Multidimensional Measurement of Fatigue in Advanced Cancer Patients in Palliative Care: An Application of the Multidimensional Fatigue Inventory

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1 Vol. 31 No. 6 June 2006 Journal of Pain and Symptom Management 533 Original Article Multidimensional Measurement of Fatigue in Advanced Cancer Patients in Palliative Care: An Application of the Multidimensional Fatigue Inventory Tina Noergaard Munch, MD, Annette S. Strömgren, PhD, Lise Pedersen, DrMSci, Morten A. Petersen, MSSci, Linda Hoermann, RN, and Mogens Groenvold, PhD The Research Unit (T.N.M., A.S.S., L.P., M.A.P., L.H., M.G.), Department of Palliative Medicine, Bispebjerg Hospital, Copenhagen; and Institute of Public Health (M.G.), University of Copenhagen, Copenhagen, Denmark Abstract To investigate the level, dimensionality, and correlates associated with fatigue in patients receiving specialist palliative care, 278 advanced cancer patients referred to a department of palliative medicine during a 2-year period were asked to complete the Multidimensional Fatigue Inventory (MFI-20), a self-assessment questionnaire measuring five dimensions of fatigue, and the Hospital Anxiety and Depression Scale. Of 267 eligible patients, 130 (49%) participated. Mean fatigue scores ( scale) were very high, especially for general fatigue (81), physical fatigue (87), and reduced activity (85). Only some of the MFI-20 subscales were significantly correlated. Fatigue was not correlated with sociodemographic factors. Depressed patients had higher scores on all five subscales except physical fatigue. Anxious patients had higher levels on the mental fatigue subscale only. The variation in fatigue explained by depression varied markedly (4%--31%) among subscales. Fatigue levels were very high in this population. The lack of significant correlation between some subscales indicates that they measure different aspects of fatigue. This is also supported by the differences in associations between fatigue subscales and depression and anxiety. JPain Symptom Manage 2006;31: Ó 2006 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved. Key Words Fatigue, asthenia, depression, advanced cancer, palliative care, multidimensional This research was supported by the Research Fund of Copenhagen University Hospital and by a grant from the Danish Cancer Society. Portions of this work were presented at the European Association of Palliative Care Congress, Lyon, France, May , 2002; the 2nd International Symposium of Research in Palliative Care, Montreal, Quebec, Canada, October 4--5, 2002; Ó 2006 U.S. Cancer Pain Relief Committee Published by Elsevier Inc. All rights reserved. and International Society of Quality of Life Research Congress, Orlando, FL, USA, October 31--November 3, Address reprint requests to: Tina Noergaard Munch, MD, Peter Fabers Gade 35, 2th, DK-2200 Copenhagen N, Denmark. doktormunch@hotmail.com Accepted for publication: November 1, /06/$--see front matter doi: /j.jpainsymman

2 534 Munch et al. Vol. 31 No. 6 June 2006 Introduction Cancer-related fatigue or asthenia can be described as extremely easy tiring, decreased capacity to maintain physical performance, and impaired mental functioning, such as loss of concentration and memory. Contrary to the normal physiological tiredness, it is not relieved by sufficient sleep or rest. Clinically, fatigue is perceived as a potentially treatable symptom requiring adequate diagnosis and interventions. 1 Fatigue has been reported to be one of the most prevalent and severe symptoms in several studies of cancer patients receiving palliative care In one study, fatigue was reported by 94% of the patients in a department of palliative medicine. 6 Another found that cancer patients rated fatigue as the symptom having most negative effect on quality of life. 7 Previous research suggests that fatigue is a multidimensional phenomenon, composed of physical, psychological, and possibly other aspects. 8 A better understanding of the dimensionality and etiology of fatigue may improve the basis for sufficient treatment of this impairing symptom. Cancer-related fatigue has been associated with pain, anemia, cachexia, dyspnea, autonomic dysfunction, impact of tumor degradation products, cytokine production, infection, pharmacological side effects, metabolic disorders, anxiety, depression, and a number of other factors. 1 Based on the great variation among the factors possibly associated with fatigue of both a physical and psychological nature, we approached fatigue working from a multidimensional hypothesis, believing that fatigue is best understood when both psychological and physical aspects are evaluated. The several questionnaires available for fatigue assessment conceptualize fatigue in different ways. Some are unidimensional, mainly with regard to fatigue intensity. This includes the Brief Fatigue Inventory and the Functional Assessment of Cancer Therapy-Fatigue. 