Validation Study of the Japanese Version of the Brief Fatigue Inventory

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1 106 Journal of Pain and Symptom Management Vol. 25 No. 2 February 2003 Original Article Validation Study of the Japanese Version of the Brief Fatigue Inventory Toru Okuyama, MD, PhD, Xin Shelley Wang, MD, Tatsuo Akechi, MD, PhD, Tito R. Mendoza, PhD, Takashi Hosaka, MD, PhD, Charles S. Cleeland, PhD, and Yosuke Uchitomi, MD, PhD Pain Research Group (T.O., X.S.W., T.R.M., C.S.C.), Division of Anesthesiology and Critical Care, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA; Psycho-Oncology Division (T.O., T.A., Y.U.), National Cancer Center Research Institute East, Chiba; Department of Psychiatry and Behavioral Science (T.O., T.H.), Tokai University School of Medicine, Kanagawa; and Psychiatry Division (T.A.), National Cancer Center Hospital East, Chiba, Japan Abstract Fatigue has been recognized as one of the most distressing symptoms in cancer patients. Concise assessment is essential to managing this symptom. To that end, the Brief Fatigue Inventory (BFI), a 9-item questionnaire, was designed to assess fatigue in cancer patients. The purpose of this study was to examine the validity and reliability of the Japanese version of this scale (BFI-J), when compared with previously validated fatigue instruments. We randomly selected 252 cancer patients and presented them with the BFI-J, along with the Cancer Fatigue Scale; Profile of Mood States fatigue, vigor, and depression subscales; and European Organization for Research and Treatment of Cancer QLQ-C30. Specifically, the reliability and construct, criterion, convergent, and discriminant validity of each instrument were evaluated. Additionally, fatigue severity classification was explored using the BFI-J. The results indicated that the BFI-J is a brief, valid, and feasible measure of fatigue for use with Japanese cancer patients. J Pain Symptom Manage 2003;25: U.S. Cancer Pain Relief Committee. Published by Elsevier. All rights reserved. Key Words Cancer, fatigue, assessment, scale, validation, symptom, palliative care, Japan, quality of life Address reprint requests to: Yosuke Uchitomi, MD, PhD, Psycho-Oncology Division, National Cancer Center Research Institute East, 6-5-1, Kashiwanoha, Kashiwa, Chiba , Japan. Accepted for publication: March 20, Introduction Fatigue is one of the most common and deleterious symptoms found in cancer patients. The prevalence rate of fatigue has been reported to be over 50% in patients having advanced cancer 1,2 and over 30% in newly diagnosed cancer patients 3 and cancer survivors. 4 In our previous studies, we reported a prevalence rate of fatigue of 82% and 56% in Japanese advanced lung cancer 5 and disease-free breast cancer patients, respectively. 6 It is also known that patients who undergo anticancer treatment modalities such as chemotherapy, radiotherapy, and bone marrow transplantation often experience fatigue as a significant treatment side effect Furthermore, it has been recognized that fatigue frequently and significantly interferes with cancer patients 2003 U.S. Cancer Pain Relief Committee /03/$ see front matter Published by Elsevier. All rights reserved. PII S (02)

2 Vol. 25 No. 2 February 2003 Validation of the Japanese Version of the BFI 107 quality of life Despite its high prevalence and impact, systematic treatment strategies designed to ameliorate fatigue have not been established. 14 One of the reasons for this is that the etiology of cancer-related fatigue has not been fully understood due to the complexity of the factors involved in its development. Specifically, both physical and psychological factors are thought to be associated with fatigue. 5 Although the physiological mechanism of fatigue is also unknown, it has been recognized that a low hemoglobin level is associated with severe fatigue. 15 Moreover, a large intervention study showed that fatigue was reduced in patients whose hemoglobin level was improved due to treatment. 16 An association between fatigue and albumin level also has been reported, 17 but is still controversial. Because fatigue is often underassessed and undertreated, concise assessment is the key to better management of this symptom. Like pain, fatigue is a subjective symptom; thus, patient self-reports should be the basis of assessment. Furthermore, self-rating scales have enabled physicians to assess patient symptoms without introducing observer bias. Some selfrating fatigue scales have been developed in English-speaking countries, such as the Multidimensional Fatigue Inventory (MFI), 18 Functional Assessment of Cancer Therapy-Fatigue, 19 Schwarz Cancer Fatigue Scale, 20 Fatigue Symptom Inventory, 21 and Piper Fatigue Scale. 22 The main characteristic of these recently developed scales is their multidimensionality. For example, the MFI consists of 5 subscales: general fatigue, physical fatigue, reduced activity, reduced motivation, and mental fatigue. These subscales enable one to assess various aspects of fatigue and are particularly meaningful in the descriptive study on fatigue. However, multidimensional scales are often too long for exhausted patients to complete. Also, the use of colloquial and descriptive expressions in these scales increases the level of difficulty in the translation process. The Cancer Fatigue Scale (CFS), which we developed and validated, is the only fatigue assessment scale originally developed in Japan. 23 This scale is easy to administer, having 15 items, and is specifically designed to reflect the nature of cancer-related fatigue via factor analysis. It consists of 3 subscales (for the physical, affective, and cognitive aspects of fatigue) and enables one to assess fatigue from multidimensional aspects. This scale does include colloquial expressions, however. The Brief Fatigue Inventory (BFI) is a questionnaire originally developed in English and designed to assess fatigue in cancer patients. 