identifying clinically meaningful fatigue with the fatigue symptom inventory

Identifying Clinically Meaningful Fatigue with the FatigueSymptom Inventory

Kristine A. Donovan, PhD, Paul B. Jacobsen, PhD, Brent J. Small, PhD, Pamela N. Munster,MD, and Michael A. Andrykowski, PhDHealth Outcomes and Behavior Program (K.A.D., P.B.J., B.J.S) and Breast Cancer Program (P.N.M.), MoffittCancer Center & Research Institute, Tampa, Florida; Department of Psychology (P.B.J.) and School of AgingStudies (B.J.S.), University of South Florida, Tampa, Florida; and Department of Behavioral Science(M.A.A.), University of Kentucky College of Medicine, Lexington, Kentucky, USA

AbstractThe Fatigue Symptom Inventory (FSI) has been used extensively to assess and measure fatigue in anumber of clinical populations. The purpose of the present study was to further establish its utilityby examining its operating characteristics and determining the optimal cutoff score for identifyingclinically meaningful fatigue. The SF-36 Vitality scale, a measure widely used to identify individualswith significant fatigue-related disability, was used to determine the sensitivity and specificity of theFSI. Results indicate that a score of 3 or greater on those items assessing fatigue in the past week isthe optimal cutoff score for identifying clinically meaningful fatigue. Individuals who scored at orabove the cutoff also reported significantly greater fatigue interference, more days of fatigue onaverage, and fatigue a greater proportion of each day in the past week. Findings suggest that the FSIcan be used to discriminate effectively between individuals with and without clinically meaningfulfatigue.

KeywordsFatigue; Fatigue Symptom Inventory

IntroductionFatigue is generally defined as a sense of persistent tiredness or exhaustion that is oftendistressing to the individual. It is a common symptom of many diseases, including cancer [1],neurological disorders such as multiple sclerosis [2], and psychiatric disorders such asdepression [3]. Among adult cancer patients, fatigue is often the most common symptomreported [4-6]. Fatigue also is common in the general population [7,8]. One epidemiologicalstudy of working adults found that 98% reported some degree of fatigue and one in five reportedsubstantial fatigue [9].

Fatigue is a subjective phenomenon and is thus assessed most accurately by individual self-report. To this end, researchers have published a plethora of self-report instruments designed

Address correspondence to: Kristine A. Donovan, PhD Health Outcomes and Behavior Program H. Lee Moffitt Cancer Center & ResearchInstitute 12902 Magnolia Drive, MRC-PSY Tampa, FL 33612, USA E-mail: [email protected]'s Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customerswe are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resultingproof before it is published in its final citable form. Please note that during the production process errors may be discovered which couldaffect the content, and all legal disclaimers that apply to the journal pertain.

NIH Public AccessAuthor ManuscriptJ Pain Symptom Manage. Author manuscript; available in PMC 2009 November 1.

Published in final edited form as:J Pain Symptom Manage. 2008 November ; 36(5): 480–487. doi:10.1016/j.jpainsymman.2007.11.013.

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to assess and measure fatigue. A recent survey of fatigue measurement scales publishedbetween 1975 and 2004 identified a total of 71 scales focusing specifically on fatigue used in416 studies [10]. The information obtained via these measures depends on the developer'sconceptualization of fatigue and the respondents' interpretation of the questions being asked[11]. The utility of any one scale rests ultimately on its reliability and validity. A review byDittner et al. [11] of 30 published fatigue scales noted that many fatigue scales have beenpublished without basic data about their reliability or evidence of sensitivity to change. Further,few scales have demonstrated an ability to discriminate clinical cases of fatigue from noncases,with acceptable levels of sensitivity and specificity [11]. That is, few scales have establishedcutoff scores to determine clinically meaningful fatigue.

The FSI, first published in 1998 [12], has been used extensively to assess fatigue, especiallyamong cancer patients. Its psychometric properties were originally established in womenundergoing treatment for breast cancer, women who have completed treatment for breastcancer, and women with no history of cancer [12]. It was further validated in a study of malesand females with a variety of different cancer diagnoses [13]. The scale has been used sinceto assess fatigue in a number of clinical populations including breast cancer patients [14],patients undergoing hematopoietic stem cell transplantation [15], hepatocellular cancerpatients undergoing stereotactic radiotherapy [16], and patients with chronic fatigue syndrome[17]. The FSI has proven to be a valid and reliable measure of fatigue in medically ill patientsand healthy individuals, and reviewers have suggested that it is a useful tool for the assessmentof fatigue [11].