9,10 Others, like the Piper Fatigue Scale and the Multidimensional Fatigue Inventory (MFI- 20), 11,12 attempt to measure different dimensions of fatigue. The MFI-20, which was used in this study, is a validated self-assessment instrument dividing fatigue into five dimensions: general fatigue, physical fatigue, reduced activity, mental fatigue, and reduced motivation. The aims of this study were 1) to investigate the level and dimensionality of fatigue in advanced cancer patients admitted to specialized palliative care; 2) to investigate the dimensionality of the MFI-20; and 3) to investigate the association between the various fatigue dimensions and demographic, psychological, and clinical factors. Thus, this study was based on the hypothesis that fatigue is multidimensional, consisting of physical and psychological components that may have different etiologies. Regarding possible associated factors, gender, age, educational level, and cohabitation were not anticipated to influence fatigue in palliative cancer patients, based on other studies that investigated these factors in cancer patients. 5,8 Interestingly, sociodemographic factors do seem to influence fatigue in general populations 13,14 and were expected to have an impact on fatigue in this study population. It was expected that inpatients would be more fatigued than outpatients and patients in the home care service because inpatients often have more pronounced symptoms. An association between cancer-related fatigue and depression has been shown in other populations of cancer patients, and was expected. 8 A study by Stromgren et al. 6 found that 47% of the patients in a department of palliative medicine were depressed. It was anticipated that depressed patients would score higher on the psychological fatigue dimensions in particular. Anxiety also was anticipated to lead to higher levels of fatigue, especially the psychological dimensions of fatigue. Anemia has been associated with fatigue and is very common in cancer patients. 15 However, data about hemoglobin levels were incomplete since blood samples are not routinely drawn from admitted patients. The use of opioids and other centrally-acting drugs in patients receiving specialized palliative care were believed to have a high impact on fatigue, which is a well-known side effect of these drugs. Further, the extensive use of opioids is a factor that separates cancer patients receiving this care from other cancer populations. Hence, it was anticipated that use of centrally-acting drugs would lead to higher levels of fatigue.

3 Vol. 31 No. 6 June 2006 Multidimensionality of Fatigue in Palliative Patients 535 Methods Patients During the period from June, 1998 to June, 2000, 278 consecutive patients were referred to the Department of Palliative Medicine, Bispebjerg Hospital, Copenhagen, Denmark for inpatient, outpatient, or home care treatment. The criterion for referral was advanced cancer for which only palliative treatment could be offered. The fact that the department has 12 beds only and serves a population of 590,000 individuals, implies that only patients with the most pronounced symptoms are admitted. Admittance to the department, Danish speaking, age $ 18 years, and informed consent were the inclusion criteria for the present project. The ethics committee approved the study. Data Collection On the first day of contact with the department, patients were informed about the study, provided that the staff found it was reasonable according to their mental status. All eligible patients were given a booklet containing the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), the Edmonton Symptom Assessment System (ESAS), the Hospital Anxiety and Depression Scale (HADS), and the MFI-20. The MFI-20 was placed in the last part. Results from the ESAS, EORTC QLQ- C30, and the HADS were published in a separate paper. Only questionnaires that were completed the same or the next day were analyzed. A participant is defined as an eligible patient who completed enough items to obtain values for at least one subscale of the MFI-20. Karnofsky Performance Status (KPS) was assessed by the doctor. Doses of analgesics were converted into morphine equivalent milligrams using defined conversion factors The patients were grouped in two ways; the first was according to the World Health Organization s (WHO) analgesic ladder: 18 Step I: nonopioid analgesics adjuvants, Step II: weak opioids nonopioid analgesics or adjuvant drugs, Step III: strong opioids nonopioid analgesics or adjuvant drugs. The second way of categorizing the use of analgesics was to make four levels of opioid consumption based on morphine equivalent milligrams per day. Instruments Smets et al. 12 developed the MFI-20 in The Netherlands. The developers wanted a self-assessment instrument for cancer patients that measured the subjectively experienced feeling of fatigue. It consists of 20 items divided into five fatigue dimensions representing general fatigue, physical fatigue, mental fatigue, reduced activity, and reduced motivation. According to the