24 It consists of 9 numerical scales of 0 to 10: 3 items that measure severity and 6 items that measure interference with daily activities. The three important characteristics of this scale are 1) it is brief and easy for patients to complete, 2) it is easily translated into other languages, and 3) it includes interference items. In general, the terms used to describe fatigue are often colloquial and difficult to translate. However, instead of asking patients to use such terms, the BFI assesses fatigue intensity and interference with daily activities using simple wording. Also, the 0 10 numerical scale was adopted to avoid the use of a rating system based on verbal descriptors, which are also difficult to translate. One of the challenges in measuring fatigue in cancer patients is developing an international standardized method of fatigue assessment. Although there are many kinds of fatigue assessment instruments currently available in English-speaking countries, there are no global standards. Such a standard would be beneficial in facilitating comparisons of results with those of other studies and trials, sharing knowledge of fatigue in cancer patients globally, and conducting international studies that consider the cultural and regional differences of this symptom. On the other hand, clarification of the differences in the characteristics and comparison of the performance of various existing fatigue instruments is also important. To our knowledge, there has been only a study that reported this issue. In it, Meek et al. 25 investigated and compared the psychometric properties of the Profile of Mood States (POMS) Short Form fatigue subscale, Multidimensional Assessment of Fatigue, Lee Fatigue Scale, and MFI, and provided clues about how to adequately select assessment instruments. Another challenge is distinguishing patients having severe fatigue from those having moderate or mild fatigue. We examined the meaning of different symptom levels by defining them in terms of how much the symptom interferes with a patient s daily activities. 24 In the original BFI development study conducted in

3 108 Okuyama et al. Vol. 25 No. 2 February 2003 the United States, we found that, on a 0 10 numerical scale, level 1 3 fatigue is mild, level 4 6 fatigue is moderate, and level 7 10 fatigue is severe. 24 We took a similar approach using CFS, finding that a score of 18 or above indicates clinical fatigue, which is defined as fatigue that interferes somewhat with patient s daily activities. 5 Other investigators have defined severe fatigue as a score at or above the 95th percentile on the Fatigue Severity Scale. 26 In the present study, we examined the reliability and validity of the Japanese version of the BFI (BFI-J) among ambulatory cancer patients in Japan. The previously validated CFS, POMS fatigue and vigor subscales, and European Organization for Research and Treatment of Cancer (EORTC) QLQ-C 30 fatigue subscale, all of which have been frequently used in the cancer patients population, were used for comparative fatigue measurement in this study. As was done in the original BFI study, we sought to categorize fatigue severity as assessed using the BFI-J and CFS as mild, moderate, or severe. We also examined the possibility of translating and comparing the BFI-J and CFS with each other to enhance their application. Finally, we clarified the severity of and interference with daily activities due to fatigue in the study patients using the study s data set. Methods Patients and Data Collection The subjects of this study were cancer patients receiving treatment at the outpatient clinics of the National Cancer Center Hospital East, Japan. To be eligible, the patients 1) had to have a pathological diagnosis of cancer, 2) must have been informed of their cancer diagnosis, 3) had to be able to understand and complete the questionnaires, and 4) could not to be suffering from severe mental or cognitive disorders. The study was approved by the Institutional Review Board of the National Cancer Center in Japan and The University of Texas M.D. Anderson Cancer Center. Each patient gave written consent after being fully informed of the study. Randomly selected outpatients who met the eligibility criteria were asked to participate in the study; randomization was conducted using a planned visiting list. After their informed consent was obtained, the patients were asked to complete self-administered questionnaires following brief instruction at home on the day of the hospital visit and then mail them back by the following day. If there were any blanks in the returned questionnaires, telephone inquiries were made to obtain the missing answers. Measures Brief Fatigue Inventory (BFI). The BFI, which was developed by Cleeland et al., 24 consists of 9 items using a numerical scale of 0 to 10 on a single page. The first 3 items ask patients to describe their fatigue now, at its usual level, and at its worst level during the previous 24 hours, using the anchor points no fatigue and fatigue as bad as you can imagine. The next 6 items ask patients to describe how much fatigue has interfered with different aspects of their life during the previous 24 hours. Specifically, these items are general activity, mood, walking ability, normal work (both work outside the home and daily chores), relations with other people, and enjoyment of life, with 0 being does not interfere and 10 being completely interferes. The global score for the BFI is calculated as the mean value of these 9 items. The validity and reliability of the original scale has been established. 