fitness and change in global QoL (path c, total effect) were examined (Table 3). Change in peakPO was associated with change in global QoL (c = 0.16, 95% CI = 0.02; 0.30). In contrast, there was no association between peakVO2 and global QoL (c = 2.97, 95% CI = −6.68; 12.62).
102 Table 3 The total association (c), direct association (c ) between physical fitness and global QoL, the association between physical fitness and the potential mediators (a-path), associations between mediators and global QoL (b-path), and mediation effect (a × b). Independent variable
Mediator variable
Estimate (95% CI) PeakPO (W) Single mediation
Multiple mediation
0.16 (0.02; 0.30)*
General fatigue Physical fatigue Reduced activity Reduced motivation Mental fatigue Fatigue symptoma
0.16 (0.02; 0.30)*
Direct association between physical fitness and global QoL, adjusted for mediators (path c’) Estimate (95% CI) 0.03 (−0.11; 0.16) 0.01 (−0.11; 0.14) 0.04 (−0.09; 0.17) 0.10 (−0.05; 0.25) 0.17 (0.02; 0.31)* 0.05 (−0.08; 0.17)
2.97 (−6.68; 12.62)
Multiple mediation
2.97 (−6.68; 12.62)
General fatigue Physical fatigue Reduced activity Reduced motivation Mental fatigue Fatigue symptoma
*
Mediation effect: (a × b)
Estimate (95% CI)
Estimate (95% CI)
Estimate (95% CI)
−0.07 (−0.11; −0.04)* −0.06 (−0.09; −0.03)* −0.06 (−0.09; −0.03)* −0.05 (−0.08; −0.03)* −0.03 (−0.08; 0.03) −0.28 (−0.47; −0.08)*
−1.90 (−2.58; −1.22)* −2.52 (−3.19; −1.86)* −2.08 (−2.80; −1.37)* −1.18 (−2.23; −0.08)* 0.15 (−0.30; 0.61) −0.41 (−0.53; −0.30)*
0.13 (0.06; 0.24)* 0.15 (0.06; 0.25)* 0.12 (0.04; 0.24)* 0.06 (0.01; 0.13)* 0.00 (−0.04; 0.03) 0.11 (0.04; 0.21)*
−0.06 (−0.09; −0.03)* −0.06 (−0.09; −0.03)* −0.05 (−0.08; −0.03)*
−2.05 (−2.92; −1.18)* −0.78 (−1.69; 0.14) 0.11 (−0.89; 1.11)
0.16 (0.07; 0.27)*
0.65 (−7.78; 9.08) 0.39 (−8.16; 7.37) −2.90 (−11.43; 5.63) −0.43 (−10.01; 9.23) 2.91 (−6.78; 12.60) 1.18 (−6.85; 9.20)
−1.18 (−3.64; 1.27) −1.32 (−3.53; 1.00) −2.64 (−4.86; −0.42)* −2.24 (−3.88; −0.60)* 0.56 (−3.32; 4.44) −4.30 (−17.68; 9.07)
−1.96 (−2.60; −1.32)* −2.56 (−3.19; −1.92)* −2.22 (−2.93; −1.52)* −1.52 (−2.59; −0.45)* 0.11 (−0.36; 0.57) −0.42 (−0.54; −0.31)*
2.32 (−2.71; 8.63) 3.36 (−2.38; 10.07) 5.87 (1.37; 12.22)* 3.40 (0.68; 8.88)* 0.06 (−1.01; 2.28) 1.82 (−4.91; 8.55)
−2.64 (−4.86; −0.42)* −2.24 (−3.88; −0.60)*
−2.16 (−2.95; −1.37)* −0.21 (−1.28; 0.86)
6.15 (1.05; 12.60)*
−3.18 (−11.87; 5.51) Reduced activity Reduced motivation
a
Association between mediators and global QoL (path b)
0.003 (−0.10; 0.17) Physical fatigue Reduced activity Reduced motivation
PeakVO2 (l/min) Single mediation
Association between physical fitness and the potential mediators (path a)
Fatigue as measured with the fatigue symptom scale of the EORTC-QLQ-C30. p < 0.05. Significant mediation effects are presented in bold. The analyses were adjusted for gender, age, and tumour type (breast vs other), and number of weeks between last chemotherapy and start training.