developers, general fatigue refers to the overall functioning status, expressed in a statement such as I tire easily. This fatigue dimension is meant to cover both physical and psychological aspects of fatigue. The items about physical fatigue cover the physical sensation related to fatigue. The mental fatigue scale measures cognitive functioning, such as having difficulties in concentrating. Reduced activity refers to the influence of both physical and psychological factors on the level of activity, and reduced motivation refers to the psychological experience of feeling unable to start an activity. Each subscale consists of four items, two indicative for fatigue and two contraindicative. For the indicative questions, a high score indicates a high fatigue level and for the contraindicative questions, a high score indicates low fatigue level. The responder indicates on a 1- to 5-point scale to what extent the statement applies to him or her. With the permission of the developer, we transformed the original subscales ranging into subscales ranging , where a high score indicates more fatigue. This was done because we found a scale difficult to interpret. The transformation must be taken into account when comparing our data to other studies using the MFI-20. The MFI-20 was validated by the developers 12,20 and showed good construct validity. Mean Cronbach alpha coefficient was 0.80 and the five-dimensional structure was validated by confirmatory factor analyses. The HADS was developed by Zigmond and Snaith, 21 and is a self-assessment questionnaire with two 7-item subscales measuring anxiety and depression, respectively. Each item is rated on a 4-point scale, with total scores ranging between 0 and 21 points. According to the developers, 0--7 points indicate a noncase, points indicate a doubtful or possible case, and points indicate a definite case of anxiety

4 536 Munch et al. Vol. 31 No. 6 June 2006 or depression. The HADS was created to be a screening tool for anxiety and depression among patients in nonpsychiatric hospital settings. The HADS is a widely used and well-validated instrument for measuring depression in somatic patients. 22,23 The HADS has been validated in advanced cancer patients Statistical Analysis Statistical analysis was performed using the SAS statistical package Comparing participants with nonparticipants, Fisher s exact test was used for analyses of gender differences, Pearson s c 2 test was used to compare place of service, and the log-rank test was used for comparison of survival data. The Wilcoxon rank test was used for comparison of groups according to age and KPS, and for investigating associations between mean scores of fatigue and the possible predictors for fatigue. Spearman correlations between the five dimensions of fatigue and the HADS anxiety and depression subscales, including P values, were calculated. Explained variance was found by calculating the square of the correlation coefficient. Results Response Rate and Patient Characteristics Of the 278 patients referred to the department, 11 patients were excluded, 10 because they did not speak Danish and 1 because of age less than 18 years. Of the 267 eligible patients, 130 patients completed the MFI-20 (49%). Table 1 compares demographic and clinical data of the patients who filled in the MFI-20 and those who did not. More women (59%) than men were admitted to the department but the participation rate was significantly higher among males (males 58% vs. females 42%). The patients who filled in the MFI-20 were significantly younger, survived significantly longer, and had significantly higher KPS scores than nonparticipants. Among the three places of service, the response rate was highest for outpatients and lowest for patients in palliative home care. The distribution of the 130 participants according to primary tumor was head and neck (5), gastrointestinal tract (27), respiratory system (35), breast (24), genitourinary system (23), gynecological (6), melanoma/ skin (5), hematological (1), and unknown (4). Fatigue Levels According to the MFI-20 Very high fatigue levels were seen, especially for general fatigue, physical fatigue, and reduced activity (range ) (Table 2). The levels of mental fatigue and reduced motivation were moderate (range ). Possible Predictors of Fatigue Sociodemographic Factors. No significant gender difference in fatigue levels and no Table 1 Response Rate in Relation to Sociodemographic and Clinical Factors Participants (n ¼ 130) Nonparticipants (n ¼ 137) P Sex Females 67 (42%) 91 (58%) a Males 63 (58%) 46 (42%) Age (years) Mean b Median Range Place of service Inpatient 74 (48%) 83 (52%) c Outpatient 33 (67%) 16 (33%) Palliative home care 23 (38%) 38 (62%) Survival from first contact with department (days) Mean d Median Range n ¼ 126 n ¼ 112 KPS Mean b Median Range a Fisher s exact test. b Wilcoxon test. c Pearson s c 2 test. d Log-rank test. A significant P value means that a significant difference was found between comparison groups.

