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The Oncologist, Vol. 12, No. suppl_1, 11-21, May 2007; doi:10.1634/theoncologist.12-S1-11
© 2007 AlphaMed Press

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Assessment of Cancer-Related Fatigue: Implications for Clinical Diagnosis and Treatment

Pascal Jean-Pierrea,b, Colmar D. Figueroa-Moseleya,c, Sadhna Kohlia,c, Kevin Fiscellab,d, Oxana G. Palesha, Gary R. Morrowa,e

aDepartment of Radiation Oncology, bDepartment of Family Medicine, cDepartment of Medicine, dDepartment of Community and Preventive Medicine, and eDepartment of Psychiatry, University of Rochester School of Medicine and Dentistry, James P. Wilmot Cancer Center, Rochester, New York, USA

Key Words. Cancer • Fatigue • Assessment • Measurement • Instruments

Correspondence: Pascal Jean-Pierre, Ph.D., University of Rochester Medical Center, James P. Wilmot Cancer Center, 601 Elmwood Avenue, Box 704, Rochester, New York 14642, USA. Telephone: 585-273-2545; Fax: 585-461-5601; e-mail: Pascal_Jean-Pierre{at}urmc.rochester.edu

Received December 11, 2006; accepted for publication January 4, 2007.


   ABSTRACT
Top
 Abstract
Introduction
 Diagnosing Cancer-Related...
 Tools for the Assessment...
 Challenges in the Evaluation...
 Conclusions
 Disclosure of Potential...
 Acknowledgments
 References
 
Cancer-related fatigue (CRF) is a highly prevalent and debilitating symptom experienced by most cancer patients during, and often for considerable periods after, treatment. The recognition of the importance of CRF to patients' psychosocial and cognitive functioning, as well as to their quality of life, has driven the development of a wide range of assessment tools for screening and diagnosis of CRF. Over 20 different measures have been used to assess CRF from either a unidimensional or multi-dimensional perspective. Unidimensional measures are often single-question scales that generally focus on identifying the occurrence and severity of CRF, whereas multidimensional measures may also examine the effect of CRF across several domains of physical, socio-emotional, and cognitive functioning. This paper provides an overview and critique of measures commonly used to assess CRF. Single-question assessment is the most commonly used and the most useful methodology. Strategies to facilitate reliable assessment of CRF are also discussed.

Disclosure of potential conflicts of interest is found at the end of this article.


   INTRODUCTION
Top
 Abstract
 Introduction
Diagnosing Cancer-Related...
 Tools for the Assessment...
 Challenges in the Evaluation...
 Conclusions
 Disclosure of Potential...
 Acknowledgments
 References
 
Cancer-related fatigue (CRF) is a highly prevalent symptom in patients with cancer. It can affect patients on multiple levels of psychosocial and physical functioning and usually causes a noticeable decrease in patients' quality of life. The negative effects of this symptom are often experienced even before a formal cancer diagnosis [1] and continue beyond the completion of treatment [2,3], regardless of the type of cancer therapy received.

Patients and oncology professionals are becoming increasingly aware of the clinical relevance of CRF. The importance of CRF to patients' quality of life underscores the need for more effective methods to be developed to control this symptom. Essential to the investigation of more effective control is the need for reliable and valid assessment. Various methods for assessing CRF have been used. In clinical trial settings, CRF has been assessed by patients reporting its presence or absence and intensity based on scores on either a single item or aggregated items of specific measures such as the Brief Fatigue Inventory (BFI). Variations in how researchers and clinicians conceptualize this debilitating symptom have resulted in the development of different tools for assessing CRF.

This paper presents and evaluates measures that have been used to assess CRF along with strategies to facilitate reliable assessment of this symptom.


   DIAGNOSING CANCER-RELATED FATIGUE
Top
 Abstract
 Introduction
 Diagnosing Cancer-Related...
Tools for the Assessment...
 Challenges in the Evaluation...
 Conclusions
 Disclosure of Potential...
 Acknowledgments
 References
 
Variations in the definition of CRF have influenced the development of reliable CRF measures. Most definitions have been based on some version of: "a persistent, subjective sense of tiredness related to cancer or cancer treatment that interferes with usual functioning" [4]. Albeit very useful to our understanding of CRF, this definition does not include two important characteristics: this symptom is disproportional to the patient's level of exertion and it is not relieved by rest or sleep. Compared with normal fatigue that is alleviated by rest or sleep, CRF is a more intense and severe symptom that can persist for a considerable time following cancer treatment.