The purpose of the present study was to further establish the usefulness of the FSI by examiningits operating characteristics and determining the optimal cutoff score for identifying clinicallymeaningful fatigue. To accomplish this, we recruited a relatively large sample of women withno history of cancer who completed both the FSI and the SF-36 Vitality scale [18]. We usedreceiver operating characteristic (ROC) curve analyses of FSI scores to determine the optimalFSI cutoff score relative to the established SF-36 Vitality scale. ROC analysis has been usedpreviously to establish cutoff scores on general measures of fatigue including the Schedule ofFatigue and Anergia [19] and the Checklist Individual Strength [20], and on disease-specificmeasures such as the Bath Ankylosing Spondylitis Disease Activity Index [21]. Although thereis not an accepted standard for the assessment of fatigue, the SF-36 Vitality scale is commonlyused to validate instruments designed to assess fatigue in the general population and in patientsamples (see for example, Kleinman et al. [22]). Thus researchers have suggested that usingthe SF-36 Vitality scores of the general population as reference data is a valid approach forestablishing cutoff scores on measures of fatigue [21]. In order to indicate significant health-related limitations, previous studies [23-25] dichotomized the Vitality scale based on the25th percentile. That is, individuals scoring at or below the 25th percentile were considered tobe experiencing limitations due to fatigue while those scoring above the 25th percentile werenot considered to be suffering such limitations. Once the optimal FSI cutoff score wasidentified, we sought to explore whether interference related to fatigue, the duration of fatigue,and demographic factors differentiated individuals who scored above or below this cutoffscore.

MethodsParticipants

Participants were recruited as part of a larger study comparing quality of life in women beingtreated for early stage breast cancer and women with no history of cancer. Eligibility criteriafor women with no history of cancer were that they must: a) be within five years of the age ofthe breast cancer patient to whom they would be matched in the larger study; b) reside withinthe same zip code as the patient to whom they would be matched; c) have no discernable

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psychiatric or neurological disorders that would interfere with study participation; d) be ableto speak and read standard English; e) report no history of cancer (other than basal cell skincarcinoma) or other potentially life-threatening diseases (e.g., AIDS); and f) report no historyof a condition in which fatigue is a prominent symptom (e.g., multiple sclerosis or chronicfatigue syndrome).

ProcedurePotential participants were identified using a database maintained by Marketing SystemsGroup, Inc. (Fort Washington, PA) that draws from all listed telephone households in theUnited States and is estimated to include demographic and contact information forapproximately two-thirds of the U.S. population. For each patient who completed the six-monthassessment in the larger study, up to 25 women who resided in the same zip code and werewithin five years of the patient's age were selected randomly from the database. One of thesewomen was selected at random and sent a letter of introduction describing the study. If thiswoman did not opt out by calling a toll-free telephone number or returned a postcard expressinginterest in the study, telephone contact was initiated to further determine eligibility. If she metall eligibility criteria and verbally agreed to participate, an appointment was set up to obtainwritten informed consent and conduct an assessment. If the first woman selected could not bereached, was ineligible, refused to participate, or did not keep the appointment, another womanon the list was selected randomly until a woman matched to the patient was recruited andcompleted the assessment.

MeasuresDemographic data were obtained via a standardized self-report questionnaire. Variablesassessed were age, race/ethnicity, marital status, annual household income, educational level,height, weight, and menopausal status.