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Total association between physical fitness and global QoL (path c)
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The associations between change in physical fitness and fatigue (path a) were examined in the second step of the mediation analyses (Table 3). Change in PeakPO was associated with changes in general fatigue (a = −0.07, 95% CI = −011; −0.04), physical fatigue (a = −0.06, 95% CI = −0.09; −0.03), reduced activity (a = −0.06, 95% CI = −0.09; −0.03), reduced motivation (−0.05, 95% CI = −0.08; 0.03), and the fatigue symptom scale (a = −0.28, 95% CI = −0.47; −0.08). Change in PeakPO was not associated with change in mental fatigue. Change in PeakVO2 was associated with changes in reduced activity (a = −2.64, 95% CI = −4.86; −0.42) and reduced motivation (a = −2.24, 95% CI = −3.88; −0.60), but not with general fatigue, physical fatigue, mental fatigue and the fatigue symptom scale. In the third step of the mediation analyses, the associations between potential mediators and global QoL (path b) were examined (Table 3). For peakPO, the following mediators were associated with global QoL: general fatigue (b = −1.90, 95% CI = −2.58; −1.22), physical fatigue (b = −2.52, 95% CI = −3.19; −1.86), reduced activity (b = −2.08, 95% CI = −2.80; −1.37), reduced motivation (b = −1.18, 95% CI = −2.23; −0.08), and the fatigue symptom scale (b = −0.41, 95% CI = −0.53; −0.30). When physical (physical fatigue and reduced activity) and mental aspects (reduced motivation) were both added in the multiple mediation model (Supplement 2), only the association between physical fatigue and global QoL remained significant (b = −2.05, 95% CI = −2.92; −1.18; Table 3). For PeakVO2 , the mediators general fatigue (b = −1.96, 95% CI = −2.60; −1.32), physical fatigue (b = −2.56, 95% CI = −3.19; −1.92), reduced activity (b = −2.22, 95% CI = −2.93; −1.52), reduced motivation (b = −1.52, 95% CI = −2.59; −0.45), and the fatigue symptom scale (b = −0.42, 95% CI = −0.54; −0.31) were associated with global QoL (Table 3). In the multiple mediation model, the association between reduced activity and global QoL remained significant (b = −2.10, 95% CI = −2.95; −1.37). Finally, the mediation effects and direct effects (path c ) were examined. The mediation effect of change in general fatigue in the association between change in PeakPO and change in global QoL was significant (a × b = 0.13, 95% CI = 0.06; 0.24, see Table 2), and accounted for 82% of the total association. This resulted in an insignificant direct association (path c ) of 0.03 (95% CI = −0.11; 0.16). Also the MFI subscales physical fatigue (a × b = 0.15, 95% CI = 0.06; 0.25), reduced activity (a × b = 0.12, 95% CI = 0.04; 0.24), reduced motivation (a × b = 0.06, 95% CI = 0.01; 0.13) and the fatigue symptom scale of the EORTC-QLQ-C30 (a × b = 0.11, 95% CI = 0.04; 0.21) mediated the association between PeakPO and global QoL. The mediation effects accounted for 91%, 76%, 38% and 71% of the total associations, respectively. In the multiple mediation model, the mediation effect of physical fatigue was the strongest. Together with reduced activity and reduced motivation, the mediation effect was 0.16 (95% CI = 0.07; 0.27), accounting for 84% of the total association between PeakPO and global QoL (Table 3). Changes in reduced activity (a × b = 5.87, 95% CI = 1.37; 12.22) and reduced motivation (a × b = 3.40, 95% CI = 0.68; 8.88) significantly mediated the association between change in peakVO2 and change in global QoL (Table 3). No single mediation effect was found for general fatigue, physical fatigue, mental fatigue and fatigue symptom scale. The mediation effect of reduced activity and reduced motivation together was 6.15 (95% CI = 1.05; 12.60), but reduced motivation became insignificant, see Table 3.