We and others have found that patients with cancer can easily and reliably rate their fatigue and its severity on a simple numeric scale ranging from 0 to 10. Patients are typically asked, "How would you rate your fatigue on a scale of 0–10 over the past 7 days?" Some have characterized responses into broad categories such as: a score of 0 indicates an absence of fatigue, a score of 1–3 indicates the presence of mild fatigue that does not require clinical intervention, and scores of 4–6 and 7–10 indicate moderate and severe fatigue, respectively, which require further evaluation and clinical intervention.


   TOOLS FOR THE ASSESSMENT OF CANCER-RELATED FATIGUE
Top
 Abstract
 Introduction
 Diagnosing Cancer-Related...
 Tools for the Assessment...
Challenges in the Evaluation...
 Conclusions
 Disclosure of Potential...
 Acknowledgments
 References
 
The fact that CRF is a subjective experience has determined the type of measures developed and used to assess this symptom. Most measures have focused on patients' self-report of CRF. This approach makes sense as all experiences of CRF, even at the observable behavioral and physiological levels, are influenced by patients' personal understanding and subjective experiences.

Self-report measures of CRF have primarily been developed for use in clinical trial settings to evaluate factors influencing this symptom and the impact of related therapeutic interventions. However, measures developed to assess CRF in clinical trials are also useful in clinical practice. The following section provides a brief overview of selected measures that have been used to assess CRF and discusses important conceptual and psychometric characteristics of these measures.

Unidimensional Tools
Most of the single-item measures of CRF are taken from symptom checklists such as the Symptom Distress Scale [5], the Rotterdam Symptoms Checklist [6], the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 quality-of-life measure [7], the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) [8], the MD Anderson Symptoms Inventory [9], and the Zung Self-Rating Depression Scale [10] (Table 1 [5–16] and Fig. 1). These single-item measures focus primarily on detecting the presence or absence of CRF. Few of these measures focus on the severity of CRF and its related effects on various aspects of patients' lives.


Figure 1
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  		Figure 1. Examples of unidimensional methods to assess fatigue: embedded within symptom checklists (A) and an independent fatigue-specific tool (B) [6,7,9,12]. Extract from the European Organisation for Research and Treatment of Cancer (EORTC)-QLQ-30 reproduced from Aaronson NK, Ahmedzai S, Bergman B et al. The European Organisation for Research and Treatment of Cancer QLQ-C30: A quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 1993;85:365–376, with permission from the EORTC. Copies of the QLQ-C30 are available from the EORTC from Ken Cornelissen (e-mail: ken.cornelissen{at}eortc.be). Extract from the MD Anderson Symptom Inventory reproduced from Cleeland CS, Mendoza TR, Wang XS et al. Assessing symptom distress in cancer patients: The MD Anderson Symptom Inventory. Cancer 2000;89:1634–1646, with permission from John Wiley & Sons, Inc. Extract from the Visual Analog Fatigue Scale reproduced from Glaus A. Assessment of fatigue in cancer and non-cancer patients and in healthy individuals. Support Care Cancer 1993;1:305–315, with permission from Springer Verlag.

 


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  		Table 1. Unidimensional tools used for the assessment of fatigue

 
An example of a single-item measure to assess the presence and severity of CRF is the Visual Analog Fatigue Scale (VAFS) [12], which has been designed specifically for use with cancer patients. The VAFS is also suitable for use in healthy individuals, a feature that could facilitate comparative analyses of the severity of fatigue experienced by patients with cancer versus their healthy counterparts. The simplicity of the VAFS lends itself to the monitoring of fatigue at multiple time points over the course of a day, which could facilitate our understanding of variations in CRF during waking hours [12].

Multi-item (unidimensional) measures of CRF that have been validated in patients with cancer include the BFI [14], which measures the severity of fatigue over the previous 24 hours. The BFI has been used as a screening tool for fatigue in many clinical trials. A scoring system has been developed for the BFI that facilitates identification of patients experiencing severe fatigue. Other multi-item CRF measures are also available that allow evaluation of the distress associated with CRF across multiple days and have been validated in a population of cancer survivors [15]. Some of these measures have been developed with input from cancer patients [16].