The FSI [12] is a 14-item measure that assesses the frequency and severity of fatigue and itsperceived interference. The measure includes three items specific to fatigue severity in the pastweek. Participants rate on 11-point scales (0 = not at all fatigued, 10 = as fatigued as I couldbe) their level of fatigue: 1) on average in the past week (FSI average), 2) on the day they feltmost fatigued in the past week (FSI most), and 3) on the day they felt least fatigued in the pastweek (FSI least). A composite fatigue score (FSI composite) was derived by calculating theaverage across the three severity items. This composite fatigue score showed high internalconsistency (alpha = 0.84). Analyses focused on the operating characteristics of the FSI averagescore and FSI composite score. Analyses also were conducted using participants' average ratingof the degree (0 = no interference, 10 = extreme interference) to which fatigue interfered withtheir general activity, ability to bathe and dress, normal work activity, ability to concentrate,relations with others, enjoyment of life, and mood (FSI interference); participants' ratings ofthe number of days in the past week (0 to 7) they felt fatigued (FSI days); and participants'ratings of what percent of each day (0 to 100), on average, they felt fatigued in the past week(FSI percent).

The Acute (past week) Version of the MOS 36-Item Short Form [18,26] (SF-36) is a widelyused self-report measure designed to assess perceived health and functioning. The instrumentconsists of eight scales: Physical Functioning, Role-Physical; Bodily Pain; General Health;Vitality; Social Functioning; Mental Health; and Role-Emotional. Each scale is standardizedon a 0 to 100 metric with higher scores indicating better functioning. Analyses focused on theVitality scale which consists of four items assessing how much of the time in the past weekparticipants felt “full of pep,” had “a lot of energy,” felt “worn out,” and felt “tired.” The lattertwo items are reverse coded prior to scoring. Responses range from “all of the time” to “noneof the time.” In analyses focused on the operating characteristics of the FSI, participants were

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classified as fatigued if their Vitality scale score was less than or equal to 45. This scorecorresponds to the 25th percentile for females in the U.S. general population [18], and isconsistent with previous research demonstrating that the 25th percentile is the most appropriatedichotomous indicator of health-related limitations [23]. Although previous research hasdemonstrated that a score of 50 is indicative of biologic and psychologic differences in fatigue[27-32], we chose the more stringent score of 45 as the criterion to increase the robustness ofour results.

ResultsDemographic Characteristics

The demographic characteristics of the sample are presented in Table 1. The mean age of thewomen was 56 years (range 28 - 79). The vast majority was white, married, and nearly halfhad a college degree. More than two-thirds had annual household incomes > $40,000. Theaverage body mass index was 27 and 72% of the women were post-menopausal.

Establishment of a Fatigue Cutoff ScoreTables 2 and 3 list the frequency distribution of FSI average scores and FSI composite scores,respectively. The mean FSI average score for the sample was 2.40 (standard deviation = 2.01)and the mean FSI composite score was 2.51 (standard deviation = 1.84). ROC curves wereconstructed for sensitivity and 1-specificity for the range of possible scores on FSI average andFSI composite compared with normative data for females in the U.S. general population(Figures 1 and 2). Based on established norms, the cutoff for fatigue-related disability wasdefined as a Vitality score > 45 [18,23]. The ROC curves are graphic representations of thetrade-off between the sensitivity (true-positive rate) and specificity (true-negative rate) forevery possible cutoff score on FSI average and FSI composite. The area under the curve (AUC)in each ROC curve provides an estimate of the overall discriminative accuracy of these itemsrelative to the established cutoff score for the Vitality scale. In ROC analysis, an AUC of 1represents a test with perfect accuracy relative to the established criterion, whereas an AUC of0.5 represents a test with no apparent accuracy relative to the established criterion. In the currentstudy, the AUC for each FSI fatigue measure was 0.75 using the 25th percentile on the Vitalityscale as the criterion. This value is in the range typically characterized as representing goodoverall accuracy. Visual inspection of the ROC curves for FSI average and FSI compositesuggests that a score ≥ 3 is the optimal cutoff for identifying significant fatigue using theVitality scale as the criterion.

The classification of participants based on a cutoff score of 3 on FSI average and FSI compositerelative to the 25th percentile of the Vitality scale is illustrated in Table 4. This cutoff score onFSI average yielded a sensitivity of 0.81 and a specificity of 0.69 relative to the 25th percentileof the Vitality scale. On FSI composite it yielded a sensitivity of 0.81 and specificity of 0.70relative to the 25th percentile of the Vitality cutoff score. Other cutoff scores yielded lessoptimal results. For example, a cutoff score of 4 on FSI average yielded a sensitivity of 0.62and a specificity of 0.83 relative to the 25th percentile of the Vitality scale. On FSI compositeit yielded a sensitivity of 0.56 and specificity of 0.83 relative to the 25th percentile of the Vitalitycutoff score.

