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Annals of Oncology Advance Access originally published online on September 5, 2007
Annals of Oncology 2007 18(11):1861-1869; doi:10.1093/annonc/mdm349
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© 2007 European Society for Medical Oncology

quality of life

Clinically relevant fatigue in cancer outpatients: the Edinburgh Cancer Centre symptom study

D. J. Storey1,*, R. A. Waters2, C. J. Hibberd3, R. W. Rush4, A. T. Cargill5, L. R. Wall1, M. T. Fallon3, V. A. Strong3, J. Walker6 and M. Sharpe6

1 Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
2 Centre for Statistics in Medicine, Wolfson College Annexe, Oxford, UK
3 University of Edinburgh Cancer Research Centre, Western General Hospital, Edinburgh, UK
4 Centre for Integrated Healthcare Research, Queen Margaret University College, Edinburgh, UK
5 SAS, Whittington House, Medmenham, Buckinghamshire, UK
6 School of Molecular and Clinical Medicine, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edinburgh, UK

* Correspondance to: Dr D. Storey, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XU. Tel: +44 (0)131 537 1000; Fax: +44 (0) 131 537 3914; E-mail: drdjs{at}talk21.com


   Abstract
Top
 Abstract
introduction
 patients and methods
 results
 discussion
 appendix: cancer and treatment...
 Acknowledgements
 References
 
Background: Fatigue is associated with cancer and its treatment but we know little about how many and which patients suffer fatigue of clinical severity. We aimed to determine the prevalence of clinically relevant fatigue (CRF) and its associations in outpatients with various cancer diagnoses.

Patients and methods: A survey of outpatients with colorectal, breast, gynaecological, genitourinary, sarcoma, melanoma and miscellaneous tumours at a regional cancer centre. Patients completed the European Organisation for Research and Treatment of Cancer (EORTC) fatigue subscale and the Hospital Anxiety and Depression Scale (HADS). These self-report data were linked to demographic and clinical variables. Data were available on 2867 outpatients.

Results: The prevalence of CRF (EORTC fatigue subscale ≥40) was 32% (95% confidence interval 31–34%). The variables independently associated with CRF were primary cancer site, having disease present, type of cancer treatment and emotional distress (total HADS score ≥15). Emotional distress had the strongest association with fatigue but half the cases of CRF were not distressed.

Conclusion: CRF is common in cancer outpatients and is associated with type of disease and treatment, as well as with emotional distress. The association between CRF and emotional distress is strong but they are not equivalent conditions.

Key words: associations, cancer, fatigue, predictors, prevalence, treatment


   introduction
Top
 Abstract
 introduction
patients and methods
 results
 discussion
 appendix: cancer and treatment...
 Acknowledgements
 References
 
Fatigue is increasingly recognized as the most common symptom associated with cancer and its treatment [1, 2]. It has been reported to be strongly associated with emotional distress [3, 4]. Most previous studies have described fatigue in terms of sample mean scores. A smaller number of reports have estimated the prevalence of cases of clinically relevant fatigue (CRF) with prevalence estimates from 15 to 99% [4–7]. This range reflects differing case definitions and fatigue measures, as well as differences in the populations studied (see Table 1). We are not aware of any published estimates of the prevalence of CRF in a representative outpatient population with mixed cancer diagnoses.


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  		Table 1 Studies that specifically examined fatigue as an outcome (sample n > 200)

 
Whilst previous studies have evaluated the risk factors for fatigue in cancer patients, it remains unclear whether the primary cancer site is independently associated with fatigue or whether factors such as age, gender, disease extent and treatment are more important. There is also a need to clarify whether the association between fatigue and emotional distress is stronger than that with cancer-related factors. The studies of mixed cancer patient samples published to date [4, 8–11] have been small or did not address these questions. We therefore aimed to estimate the prevalence of CRF in a large sample of outpatients with a variety of cancer diagnoses; to determine demographic and clinical risk factors for CRF; and to measure the association of CRF with emotional distress.