24 To develop the BFI-J, the forward-backward translation method was used. In the translation process, the items were first translated into Japanese by a translator whose native language was Japanese and then back-translated into English by a second translator whose native language was English, and who had not seen the original English version. Bilingual fluency was required of both translators to complete the translation. Next the English back-translated items were compared with the originals. If a back-translated item did not agree with the original, the first translator performed a second translation and the second translator performed second back-translation. This process was repeated until agreement was reached. Cancer Fatigue Scale (CFS). The CFS is a 15-item self-rating scale used for assessing fatigue in cancer patients that was originally developed in Japan. 23 This scale consists of 3 subscales: physical, affective, and cognitive aspects of fatigue and assesses the multidimensional nature

4 Vol. 25 No. 2 February 2003 Validation of the Japanese Version of the BFI 109 of fatigue. Each item is rated on a scale of 1 (not at all) to 5 (very much). Patients are asked to circle the number for each item that best describes their current state. The possible response range for each subscale score is 0 to 28 for the physical subscale, and 0 to 16 for both the affective and cognitive subscale (the scores are adjusted for 0 as a state of no fatigue). Thus, total fatigue is calculated as the sum of these subscale scores, with the maximum total score being 60, the higher the total scores, the more severe the fatigue. The reliability and validity of this scale were well established in a series of studies in cancer patients. 5,6,23 Profile of Mood States (POMS). The original version of the POMS is a 65-item adjective checklist (including 7 dummy items) that measure six emotional states (tension-anxiety, depression-dejection, anger-hostility, vigor, fatigue, and confusion) and total mood disturbance. 27 In particular, the fatigue and vigor subscales have been used to assess fatigue in cancer patients. These subscales consist of 7 and 8 items, respectively, and each item is rated using the 5-point Likert scale (0 [not at all] to 4 [very much]), with higher scores indicating a more fatigue and vigor, respectively. We also used a depression subscale to assess the patients depression in this study. The reliability and validity of the Japanese version of the POMS have been established. 28 European Organization for Research and Treatment of Cancer QLQ-C 30 (version 3.0). The EORTC QLQ-C 30 is one of the most frequently used self-rating questionnaires in assessing patients quality of life. 29 It has 30 items and consists of 5 multi-item function subscales plus global health status/quality of life, (physical, role, emotional, cognitive, and social function), 4 multi-item symptom scales (fatigue, pain, nausea, and vomiting), and 6 separate items to assess symptoms (dyspnea, sleep disturbance, appetite loss, diarrhea, and constipation) and financial impact. Specifically, we used the fatigue subscale in our analysis, which consisted of the items need to rest, weakness, and tired using a 4-point Likert scale. The Japanese version of the EORTC QLQ-C 30 has been established. 30 Questionnaire for Sociodemographic Information. The patient s education level, job status, and marital status were obtained using an ad hoc questionnaire. Clinical Data Checklist. The patients medical information was obtained from their medical records using a specific checklist, which included disease information (cancer site and stage, presence of metastatic lesions, nutritional status), treatment status (including history of cancer treatment), prescribed medication, and laboratory data. The laboratory data results included the hemoglobin and albumin level, if they were obtained within a week of assessment. Additionally, their performance status, as defined by the Eastern Cooperative Oncology Group (ECOG), was clinically evaluated on the same day as assessment by attending oncologists. Statistical Analysis The reliability and validity of each fatigue assessment instrument was evaluated as follows. The reliability was evaluated by calculating the Cronbach s alpha coefficient, which is a measure of the internal consistency of responses. This coefficient ranges from 0 to 1, with higher values indicating good reliability. Construct validity was evaluated based on the factor analysis that reproduced the same factor loading pattern seen in the original scale, and the fit of the factor model was evaluated based on the results of the scree test, interpretability, and examination of the residuals. Concurrent validity was evaluated by calculating the interinstrument Pearson s correlation coefficient. Also, convergent validity was evaluated by calculating Pearson s correlation coefficient between the fatigue instruments and the EORTC QLQ-C30 global quality of life score, POMS depression subscale, the association of which with fatigue was previously reported (as described in the Introduction). We also investigated the association between fatigue scale scores and laboratory data (hemoglobin and albumin). Partial correlation coefficients were calculated to investigate this association for adjusting the results according to sex and age. Finally discriminant validity was examined by comparing the BFI-J and other fatigue scale scores in patients having different ECOG performance statuses; it was hypothesized that patients having poor performance status have an increased level of fatigue severity.