Multidimensional Tools
Some researchers have advanced the theory that CRF is a multidimensional symptom affecting behavioral, cognitive, somatic, and affective domains of patient functioning. Several of these are summarized in Table 2 [17–27] and are discussed briefly below.


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  		Table 2. Multidimensional tools used for the assessment of fatigue

 
The Multidimensional Fatigue Inventory (MFI) [18] has been validated in patients with cancer and focuses on the subjective experience of fatigue. This scale evaluates the general, mental, and physical dimensions of fatigue, as well as levels of motivation and activity. The 20-item version of the MFI has been used to assess fatigue in patients with a variety of cancers who are receiving chemotherapy or radiotherapy (Table 3Go) [28–56]. The MFI has also been shown to capture differences in CRF across time. Using this scale, higher levels of fatigue have been detected during and immediately after treatment. One study confirmed higher levels of fatigue across all five dimensions measured (general, physical, activity, motivation, and mental) in patients receiving anticancer treatment compared with healthy individuals (Fig. 2) [30]. The MFI has also been used to demonstrate the persistence of multiple dimensions of fatigue after completion of initial treatment in a range of cancers [57,58].


Figure 2
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  		Figure 2. Multidimensional Fatigue Inventory (MFI) subscale scores among patients with cancer with/without anemia and healthy controls. Higher scores indicate greater fatigue. Based on data from Holzner B, Kemmler G, Greil R et al. The impact of hemoglobin levels on fatigue and quality of life in cancer patients. Ann Oncol 2002;13:965–973.

 


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  		Table 3. Fatigue during anticancer therapy, as assessed by some of the most widely used multidimensional tools

 


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  		Table 3. (Continued)

 
The original Functional Assessment of Cancer Therapy–Fatigue scale (FACT-F) was relatively long (41 items, each assessed on a scale of 0–4) [19]. However, the FACT-F includes a brief 13-item fatigue subscale that is more suitable for use in clinical trials. The FACT-F has been used to evaluate fatigue in patients with a variety of diagnoses receiving various treatments (Table 3Go) [35–40]. In each study, the majority of patients reported some degree of fatigue regardless of diagnosis or treatment modality. A study using the FACT-F found that persistent fatigue was related to depression and performance status following treatment for hematologic malignancies [59]. The FACT-F also demonstrated the persistence of significant levels of fatigue in patients with advanced lung cancer on completion of treatment [60].

The original version of the Multidimensional Fatigue Symptom Inventory (MFSI), like the FACT-F, was long (including 83 items) and required too much time to complete to be suitable for use in the clinical setting [20]. A validated short form is now available, which consists of 30 items that evaluate general, emotional, physical, and mental fatigue and vigor over the preceding week [21]. The MFSI has been used to evaluate fatigue during anthracycline-based therapy for breast cancer and has shown that fatigue increases significantly with each treatment cycle (Fig. 3) [41].


Figure 3
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  		Figure 3. Temporal profile of fatigue evaluated using the Multidimensional Fatigue Symptom Inventory (MFSI) during anthracycline-based therapy for breast cancer. Higher scores indicate greater fatigue. Based on data from Mills PJ, Parker B, Dimsdale JE et al. The relationship between fatigue and quality of life and inflammation during anthracycline-based chemotherapy in breast cancer. Biol Psychol 2005;69:85–96.

 
The revised Piper Fatigue Scale (PFS) [23] was primarily validated in patients with breast cancer and, as such, might have limited generalizability to patients with other cancer diagnoses. The evaluation reference point of the PFS is "now," thus, this scale can be used only in patients experiencing fatigue at the time of assessment. Both the original and revised versions of the PFS have been widely used in the assessment of CRF during anticancer therapy (Table 3Go). These aforementioned studies have consistently demonstrated elevated levels of fatigue during anticancer treatment in patients with breast, liver, and ovarian cancer and malignant melanoma who were treated with chemotherapy, radiotherapy, and immunotherapy (Table 3Go). Longitudinal studies using the PFS as a measure of fatigue have demonstrated persistent and elevated levels of fatigue across multiple domains in patients with various cancer diagnoses compared with controls (Fig. 4) [61–64].