   patients and methods
Top
 Abstract
 introduction
 patients and methods
results
 discussion
 appendix: cancer and treatment...
 Acknowledgements
 References
 
This was a cross-sectional survey that linked self-report data with clinical and demographic data. The study took place in the Edinburgh Cancer Centre, a regional, tertiary cancer centre that is the sole provider of specialist cancer services to a geographically defined area of 1.5 million people in the South East of Scotland, United Kingdom. We surveyed 3424 consecutive patients attending for follow-up visits between June 2003 and December 2004 in outpatient cancer clinics specializing in the following cancer types: colorectal, breast, gynaecological, genitourinary, sarcoma, melanoma and miscellaneous cancers (including phase 1 trials). As part of routine semi-automated symptom screening, all patients attending follow-up clinics were invited to participate. After the patient had checked in, the questionnaire was administered on touch-screen computers and the results were made available to the oncologist prior to the consultation. Only patients who were too ill to complete the questionnaire and those with cognitive impairment or communication difficulties were excluded. As the data were collected as part of the clinical service, individual patients’ written consent was not obtained. Approval for the aggregated anonymized data to be reported was obtained from the local Research Ethics Committee.

measures
Fatigue was measured using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ core 30) fatigue subscale [12]. This comprises three items relating to the past week: ‘did you need to rest?’, ‘have you felt weak?’ and ‘were you tired?’ Each item is answered on a four-point scale: ‘not at all’, ‘a little’, ‘quite a bit’ and ‘very much’. In accordance with the EORTC manual [13], total scores are then transformed to a 0–100 scale with higher scores representing more severe fatigue. As no generally agreed definition of CRF exists, we constructed one based on the National Comprehensive Cancer Network (NCCN) guidelines and the data from which these were derived [14]. On a 0–10 scale: 1–3 was termed mild; 4–6 as moderate; and 7–10 as severe fatigue. The NCCN recommended a cut-off of 4 or greater as indicating fatigue worthy of further clinical attention [15]. Following this guidance we used a cut-off score of 40 or greater on the 100-point EORTC fatigue subscale to define CRF (also previously suggested by other authors [16]).

Emotional distress was measured using the Hospital Anxiety and Depression Scale (HADS) [17]. This comprises 14 items that refer to the previous week. Each item can be answered on a four-point scale (0–3) resulting in a maximum score of 42 with higher scores indicating more severe distress. Clinically significant emotional distress was defined as a total score of ≥15 [18]. HADS question 8, ‘I feel as if I am slowed down’ may be construed as referring to fatigue, so analyses of associations were repeated with it excluded. This approach has been used by other authors [19].

Patients’ demographic and clinical data including cancer diagnosis, extent of disease and treatment received were available from a clinical database. These variables were categorized as follows:

(1) primary cancer diagnosis, classified according to the site of origin (if patients had more than one primary cancer they were categorized according to the one that was dominating treatment, or the most recent if disease-free);
(2) disease extent, described according to the clinically detectable cancer at the time: disease-free or disease present (local disease or metastatic);
(3) cancer treatment status within the previous two months, categorized as: no prescribed treatment (included a small number of patients who had had surgery), hormone treatment, chemotherapy and/or radiotherapy (for details see Appendix).

analysis
Self-report and clinical data were linked by a unique patient identification number and date of birth. Data were available on 2867 outpatients, representing 84% of those eligible (see Figure 1). To assess whether our data were representative of our eligible population, we first compared the characteristics of patients on whom we had fatigue data to those on whom we did not, using chi-squared and Mann Whitney tests. Fatigue was described as mean and median scores and the prevalence of CRF (with 95% confidence intervals as denoted by 95% CI) was calculated. Associations of CRF with age, gender, primary cancer site, disease extent, treatment status and emotional distress were then examined in a univariate logistic regression analysis. Wald chi-squared tests, odds ratios and 95% confidence intervals were calculated for each variable (bowel cancer was chosen as the reference cancer site because it affects both males and females). A P-value of <0.05 was considered statistically significant. Multivariate logistic regression, using the method of stepwise selection, was subsequently applied to significant variables to identify the independent associations with CRF. This was first done using clinical and demographic variables that would routinely be available to outpatient clinicians, then repeated to include emotional distress scores to assess whether independent associations changed if these were also known.