5 110 Okuyama et al. Vol. 25 No. 2 February 2003 We also examined the possibility of classifying fatigue as mild, moderate, or severe based on the fatigue item worst, in the original BFI. This classification was originally developed in pain research and has proven useful in many clinical applications The cut-off point between 6 and 7 on the numerical scale was used to distinguish between moderate and severe fatigue, while that between 3 and 4 showed a weak difference between mild and moderate in the original BFI. Additionally, we tested the classification was tested using multivariate analysis of variance (MANOVA). The ideal cut-off points between each severity group should yield greater discrepancy between each interference item score on the BFI-J, as it is assumed that the person having severe fatigue has significantly more fatigue interference than does a person having milder fatigue. Thus, MANOVA was used to investigate this discrepancy. The dependent variables were the 6 interference items in the BFI-J, and the between-groups factor was 3. Four boundary models (3/4 6/7, 3/4 7/8, 4/5 6/7, and 4/5 7/8 for the mild/moderate moderate/severe cut points, respectively) examined in the original BFI study were tested. Pillai s trace (or Pillai-Bartlett trace), Wilk s lambda, and Hotelling s trace between the models were compared. Wilk s lambda is one of the most widely used criteria, and both the Pillai s trace and Hotelling s trace are alternative criteria that are functions of the eigen values. Smaller Wilk s lambda values and larger Pillai and Hotelling values lead to rejection of the null hypothesis. Bivariate regression analysis was conducted to examine the relationship between the BFI and CFS. To control Type I error rates, the level of significance in involving unpaired t-tests, bivariate correlations, and partial correlations was determined by dividing the significance level (.05) by the number of tests performed. For example, the significance level in demonstrating criterion validity was because there were 19 tests conducted. Similarly the significance level for discriminant validity was 0.01 (5 tests), and that for both convergent validity and laboratory data analyses was (each 14 tests). All of the P values reported are 2-tailed. All statistical procedures were performed using the SPSS statistical software program for Windows (version 10.0, SPSS Inc., Chicago, IL). Results Patient Characteristics Patient samplings was conducted in the outpatient clinics of 6 oncology divisions of the National Cancer Center Hospital East, Japan: the Palliative Care Unit, Thoracic Oncology, Gastrointestinal Oncology, Head and Neck Oncology, Hepatobiliary and Pancreatic Oncology, and Chemotherapeutic Oncology. As a result, pool of 282 potential outpatients was identified for this study. Thirty of these patients were excluded: 8 for refusal to participate, 8 for cognitive disturbance, 7 for excessive illness, and 5 for other reasons. Two patients were enrolled but not able to complete the questionnaires. The sociodemographic and clinical characteristics of the remaining 252 patients are shown in Table 1. Eighteen percent (18%) of the patients had a poor functional status (performance status of 2 or more). Additionally, according to the results of the worst fatigue item on the BFI-J, 82% of the patients experienced some degree of fatigue. Utility: Rate of Missing Data We found that 15 responses to the first question of the BFI-J, which asked whether patient had unusual fatigue in the last week, were missing. There was a total of 14 missing responses for the other 9 questions combined. Thus, only 0.6% of the total data points (252 patients answering 9 items) was missing. The missing data rates for other fatigue instruments are shown in Table 2. The CFS had the lowest rates at 0.1%; all of the other instruments had a rate of below 1.0%. Reliability The Cronbach s alpha coefficient for the BFI-J was 0.96, which was the highest among the fatigue instruments used in the study. The other fatigue scales also showed good reliability, having a Cronbach s alpha coefficient at about or above Construct Validity The results of the scree test for the BFI-J suggested a 1-factor solution. The eigenvalue was 6.80 for this first factor, followed by 0.78 and 0.46 for the second and third factor, respectively. Also, the first factor explained 76% of the variability in the data. The eigenvalues and