Figure 4
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  		Figure 4. Persistent fatigue following treatment for breast cancer. (A): Total Piper Fatigue Scale (PFS) scores at initial and follow-up (4–6 months later) assessments. (B): Adjusted mean sub-scale scores at initial assessment. Higher scores indicate more severe fatigue. Based on data from Andrykowski MA, Curran SL, Lightner R. Off-treatment fatigue in breast cancer survivors: A controlled comparison. J Behav Med 1998;21:1–18.

 
The Fatigue Symptom Inventory (FSI) [26,27] is another multidimensional measure that considers temporal variations in fatigue. This scale measures the severity, frequency, diurnal variation, and interference with quality of life resulting from fatigue over the previous 7 days. However, the test–retest reliability of this scale is weak, perhaps because of the relatively long recall period. The FSI has mainly been used in studies examining the effect of chemo-therapy for breast cancer [51–56]. These studies have shown that the majority of patients with breast cancer who receive chemotherapy are likely to experience some degree of CRF. More importantly, these studies have shown that the CRF these patients reported was more severe than normal fatigue reported by healthy controls. In follow-up studies using the FSI, patients with breast cancer reported significantly more fatigue for longer periods—months and even years following completion of treatment [65–67].

Some less widely used measures of CRF include the Lee Fatigue Scale [17], the revised Schwartz Cancer Fatigue Scale [24], and the Cancer Fatigue Scale [25]. The Schwartz Fatigue Scale has been used successfully in a number of interventional trials to assess the impact of exercise on the experience of fatigue in women with breast cancer [68–70].


   CHALLENGES IN THE EVALUATION OF CANCER-RELATED FATIGUE
Top
 Abstract
 Introduction
 Diagnosing Cancer-Related...
 Tools for the Assessment...
 Challenges in the Evaluation...
Conclusions
 Disclosure of Potential...
 Acknowledgments
 References
 
Perhaps one of the greatest challenges facing oncology professionals is distinguishing CRF from other psychosomatic and psychological ailments, such as depression. Oncology professionals should consider and exclude the possibility of an underlying affective disorder before making a diagnosis of CRF. The ability to discriminate CRF from fatigue related to other medical and psychological conditions would facilitate the development of randomized clinical trials and interventions to identify and control this symptom more precisely.

One challenge in separating CRF from other related conditions, such as depression, lies in measurement. Fatigue measures and depression measures can correlate very highly, as evidenced in a sample of 724 cancer patients taking part in a clinical trial assessed 1 week after their first chemotherapy treatment [71]. Depression, as assessed by the Center for Epidemiologic Studies Depression (CES-D) questionnaire [72] and the depression subscale of the Profile of Mood States (POMS) [73] had correlations of 0.69 and 0.59, respectively, with the Fatigue Symptom Checklist (FSCL) [74] and correlations of 0.68 and 0.55, respectively, with the fatigue/inertia subscale of the POMS. The strength of these correlations indicates that there is extensive overlap with depression in these multi-item measures of fatigue. The extent of the overlap between fatigue and depression is reduced when using a single-item measure for fatigue. In this same sample, we also asked patients "to what degree have you experienced fatigue during the past week?" on a 1–10 scale anchored by 1 = not at all and 10 = a great deal. This single-item assessment of fatigue correlated to a substantially lower degree with the CES-D and the POMS-Depression Dejection (POMS-DD) subscale at 0.57 and 0.40, respectively, while correlating robustly with the fatigue/inertia subscale of the POMS (r = 0.79) and with the FSCL (r = 0.64). Similar results were also observed in a sample of 450 patients from an ongoing trial in which fatigue (measured by the BFI) and depression (by the CES-D and POMS-DD subscale) were assessed 1 week after their second chemotherapy treatment. In this sample, the BFI total score correlated at 0.55 and 0.47 with the CES-D and the POMSDD, respectively. As in the previous sample, a single question assessing fatigue at its worst during the last 24 hours on a 0–10 scale had considerably lower correlations with the CES-D and the POMS-Dsubscale at 0.39 and 0.32, respectively, than the full measure. This question, which is one of the nine questions on the BFI, is often used as a stand-alone, single-item fatigue assessment. It correlated with the full BFI at 0.80.