Relation of Fatigue ≥ 3 Cutoff Score to Demographic CharacteristicsChi-squared analyses and analysis of variance were conducted to explore the relation of theFSI average and FSI composite cutoff score of 3 to demographic characteristics. As shown inTable 5, none of the demographic characteristics assessed were related significantly to the FSIaverage cutoff score. Similarly, none of the demographic characteristics were associated withthe FSI composite cutoff score of 3.

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Relation of Fatigue ≥ 3 Cutoff Score to Fatigue InterferenceAnalyses of variance indicated that women who scored above the FSI average cutoff reportedsignificantly greater FSI interference compared to women who scored below the cutoff (2.29± 1.80 versus 0.41 ± 0.58, P < 0.0001). Similarly, women who scored above the FSI compositecutoff reported significantly greater fatigue interference compared to women who scored belowthe cutoff (2.31 ± 1.82 versus 0.42 ± 0.61, P < 0.0001).

Relation of Fatigue ≥ 3 Cutoff Score to Fatigue DurationAnalyses of variance also indicated that the FSI average cutoff score of 3 was significantlyassociated with differences in both FSI days and FSI percent. Women who scored above theFSI average cutoff reported that they felt fatigued an average of 4.11 ± 1.97 days in the pastweek versus 1.56 ± 1.65 days for women below the cutoff (P < 0.0001). Compared to womenbelow the cutoff, women above the cutoff also reported significantly greater FSI percent; theyfelt fatigued a significantly greater proportion of the day in the past week: an average of 36.9%versus 14.0%, (P < 0.0001).

Similar results were obtained for the FSI composite cutoff. Compared to women below thecutoff, women above the cutoff reported significantly more days of fatigue on average: 4.06 ±2.03 versus 1.6 ± 1.70 (P< 0.0001). Women above the cutoff also reported that they felt fatigueda significantly greater proportion of the day in the past week: an average of 37.5% versus 14.2%(P < 0.0001).

Relation of Fatigue ≥ 3 Cutoff Score to VitalityFinally, analysis of variance was conducted to examine whether there were differences in theVitality continuous score between women below and above the FSI average and FSI compositecutoff score of 3. With respect to the FSI average cutoff, women above the cutoff reportedsignificantly higher average Vitality scores than women below the cutoff: 71.8 ± 15.27compared to 49.27 ± 19.40, (P < 0.0001). Likewise, women above the FSI composite cutoffreported significantly higher average Vitality scores: 71.64 + 15.06 compared to 48.82 ± 19.60,(P < 0.0001).

DiscussionThe results of the current study indicate that a score of 3 or greater for FSI average or the FSIcomposite is the optimal cutoff for identifying clinically meaningful fatigue using the FSI. Thatis, this score yielded the optimal sensitivity and specificity relative to the established cutoffscore on the SF-36 Vitality scale. There were no demographic characteristics associated withscoring at or above the cutoff of 3. Individuals who scored at or above the cutoff reportedsignificantly greater fatigue interference, more days of fatigue on average, and fatigue a greaterproportion of each day. As expected, individuals who reported a 3 or greater fatigue score alsohad significantly higher Vitality scores.

The FSI compares favorably with the SF-36 Vitality scale. This conclusion is based on theAUC statistics obtained when comparing the full range of FSI average and FSI compositescores with the established cutoff score on the Vitality scale (AUC = 0.75 in both cases). Theseresults show that the FSI, specifically those items concerning fatigue severity in the past week,can discriminate between those individuals with and without clinically meaningful fatigue.

As noted previously, few published measures of fatigue include a cutoff score by which todetermine the presence or absence of clinically meaningful fatigue [11]. Thus, study findingsmake the FSI relatively unique among fatigue assessment measures. The establishment of acutoff score on the FSI greatly expands the instrument's utility. For example, researchers may

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find it useful to dichotomize samples based on a cutoff score of 3 into groups with and withoutclinically meaningful fatigue. Subsequent analyses would then focus on elucidating thosephysiological and psychosocial factors that contribute to the development and persistence offatigue. A score of 3 or greater also might be used as an eligibility criterion for participationin intervention trials focused on treating clinically meaningful fatigue. Finally, the cutoff scoremay be useful clinically in screening for fatigue among medically ill patients. A “positive”screen for clinically meaningful fatigue could initiate a more comprehensive work up orassessment and the identification of contributing factors or treatable causes of the fatigue.