6 Vol. 25 No. 2 February 2003 Validation of the Japanese Version of the BFI 111 Table 1 Demographic and Clinical Characteristics of the Study Patients (n 252) Characteristic n % Mean age SD, years (median) (65) Sex, Female Education level, Junior high school or less Marital status, Married Job status, Full/part time Cancer site Gastrointestinal Lung Hepatobiliary and pancreas Hematological Head and neck Breast Others Clinical stage, Recurrence Metastasis, Present ECOG performance status History of anti-cancer treatment within a month Surgery 5 2 Chemotherapy Radiotherapy 5 2 amount of explained variability indicate that most of the data can be explained by a single construct, which is consistent with the original BFI. Furthermore, the results of the factor analysis for other instruments are summarized in Table 3. Notably the factor analysis for the CFS revealed the 3-factor solution, which is consistent with previous analyses. 5,6,23 Additionally, the factor analysis for the POMS was conducted separately for both of its subscales, revealing a 1-factor solution for the fatigue subscale and the vigor subscale. Finally, for the EORTC QLQ-C30 scale, we first conducted the factor analysis for all 30 items, revealing 6 factors. Two of the 3 fatigue items need to rest and weak loaded on the first factor, which consisted mainly of items assessing physical symptoms or their interference. Another item, tired loaded evenly on both the first and second factor, the latter of which consisted mainly of items assessing psychological and cognitive symptoms. We found a 1-factor solution when we conducted the factor analysis for only 3 fatigue items. Criterion Validity The criterion validity of the BFI-J was demonstrated by calculating the correlations between the BFI-J scores and other fatigue instrument scores (CFS, POMS fatigue and vigor subscales, and EORTC QLQ-C 30 fatigue subscale; Table 4). The usual item, worst item, Fatigue Instrument Table 2 Descriptive Data and Reliability of the BFI-J and Other Fatigue Instruments (n 252) Number of Items Time Frame Range of Possible Scores Mean Standard Deviation Cronbach s Alpha Coefficient Missing Data Rates (%) a BFI 9 24 hours CFS 15 current POMS fatigue subscale 7 1 week POMS vigor subscale 8 1 week EORTC QLQ-C 30 fatigue subscale 3 1 week a (Number of missing data points total data points) 100.

7 112 Okuyama et al. Vol. 25 No. 2 February 2003 Table 3 Construct Validity Examined via Factor Analysis (n 252) Fatigue Instrument Number of Factors Expected Number of Factors Obtained Total Variance (%) BFI CFS POMS fatigue subscale POMS vigor subscale EORTC QLQ-C 30 fatigue subscale and global score for the BFI-J were significantly correlated with those for the other fatigue instruments. Particularly, correlations in the effect sizes were found between the BFI global score and both the CFS and POMS Fatigue subscale, which were quite large (correlation coefficients of 0.7 or higher). Of the three BFI scores listed above, the global score consistently had the highest correlation coefficients with other fatigue instruments. The correlations between the other fatigue instruments were found to be significant, and the effect sizes were large enough (correlation coefficients of 0.60 or higher). However, the effect size between the POMS vigor subscale and the other instruments were small or moderate (correlation coefficient of ). Convergent Validity Correlation coefficients between the fatigue instruments and quality of life, depression level are shown in Table 4. Among the BFI-J scores, the global score again had higher correlation coefficients with these indices than did the BFI usual and worst fatigue items. The POMS fatigue subscale had the highest correlation coefficient with the POMS depression subscale. The effect sizes of POMS vigor subscale with these indices were relatively