Another ongoing challenge in measuring CRF is the difficulties cancer patients may experience in reporting the presence/absence and severity of this symptom. These reporting difficulties are also evident in patients' inability to complete multi-item questionnaires several times per day. Difficulties reporting CRF represent a considerable challenge to researchers involved in developing clinical intervention trials for the management of CRF. However, work is currently under way to develop computerized assessment tools that could prove useful in both the research and clinical settings [75].

Fluctuations across time, that is, the temporal profile of CRF in patients, should also be considered when screening and monitoring this symptom during and after treatment. Fatigue levels may fluctuate throughout the day and clinical trials seeking to evaluate the relationship between treatments for cancer and CRF should take into account the possibility of daily, and even hourly, fluctuations.


   CONCLUSIONS
Top
 Abstract
 Introduction
 Diagnosing Cancer-Related...
 Tools for the Assessment...
 Challenges in the Evaluation...
 Conclusions
Disclosure of Potential...
 Acknowledgments
 References
 
Although disagreement exists regarding the etiologies of CRF, oncology professionals agree that this subjective symptom is highly prevalent among patients both during and after cancer treatment. Oncology professionals have also become more cognizant of the debilitating effects of CRF on important areas of physical, emotional, and cognitive functioning, as well as on quality of life. Many different instruments are available to measure CRF. Most of these measures vary in their assumptions of the latent structure of CRF as either a unidimensional or multidimensional symptom. Variations in symptom conceptualization have influenced the development of these measures, and could markedly influence data collection and interpretation. In addition, some of these measures involve a general assessment of fatigue and do not focus on fatigue related to cancer and its treatments. A lack of cancer specificity might introduce extraneous variance in the assessment process.

Multidimensional measures could add texture and relevance to the assessment of CRF based on the assumption that this symptom affects multiple interactive physical, emotional, and cognitive domains. However, for such a multidimensional assessment to be reliably obtained and authenticated, a clear understanding of the independent and interactive contributions of each of the proposed domains of CRF is necessary. Unfortunately, relevant information to facilitate an adequate mapping of the etiologies of CRF and its multidimensionality is limited and controversial.

Compared to multidimensional measures, unidimensional measures of CRF that focus on the detection of the presence or absence and severity of the symptom are often portrayed as unable to capture the complexities of CRF. As is the case for the subjective symptoms of nausea and pain, we do not believe that the subjective experience of fatigue is, in itself, complex. Patients can very reliably report its occurrence and severity.

It might be more relevant from both a clinical and research standpoint to use a simple measure that could clearly indicate the presence/absence and severity of CRF for patients during and after treatment. As one early researcher noted, "the validity of subjects' self-report on simple rating scales is often ‘equal or superior’ to considerably more lengthy, cumbersome, complex, and costly questionnaires and rating schedules" [76]. It is important to recognize that adding more items or more domains to a simple measure of a subjective symptom does not make that measure more objective, reliable, or valid. It is, perhaps, for this reason that simple, single-item measures of CRF have become the most frequently used assessment tools.


   DISCLOSURE OF POTENTIAL CONFLICTS OF INTEREST
Top
 Abstract
 Introduction
 Diagnosing Cancer-Related...
 Tools for the Assessment...
 Challenges in the Evaluation...
 Conclusions
 Disclosure of Potential...
Acknowledgments
 References
 
G.R.M. has acted as a consultant for MGI Pharma and Cephalon.


   ACKNOWLEDGMENTS
Top
 Abstract
 Introduction
 Diagnosing Cancer-Related...
 Tools for the Assessment...
 Challenges in the Evaluation...
 Conclusions
 Disclosure of Potential...
 Acknowledgments
References
 
The authors are recipients of National Cancer Institute grants 1R25-CA102618-01A1 and 2U10 CA037420-20, and American Cancer Society grant RSG01071-01-PBP. Publication of this article was supported by a grant from Cephalon, Inc., Frazer, PA.


   REFERENCES
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 Abstract
 Introduction
 Diagnosing Cancer-Related...
 Tools for the Assessment...
 Challenges in the Evaluation...
 Conclusions
 Disclosure of Potential...
 Acknowledgments
 References
 

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