5 Vol. 31 No. 6 June 2006 Multidimensionality of Fatigue in Palliative Patients 537 Table 2 MFI-20 Mean Fatigue Scores and Standard Deviations (SD) in Relation to Demographic, Psychological, and Clinical Predictors General Fatigue Physical Fatigue Mental Fatigue Reduced Activity Reduced Motivation Mean (SD) P Mean (SD) P Mean (SD) P Mean (SD) P Mean (SD) P All patients n ¼ (19) 87 (18) 53 (30) 85 (18) 52 (26) Gender Female, n ¼ (17) (16) (32) (19) (27) 0.88 Male, n ¼ (21) 87 (19) 57 (27) 84 (17) 52 (26) Age , n ¼ (26) (24) (279) (26) (26) , n ¼ (18) 91 (14) 52 (33) 87 (15) 50 (25) , n ¼ (17) 85 (19) 63 (27) 82 (16) 52 (25) , n ¼ (19) 87 (15) 51 (28) 89 (13) 63 (27) 80--, n ¼ (12) 88 (20) 43 (36) 43 (36) 51 (27) Education #1 year n ¼ (19) (15) (30) (15) (26) 0.21 >1 year 84 (14) 90 (16) 52 (31) 85 (19) 51 (26) and #3 years n ¼ 59 >3 years n ¼ (24) 86 (17) 51 (829) 83 (17) 48 (24) Cohabitation Cohabiting, n ¼ (21) (20) (30) (21) (28) 0.60 Living alone, n ¼ (18) 89 (15) 55 (29) 86 (16) 52 (26) Place of service Inpatients, n ¼ (17) (14) (30) (15) (26) 0.33 Outpatients, n ¼ (21) 85 (22) 51 (27) 81 (21) 47 (27) Home care, n ¼ (22) 84 (21) 47 (33) 81 (22) 51 (27) HADS Depression subscale Negative ¼ 0--7, n ¼ (22) < (21) (25) < (22) (23) < Possible ¼ 8--10, n ¼ (14) 92 (11) 47 (24) 86 (16) 49 (20) Positive ¼ , n ¼ (13) 89 (16) 65 (32) 90 (14) 67 (22) HADS Anxiety subscale Negative ¼ 0--7, n ¼ (22) (19) (30) < (20) (28) 0.48 Possible ¼ 8--10, n ¼ (17) 90 (17) 48 (27) 82 (19) 51 (25) Positive ¼ , n ¼ (13) 85 (16) 74 (25) 85 (15) 57 (25) Analgesics None, n ¼ (29) (28) (25) (34) (24) 0.86 WHO Step I, n ¼ 6 74 (14) 70 (17) 40 (35) 74 (17) 44 (30) WHO Step II, n ¼ 8 84 (18) 96 (9) 51 (29) 84 (16) 52 (15) WHO Step III, n ¼ (19) 88 (17) 54 (30) 85 (26) 53 (17) Morphine doses (mg parenteral/24 hours) No morphine, n ¼ (20) (21) (28) (21) (27) , n ¼ (17) 87 (19) 51 (30) 86 (19) 57 (23) , n ¼ (19) 90 (14) 60 (29) 85 (15) 47 (29) >150, n ¼ (20) 86 (33) 52 (33) 85 (18) 55 (26) Antidepressants No, n ¼ (19) (18) (29) (19) (25) 0.26 Yes, n ¼ (19) 88 (16) 61 (30) 82 (16) 48 (29) For calculating the P-values, the Wilcoxon test was used. MFI-20 scores were transformed from the original scales to scales. A significant P-value means that a difference is found between comparison groups. evidence of increasing fatigue with age were seen. Neither cohabitation nor the level of education was associated with the levels of fatigue (Table 2). Depression and Anxiety. Sixty-three patients (48%) were classified as positively depressed (HADS score $ 11). These patients scored significantly higher than patients classified as nondepressed (HADS score # 7) on four of the five fatigue scales (Table 2). The subscale with the highest mean score, physical fatigue, was not significantly associated with depression (P ¼ 0.057). Thirty-five patients (27%) scored