small, when compared with those of the other fatigue scales. Discriminant Validity To have discriminant validity, an assessment instrument should be able to distinguish between the fatigue levels of those having a poor and good performance status. In the present study, patients having a poor performance status (a score of 2 or higher on the ECOG scale) had significantly higher BFI scores than did those having a good status. The mean (standard deviation) BFI worst score was 5.0 (3.0) and 3.2 (2.6) for patients in the poor and good performance status groups, respectively (95% CI: 0.93, 2.65, P 0.001). The scores of all of other fatigue instruments were also significantly different between the two groups (CFS: 28.2 (11.3) and 20.0 (9.7) (95% CI: 4.95, 11.38, P 0.001), POMS fatigue subscale: 12.3 (6.7) and 8.1 (6.1) (95% CI: 2.22, 6.21, P 0.001), EORTC QLQ-C 30 fatigue subscale: 57.3 (22.6) Table 4 Criterion Validity According to Intercorrelation Between Fatigue Instruments and Convergent Validity According to Correlation Between Fatigue Instruments and Other Indices (n 252) Correlation Coefficient Between Fatigue Instruments Correlation Coefficient with Other Indices POMS Laboratory Data POMS (n 132) EORTC EORTC Depression Fatigue Instrument BFI (usual) CFS Fatigue Vigor Fatigue Global QOL Subscale Albumin Hemoglobin BFI (worst) 0.90* 0.64* 0.60* 0.23* 0.59* 0.40* 0.35* 0.32* 0.21 BFI (usual) 0.68* 0.64* 0.23* 0.61* 0.42* 0.43* 0.28* 0.25 BFI (global score) 0.76* 0.70* 0.28* 0.72* 0.51* * 0.27* CFS 0.77* 0.42* 0.78* 0.52* 0.58* 0.34* 0.20 POMS fatigue subscale 0.38* 0.74* 0.51* 0.72* 0.37* 0.17 POMS vigor subscale 0.38* 0.46* 0.27* * EORTC QLQ-C 30 fatigue subscale 0.54* 0.53* 0.32* 0.24 a Partial correlation coefficients with laboratory data adjusted by sex and age. QOL quality of life. *Significant correlation.

8 Vol. 25 No. 2 February 2003 Validation of the Japanese Version of the BFI 113 Table 5 F Statistics for Fatigue Severity Categorization Based on Various Test Criteria in MANOVA (n 205) Possible Boundaries Model Mild Moderate Severe Pillai s Trace Wilk s Lambda Hotelling s Trace n n n n and 39.4(22.9) (95% CI: 10.55, P 0.001)), except POMS vigor subscale: 9.4 (6.3) and 11.8 (5.8) (95% CI: 4.31, 0.54, P 0.012), for patients in the poor and good performance status groups, respectively. Categorizing Fatigue Severity Using the BFI-J Worst Item Table 5 shows the results of MANOVA. The models having the highest F values (models 1 and 2) indicated that the lower cut-off point was consistently between 3 and 4; model 2, which had a cut-off point of 7 to 8 for the upper boundary, had the higher F value. Thus, the optimal model was determined to be model 2. However, there was only a slight difference in the F values for models 1 and 2. To show how the categorization differentiated between severity groups, the mean interference scores of the fatigue severity groups in models 1 and 2 are shown in Figure 1. This showed that the discrepancy in each interference score was almost the same in these two models; the only exceptions were the work and enjoyment items; both of which were greater in model 2. Additionally, Figure 2 is a line graph of the mean BFI-J interference score and fatigue worst score. It showed that the optimal cut points were associated with large increases in interference. The steepest slopes were found between 3 to 4 and 6 to 7. Thus, analysis using the mean interference score suggested that a score of 6 to 7 as the upper boundary. Interpreting BFI and CFS Scores The CFS and BFI were significantly correlated with each other as demonstrated by their concurrent validity. We, therefore, examined Fig. 1. Discrepancy of mean interference scores between the fatigue severity groups by each daily life activity (n 252). Cut-off point for moderate/severe fatigue was 6/7 and 7/8 in model 1 and model 2, respectively. Cut-off point for mild/moderate fatigue was 3/4 in common. The greater discrepancy in each mean interference score indicates the more valid categorization. Fig. 2. Plot of mean BFI-J interference score against fatigue severity measured by Fatigue worst on BFI-J (n 252).