4. Discussion This study provides further insight into mechanisms to improve QoL of cancer patients who completed chemotherapy. Similar to previous studies,5,21,22 the present study showed that increased physical fitness was significantly associated with improved global
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QoL. Furthermore, we found that this association was mediated by fatigue, suggesting that improved fitness improves global QoL by reducing fatigue. This mediation effect of fatigue is consistent with the previous finding of Schwartz13 who reported that improvements in functional ability and increases in energy expenditure were associated with improvements in QoL, and that these associations were mediated by their effects on fatigue. Thus, to improve QoL, it is important to reduce fatigue, which can be accomplished by improving levels of physical activity and fitness. Fatigue is a multidimensional concept covering both physical and mental aspects.23 In this study, we evaluated general fatigue, as well as physical and mental aspects, as potential mediators in the association between physical fitness and global QoL. Results of the present study indicate that the association between physical fitness and global QoL is mainly mediated by physical aspects of fatigue. However, although the single mediation analyses showed a mediating effect of reduced motivation, this effect disappeared in the multiple mediation analyses. This suggests that the mediating effects of physical fatigue are stronger. Although the general fatigue scale encompasses both physical and mental aspects, the current study did not provide support for mediation by mental fatigue. Mental aspects of fatigue are perhaps more likely to be influenced by concepts other than physical fitness, as targeted by, for example, psychosocial interventions.24 On the other hand, physical exercise may also have beneficial effects on psychological well-being,5,25,26 suggesting that it has the potential to improve mental aspects of fatigue as well. In addition to mental and physical aspects, inflammatory processes may also be involved in cancer-related fatigue.27 In the current study, we evaluated both peakPO and PeakVO2 as measures of physical fitness. Results showed that the association between change in peakPO and global QoL was significant, while this was not the case for change in peakVO2 . Also Herrero et al.21 reported a significant association between QoL and PeakPO in a small sample of breast cancer survivors, but not between QoL and peakVO2 . Although both variables are indicators of physical fitness, they are slightly different concepts. PeakVO2 is considered to be a measure of general fitness whereas peakPO is a measure of functional capacity, determined not only by peakVO2 , but also by mechanical efficiency and anaerobic power production.28 This may explain the stronger relationship between peakPO and global QoL. The lack of association with peakVO2 may also have a statistical cause due to relatively high standard deviations compared to peakPO. Several limitations of this study should be taken into account when interpreting the results. The first limitation is related to the study design. This study was not a randomised controlled trial and lacked a non-exercise control group. Therefore, we were unable to establish true causal pathways, the reverse relation may also be present: patients may have improved global QoL over time, causing less feelings of fatigue, and consequently be more physically active resulting in larger improvements in physical fitness. Future randomised controlled trials should confirm whether fatigue mediates the effect of exercise interventions on global QoL. Another limitation is related to the drop-out and missing data. Of the 227 patients who started with the exercise programme, 48 (21%) were unable to complete it, mostly due to cancer-recurrence or other diseases (63%). As a result, absolute values of QoL may be overestimated, since more healthy patients completed the intervention. Furthermore, of the 179 patients who completed the high intensity exercise programme, 119 patients (66%) had complete data for physical fitness, fatigue and HRQoL. The pre- and postintervention data was collected in a clinical setting rather than a research setting. This may have introduced a larger number of missing values for logistical reasons, limiting the power of the study. Nevertheless, performing analyses on complete cases is unlikely to have affected the mediation analyses presented.
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A third limitation is the lack of valid information regarding muscle strength. Thus the effect of changes in muscle strength on fatigue and QoL could not be examined. Finally, the present study is based on a heterogeneous group of cancer survivors. Future studies with larger samples are needed to investigate whether the mediators differ between types of cancer. Taking into account the abovementioned limitations, this study provides valuable insight into potential working mechanisms of improved global QoL after improving physical fitness in cancer survivors. Studies evaluating the mediators of the relationship between fitness and global QoL are scarce. Results from this study indicate that reducing fatigue is important to improve global QoL, and improving physical fitness (peakPO) may be effective in improving global QoL by reducing fatigue. Future studies should provide more insight into the most important parameters of physical fitness, e.g. aerobic fitness, or muscle strength, with respect to fatigue reduction, and the most optimal exercise intensity. 5. Conclusion Results showed that general fatigue and physical aspects of fatigue mediate the relationship between physical fitness and global QoL. We found no mediating effect of mental fatigue. Cancer rehabilitation programmes should also aim to improve physical fitness, since it may reduce fatigue and improve QoL. Practical implications • Improving physical fitness in cancer patients improves their quality of life. • Improving physical fitness in cancer patients reduces their level of fatigue. • Decreasing fatigue in cancer patients improves their quality of life. • Physical fitness-induced improvements in quality of life can be explained by improvements in fatigue. Conflicts of interest None. Financial support This research was funded by Alpe d’HuZes/KWF fund, provided by the Dutch Cancer Society, and the research foundation of Máxima Medical Center. The contribution of L.M. Buffart was further supported by a fellowship granted by the EMGO Institute for Health and Care Research. Acknowledgements The authors thank all patients for participating in this study. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.jsams.2012.05.014.
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