6 538 Munch et al. Vol. 31 No. 6 June 2006 positive for anxiety on the HADS anxiety subscale. These patients scored significantly higher on mental fatigue (P < ). Fatigue and Medication. A significant association between use of analgesics and physical fatigue was found, as categorized according to the WHO analgesic ladder. However, this was a nonmonotonic relationship, making interpretation difficult. No association was seen when the use of analgesics was classified after dose per day. Significant associations were seen between the use of antidepressants and general as well as mental fatigue: the patients treated with antidepressants were less generally fatigued but more mentally fatigued. Correlations Among MFI-20 Subscales General fatigue was significantly correlated with the four other subscales (Table 3). Physical fatigue correlated significantly with reduced activity but not with the psychological subscales. The other physical subscale, reduced activity, was significantly associated with the mental subscale, reduced motivation, but not with mental fatigue. Finally, the two psychological subscales, mental fatigue and reduced motivation, were significantly associated with each other. The strongest correlations (range ) were between general fatigue and physical fatigue, reduced activity, and reduced motivation, respectively, and between physical fatigue and reduced activity. Correlations with HADS Subscales All five subscales were significantly associated with the HADS depression subscale, with correlations ranging from 0.20 for physical fatigue to 0.56 for reduced motivation. There were considerable differences in the variation in each subscale explained by depression: general fatigue 27%, physical fatigue 4%, mental fatigue 19%, reduced activity 9%, and reduced motivation 31%. Only general fatigue and mental fatigue were significantly correlated with the HADS anxiety subscale. The variance explained by anxiety was 5% for general fatigue and 19% for mental fatigue. Discussion Participation A common but unavoidable problem of doing research based on self-assessment questionnaires in a palliative care setting is the selection bias due to unattainable data from the patients with the most pronounced symptomatology. Table 1 shows the differences between participants and nonparticipants. The impact of this selection bias is likely to be an underestimation of the true fatigue levels. We have no reason to believe that the associations between fatigue and the other variables are strongly affected by this selection bias. The Level of Fatigue The very high fatigue levels observed in Danish patients receiving specialized palliative care are in accordance with the advanced disease stage, short survival, and the pronounced symptom load seen in these patients. 6 Even though the scores on the subscales cannot be directly compared, it seems clear that the scores for general fatigue and the physical dimensions are higher than the psychological scores. To put these levels in perspective, the mean MFI scores for the Danish general population were general fatigue 35, physical fatigue 33, mental fatigue 24, reduced activity 26, and reduced motivation Table 3 Comparison of Correlations Among Subscales of the MFI and the HADS Physical Fatigue Mental Fatigue Reduced Activity Reduced Motivation Anxiety (HADS) Depression (HADS) General fatigue 0.48 (<0.0001) 0.27 (0.0025) 0.45 (<0.0001) 0.43 (<0.0001) 0.23 (0.011) 0.52 (<0.0001) Physical fatigue (0.89) a 0.41 (<0.0001) 0.16 (0.064) a 0.17 (0.064) a 0.20 (0.021) Mental fatigue (0.85) a 0.24 (0.0073) 0.41 (<0.0001) 0.43 (<0.0001) Reduced activity 0.35 (<0.0001) (0.32) a 0.29 (0.0008) Reduced motivation 0.15 (0.087) a 0.56 (<0.0001) Anxiety (HADS) 0.33 (0.0002) a The two subscale scores are not significantly correlated (P > 0.05).