9 114 Okuyama et al. Vol. 25 No. 2 February 2003 the possibility of comparing these two fatigue scales with each other in a regression model, to enhance their performance in future research; we did this to translate the score on one scale into that on the other scale. We conducted bivariate regression analysis, which yielded the following regression equation: BFI worst item score 0.17 CFS score This equation indicated that 6 points for the CFS equals 1 point for the BFI worst item score. Also, the intercept was approximated to 0. Thus, we interpreted that 0, 1 6, 7 12,..., and for the CFS corresponded with 0, 1, 2,..., and 10 for the BFI worst item score. Figure 3 showed a line of classified CFS and mean BFI interference scores. The steepest slopes were found between 3 and 4 and 6 and 7, consistent with the cut point for the BFI-J and original BFI. Fig. 3. Plot of mean BFI-J interference score against fatigue severity measured by Cancer Fatigue Scale (n 252). No patients had scores greater than 48. Additional Findings: Fatigue Severity and Interference Regarding fatigue severity, when we applied model 1 as described above, 18%, 30%, and 34% of patients were categorized as having severe, moderate, and mild fatigue, respectively. In addition, when we arbitrarily defined a score of 4 or more on the interference items as indicating a clinically problematic disability, 48% of the patients were found to have interference with daily activity due to fatigue. Specifically, 37%, 38%, 36%, 36%, 31%, and 35% of them had interference with activity, mood, walk, work, relationships with others, and enjoyment, respectively. Furthermore, we compared the fatigue interference staircase in our study with that in a previous study in the United States 34 (Figure 4). Each severity rating in the staircases represented groups of patients having the worst symptom severity at that level. Also, an interference items were included in the staircases when the group mean for a sever- Fig. 4. Activity impaired by increased fatigue severity comparison in staircase between United States (n 354) and Japan (n 252).

10 Vol. 25 No. 2 February 2003 Validation of the Japanese Version of the BFI 115 ity item was 4 or more. In both staircases, increasing interference with activity is associated with increasing fatigue severity. According to this result, patients having a score or 7 or higher on the worst fatigue item can be defined as being extremely fatigued in both samples. Discussion The BFI-J showed excellent validity and reliability. In particular, the minimum number of missing value rates proved that the scale is easy to administer. Factor analysis confirmed its single-dimensional structure as well as that of the original scale, indicating good construct validity. Patients having poor ECOG performance status scores had higher BFI-J scores, which indicated the discriminant validity. Also, the correlation of the BFI-J with existing fatigue scales such as CFS and POMS fatigue subscale was found to be significant. Furthermore, the large effect size between the BFI-J and CFS, which was developed in Japanese cancer patients and was shown to have excellent feasibility in previous studies, proved the optimal performance of the BFI-J in such patients. Among the BFI-J scores, the global score consistently showed higher correlation coefficients with other fatigue instruments than did either the worst or usual fatigue item. This may indicate that the global score has better stability of than do single item scores. On the other hand, use of a single item score is more practical from a clinical standpoint, especially if assessment is done on a daily basis. Thus, both approaches should be considered depending on the study design and setting. Among the other fatigue scales, the CFS showed excellent reliability and validity, especially because of the few missing data and its robust structure, indicating its feasibility for Japanese cancer patients. The POMS fatigue subscale also showed good reliability and validity. This subscale had the biggest correlation coefficient with the POMS depression subscale and the lowest correlation coefficient with the hemoglobin level among the fatigue instruments. Originally the POMS was designed to assess patients mood status. Our result indicated that the concept of fatigue subscale in the POMS is a relatively psychological one. The POMS vigor subscale had a relatively small effect size when compared with other fatigue instruments, indicating that vigor in the POMS is not the counter-concept to fatigue. Furthermore, our results failed to reveal the discriminant validity of this subscale. Therefore, use of the POMS vigor subscale to assess fatigue is not recommended. In addition, EORTC QLQ-C 30 fatigue subscale consists of only 3 items that correlated with other fatigue instruments and had the large effect size, indicating its utility. However, factor analysis for the whole scale failed to find these items in a certain factor. Also, the Cronbach s alpha coefficient for this subscale was relatively low (0.79), which may also indicate the inconsistency of the scale items. However, the low coefficient may have been due to the small number of items included in this subscale, because the alpha coefficient is influenced by the number of items included in a measure: the smaller the number, the lower the coefficient. Assessing fatigue using a multi symptom or quality of life questionnaire must be beneficial in screening for this symptom. Further research is required to establish the utility of the fatigue subscale. Identification of patients having a critical level of fatigue is useful in providing intensive care to the target population. In the present study, a score of 3 to 4 on the BFI-J was determined to be a boundary between the mild and moderate fatigue groups. On the other hand, the boundary between moderate and severe fatigue was not clear. We determined that there was no proof of clinical differences between the models having 7 to 8 and 6 to 7 as a boundary between moderate and severe fatigue, although MANOVA results suggested that the former model was somewhat superior. However, the statistical results obtained using the former model may be not so reliable because of the small number of patients who rated 8 or more on the fatigue scale. In the original BFI study, a score of 6 to 7 was determined to be a boundary between moderate and severe fatigue, which was consistent with pain severity ratings, however, the boundary between mild and moderate fatigue was not clearly determined. In considering the results of this study and ours, fatigue severity should be categorized as mild (1 3), moderate (4 6), and severe (7 10). It should be noted that this categorization can be applied across cultures, indicating cross-cultural validity of the BFI.