Strengths of the current study should be noted. The sample size was relatively large and wasrecruited using an outreach procedure designed to limit participation bias. We compared theFSI to the SF-36 Vitality scale, a measure that has been widely used with both healthy andmedically ill populations and has established norms for identifying individuals with significantfatigue. In addition, we used statistical methods appropriate for the identification of an optimalcutoff score. The current study also has several noteworthy limitations. Only women wereincluded in the study sample and the majority was peri- or post-menopausal. There also waslimited diversity within the sample with respect to ethnicity, education, and socioeconomicstatus. Thus, the operating characteristics of the FSI cutoff score are unknown in men and inminority populations and low-literacy populations of women. Finally, the finding that a cutoffscore of 3 on FSI average or the FSI composite measure yielded the optimal combination ofsensitivity and specificity was not cross-validated in a second sample of individuals. Findingsthat a similar cutoff score was obtained in another sample of healthy individuals would increaseconfidence in our findings.

In conclusion, the present study further establishes the usefulness of the FSI by determiningthat an FSI average or FSI composite score of 3 or greater is indicative of clinically meaningfulfatigue. This cutoff score yielded the optimal sensitivity and specificity relative to the widelyused SF-36 Vitality scale. The cutoff score also classified effectively those individuals withgreater fatigue-related interference and fatigue duration. These findings support the continueduse of the FSI not only as a means of assessing fatigue but also as a means of distinguishingthose individuals with clinically meaningful fatigue.

AcknowledgementsThis work was supported by National Cancer Institute Grant R01 CA82822.

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Figure 1.Receiver operating characteristic curve analysis comparing FSI average scores with establishedVitality cutoff score of > 45.

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Figure 2.Receiver operating characteristic curve analysis comparing FSI composite scores withestablished Vitality cutoff score of > 45.

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Table 1Demographic Characteristics of the Sample (n = 265)

Age in years (mean ± SD) 56.34 ± 9.42

Race/ethnicity White 252 (95.1) Non-white 13 (4.9)Marital status Married or marriage-like 184 (69.4) Not married 81(30.6)Education College degree 126 (47.5) Less than college degree 139 (52.5)Household income < $40,000 per year 72 (27.2) ≥ $40,000 per year 193 (72.8)Menopausal status Pre-menopausal 70 (27.9) Peri- or post-menopausal 181 (72.1)Body mass index (mean ± SD) 27.69 ± 6.85


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Table 2Frequency Distribution of FSI Average Scores

Score Frequency % Cumulative %

0 43 16.2 16.21 65 24.5 40.82 48 18.1 58.93 40 15.1 74.04 31 11.7 85.75 18 6.8 92.56 7 2.6 95.17 6 2.3 97.48 6 2.3 99.610 1 0.0 100.0


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Table 3Frequency Distribution of FSI Composite Scores

Score Frequency % Cumulative %

0 27 10.2 10.2 > 0 ≤ 1 47 17.7 27.9> 1 ≤ 2 54 20.4 48.3> 2 ≤ 3 48 18.1 66.4> 3 ≤ 4 41 15.5 81.9> 4 ≤ 5 25 9.4 91.3> 5 ≤ 6 11 4.2 95.5> 6 ≤ 7 8 3.0 98.5> 7 4 1.5 100.0


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Table 4Correspondence of FSI Average and FSI Composite with the Vitality Scale of the SF-36

SF-36 Vitality Scale Frequency (%)> 45 ≤ 45

FSI averagea< 3 146 (55.1) 10 (3.8)≥ 3 67 (25.3) 42 (15.9)

FSI compositeb< 3 149 (56.2) 10 (3.8)≥ 3 64 (24.2) 42 (15.9)

aChi-squared = 41.98, P < 0.0001.

bChi-squared = 44.80, P < 0.0001.


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± 8

.0.9

227

.5 ±

6.3

28.0

± 7

.6.6

0


identifying clinically meaningful fatigue with the fatigue symptom inventory

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