7 Vol. 31 No. 6 June 2006 Multidimensionality of Fatigue in Palliative Patients 539 Predictors of Fatigue Sociodemographic Factors. In the Danish and Norwegian general populations, sociodemographic factors have been found to be associated with fatigue; 13,14 women were found to be more tired than men, fatigue was found to increase with age, people of lower social class reported more fatigue, and singles reported more fatigue than cohabiting people. However, such associations were not found in advanced cancer patients. The lack of association with demographic factors such as gender, age, educational level, and cohabitation in our study is consistent with other studies of cancerrelated fatigue. 5,8 Depression and Anxiety. Several studies of cancer patients in earlier stages of disease have found depression and anxiety associated with fatigue. 20,27,28 In contrast, Stone et al. 29 did not find such association between fatigue assessed by the Fatigue Severity Scale (FSS) and depression measured with the HADS, which is remarkable since this study population matches ours very well. The FSS does not discriminate between different dimensions of fatigue, and possibly the pronounced physical fatigue seen in advanced cancer patients may hide an association with depression on a unidimensional rating scale. Patients classified positive for anxiety are clearly more mentally fatigued than patients classified negative for anxiety. Fatigue in anxious patients may be improved by anxiolytic treatment, according to a study by Tchekmedyian et al. 30 Fatigue and Medication. A nonmonotonic association between physical fatigue and the use of analgesics when classified according to the WHO analgesic ladder was seen, but given the small number of patients not treated with analgesics and the lack of a similar tendency when using the dose-per-day classification, this may be a spurious finding. An association with centrally-acting drugs was anticipated, especially in this group of patients, but not found. This could mean two things: the physicians appropriately adjusted the doses of the centrally-acting drugs to relieve pain and other symptoms without sedating the patients or that the nature of fatigue among cancer patients in palliative care is more likely to originate from other causes. The significant correlation with general fatigue suggests that antidepressants may reduce the overall feeling of fatigue. Regarding the expectation that using antidepressants should cause more mental fatigue, this was marginally significant and is most likely to be a random finding. Tchekmedyian et al. 30 suggested that treating fatigue might improve depression as well. On the other hand, patients given antidepressants are likely to be depressed, and as described above, depression was associated with scores on both of these scales. This illustrates that associations in nonrandomized cross-sectional studies should not be overinterpreted. We, therefore, emphasize the fact that effects of opioids and antidepressants on fatigue certainly cannot be excluded based on this study. The Dimensionality of Fatigue Even though the scores on the MFI-20 subscales cannot be directly compared, it seems clear that the scores for general fatigue and the physical dimensions are higher than the psychological scores. These findings provide support for the assumption that fatigue consists of more than one dimension. At a minimum, fatigue in advanced cancer patients can be divided into physical and psychological fatigue. To determine whether all five different dimensions of the MFI exist as viable constructs needs further investigation; it may be questionable how many dimensions are relevant to assess from a clinical perspective. It seems likely that future research will show that it is advantageous to characterize patients with respect to the nature of their fatigue with a multidimensional instrument when planning treatment of individual patients and in clinical trials having fatigue as an endpoint. Correlations with HADS Subscales Does the MFI-20 add anything to a unidimensional assessment of fatigue combined with measurement of depression? The results confirm that the psychological MFI-20 subscales are indeed correlated with depression, but correlations were seen with all fatigue subscales. Pronounced differences were seen in the variation in each subscale explained by depression: general fatigue 27%, physical fatigue