11 116 Okuyama et al. Vol. 25 No. 2 February 2003 The results of the present study show that it is possible to cross-interpret CFS and BFI scores accurately and easily. Specifically, the result clearly revealed the linear association between these two scales, as a score of 6 on the CFS corresponds with a score of 1 on the BFI. The establishment of this interpretation method enhances the effectiveness of both fatigue scales. Furthermore, the cut-off points of 3 and 7 on the BFI-J correspond with 18 and 19 and 36 and 37 on the CFS, respectively. In a previous study, we found that a score of 18 on the CFS was a cut point for screening clinical fatigue, defining as fatigue that causes interference with daily activities. 5 This consistency shows the feasibility of categorizing patients based on this cut point. According to the fatigue classification described above, 18%, 30% and 34% of the patients experienced mild, moderate, and severe fatigue, respectively. Also, about half of the patients experienced interference with daily activities due to fatigue. These results revealed that fatigue is a critical problem even in ambulatory cancer patients and should be treated intensively. Finally, this validation study had two limitations. First, it was conducted using ambulatory cancer patients. Thus, patients having extremely severe fatigue may not be have been included. Second, the sensitivity to the changes in fatigue of the BFI-J was not investigated. Further studies of these points are required. In conclusion, this study proved that the BFI-J is a reliable, valid self-rating assessment tool for fatigue. Presently in Japan, two scales specifically designed to assess fatigue in cancer patients are available. They should be chosen as appropriate and applicable for the purpose of study. The BFI is now a multilingual scale because its availability in English and Japanese; Chinese, German, and Korean versions of it are now being developed, which is helpful, as this scale is particularly applicable in international studies. Also, interference items play a particular role in fatigue research. The reliability and validity of the CFS have been established in a series of studies, which means that it possesses stable feasibility; in particular, its multidimensional characteristics provide useful information in descriptive studies. Additionally, both the POMS fatigue and EORTC QLQ-C30 fatigue subscales also can be used; however, the user has to be aware of their characteristics clarified in this study. Acknowledgments We would like to thank the patients who cooperated so willingly. We would also like to thank the attending physicians for their assistance in enrolling the patients into the study: Drs. H. Fujii, J. Furuse, K. Gotoh, R. Hayashi, K. Ishizawa, K. Ito, R. Kakinuma, K. Kubota, Y. Maru, T. Matsumoto, H. Minami, M. Muto, F. Nagashima, H. Ohmatsu, A. Ohtu, M. Saikawa, Y. Sano, Y. Sasaki, and Y. Shima (National Cancer Center Hospital East, Japan). Finally we also would like to thank Ibrahima Gning and Jermaine McMillan, (Pain Research Group, M.D. Anderson Cancer Center) for data entry and editing, respectively. This work was supported in part by Grants-in-Aid for Cancer Research (9-31) and the Second Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health and Welfare, Japan. Toru Okuyama is a 2000 awardee of an American Cancer Society International Fellowship for Beginning Investigators from the International Union Against Cancer. References 1. Vainio A, Auvinen A, with Members of the Symptom Prevalence Group. Prevalence of symptoms among patients with advanced cancer: an international collaborative study. J Pain Symptom Manage 1991;12: Stone P, Hardy J, Broadley K, et al. Fatigue in advanced cancer: a prospective controlled cross-sectional study. Br J Cancer 1999;79: Degner LF, Sloan J. Symptom distress in newly diagnosed ambulatory cancer patients and as a predictor of survival in lung cancer. J Pain Symptom Manage 1995;10: Bower JE, Ganz PA, Desmond KA, et al. Fatigue in breast cancer survivors: occurrence, correlates, and impact on quality of life. J Clin Oncol 2000;18: Okuyama T, Tanaka K, Akechi T, et al. Fatigue in ambulatory patients with advanced lung cancer: prevalence, correlated factors, and screening. J Pain Symptom Manage 2001;22: Okuyama T, Akechi T, Kugaya A, et al. Factors correlated with fatigue in disease-free breast cancer patients: application of the Cancer Fatigue Scale. Support Care Cancer 2000;8: Nail L, Jones L. Fatigue side effects and treatment and quality of life. Qual Life Res 1995;4: Love RR, Leventhal H, Easterling DV, et al. Side effects and emotional distress during chemotherapy. Cancer 1989;63:

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