8 540 Munch et al. Vol. 31 No. 6 June %, mental fatigue 19%, reduced activity 9%, and reduced motivation 31%. This shows that the information gained from a multidimensional assessment of fatigue is different from that obtained with a fatigue scale and a depression scale only. As discussed above, additional research is needed to find out whether patients benefit from different treatment strategies depending on the nature of their fatigue. Even without considering multidimensionality, the etiology of fatigue in advanced cancer is very complex. There are a large number of diverse possible predictors, which may be interrelated. For example, Stone et al. 29 found that fatigue was associated with pain and dyspnea in a multivariate analysis including multiple clinical, physiological, and psychological factors. A recently published study in patients with advanced lung cancer suggests that the systemic inflammatory response is correlated with fatigue, as well as other physical and psychological factors. On the multivariate regression analysis, KPS, weakness, and HAD scores were correlated with fatigue. 31 Taking multidimensionality into account may at first be seen as making etiologic studies even more complex, but it may, on the other hand, make relationships more readably understandable. Further validation of the MFI-20 in advanced cancer patients is needed. This study suggests that the MFI-20 could indeed be a useful tool for further investigation of the etiology of fatigue, for evaluation of treatment of fatigue, and as a diagnostic tool in clinical work. References 1. Neuenschwander H, Asthenia Bruera E. In: Doyle D, Hanks G, Macdonald N, eds. Oxford textbook of palliative medicine, 2nd ed. Oxford: Oxford University Press, 1998: Stone P, Hardy J, Broadley K, et al. Fatigue in advanced cancer: a prospective controlled cross-sectional study. Br J Cancer 1999;79: Donnelly S, Walsh D. The symptoms of advanced cancer. Semin Oncol 1995;22: Ng K, von Gunten CF. Symptoms and attitudes of 100 consecutive patients admitted to an acute hospice/palliative care unit. J Pain Symptom Manage 1998;16: Jordhoy MS, Fayers P, Loge JH, et al. Quality of life in advanced cancer patients: the impact of sociodemographic and medical characteristics. Br J Cancer 2001;85: Stromgren AS, Goldschmidt D, Groenvold M, et al. Self-assessment in cancer patients referred to palliative care: a study of feasibility and symptom epidemiology. Cancer 2002;94: 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: Servaes P, Verhagen C, Bleijenberg G. Fatigue in cancer patients during and after treatment: prevalence, correlates and interventions. Eur J Cancer 2002;38: Mendoza TR, Wang XS, Cleeland CS, et al. The rapid assessment of fatigue severity in cancer patients: use of the Brief Fatigue Inventory. Cancer 1999;85: Yellen SB, Cella DF, Webster K, et al. Measuring fatigue and other anemia-related symptoms with the Functional Assessment of Cancer Therapy (FACT) measurement system. J Pain Symptom Manage 1997;13: Piper BF, Dibble SL, Dodd MJ, et al. The revised Piper Fatigue Scale: psychometric evaluation in women with breast cancer. Oncol Nurs Forum 1998;25: 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: Watt T, Groenvold M, Bjorner JB, et al. Fatigue in the Danish general population. Influence of sociodemographic factors and disease. J Epidemiol Community Health 2000;54(11): [Erratum in: J Epidemiol Community Health 2001 Mar; 55(3):216]. 14. Loge JH, Ekeberg O, Kaasa S. Fatigue in the general Norwegian population: normative data and associations. J Psychosom Res 1998;45: Glaspy J. Anemia and fatigue in cancer patients. Cancer 2001;92: Clausen TG, Eriksen J, Borgbjerg FM. Legal opioid consumption in Denmark Eur J Clin Pharmacol 1995;48: Coda BA, O Sullivan B, Donaldson G, et al. Comparative efficacy of patient-controlled administration of morphine, hydromorphone, or sufentanil for the treatment of oral mucositis pain following bone marrow transplantation. Pain 1997;72: Hanks G, Cherny N. Opioid analgesic therapy. In: Doyle D, Hanks G, Macdonald N, eds. Oxford textbook of palliative medicine, 2nd ed. Oxford: Oxford University Press, 1998: Pereira J, Lawlor P, Vigano A, et al. Equianalgesic dose ratios for opioids. A critical review and proposals for long-term dosing. J Pain Symptom Manage 2001;22:

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