Figure 1
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  		Figure 1. Derivation of patient sample.

 

   results
Top
 Abstract
 introduction
 patients and methods
 results
discussion
 appendix: cancer and treatment...
 Acknowledgements
 References
 
Demographic and cancer characteristics of this sample, and for patients without fatigue data, are shown in Table 2. There were modest but statistically significant differences on all variables measured, mainly reflecting missing screening data from very ill patients.


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  		Table 2 Characteristics of eligible patients with and without fatigue data

 
The mean age of the sample was 60 years and the majority were female. Breast cancer was the largest single cancer group. The majority of patients were disease-free and attending for post treatment follow-up.

fatigue scores and prevalence of CRF
The distribution of the fatigue scores for the whole sample was skewed toward less fatigue (see Figure 2). The median was 33 (inter-quartile range 11–44) and the estimated prevalence of CRF was 32% (926/2867; 95% CI 31–34%). The prevalence of CRF varied between cancer diagnoses, being highest in breast, ovarian and in the miscellaneous group (see Table 3). Further examination of fatigue subcategories showed 15% (n = 437) had no fatigue, 52% (n = 1504) had mild fatigue, 24% (n = 679) had moderate fatigue and 9% (n = 247) had severe fatigue.


Figure 2
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  		Figure 2. Distribution of fatigue subscale scores.

 

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  		Table 3 Univariate and multivariate analysis of CRF associations

 
univariate associations between CRF, demographic and clinical variables
Univariate analysis revealed that the risk factors for CRF were primary cancer site, being female, having disease present and having radio/chemotherapy or hormone treatment. Age (over or less than 65) was not associated with CRF. Emotional distress was strongly associated with CRF and this remained the case when HADS question 8 (‘feel slowed down’) was removed (see Table 3).

In order to further explore the degree of association between CRF and emotional distress, we examined the amount of overlap between them. Of the patients who were emotionally distressed, the majority (430/621, 69%) also had CRF, whereas for those who had CRF, more than half (495/925, 54%) did not fulfil the criteria for emotional distress indicating a lack of equivalence between CRF and emotional distress.

multivariate associations with CRF
Multivariate logistic regression of demographic and clinical variables that would be routinely available to any clinician in the outpatient clinic setting (age, gender, primary cancer site, disease extent and treatment status) revealed that primary cancer site, having disease present and type of cancer treatment were independently associated with CRF (see Table 3). Age over 65 and gender were no longer significant factors once these variables were accounted for.

In some centres, additional information about emotional distress is also available to clinicians. When this was added to the model the same three clinical variables remained but emotional distress had a much stronger independent association (odds ratio 8.05). This remained the case even when the HADS question 8 was removed (odds ratio 6.57, 95% CI 5.25–8.22).


   discussion
Top
 Abstract
 introduction
 patients and methods
 results
 discussion
appendix: cancer and treatment...
 Acknowledgements
 References
 
The main finding of this study was that one-third of outpatients with a variety of cancer diagnoses were identified as having fatigue of a severity that was considered clinically relevant. As expected, the strongest association of CRF was with emotional distress but more than half of those who had CRF did not have emotional distress.

These findings must be set in the context of methodological limitations: First, there may have been sampling bias as data was missing on patients too sick to complete the questionnaire and not all clinics were included in our sample. For example, haematological, head and neck and lung cancer have been reported to be associated with fatigue [4, 9, 20, 21] and were not included. Second, we used only one of the many available measures of fatigue, although none of these are clearly superior [22]. Nonetheless it is brief, widely used and the application of a cut-off score allowed a prevalence estimate of cases that may require clinical attention and not just the average level of fatigue in the sample. Third, the threshold we used for CRF, although based on published recommendations [15], remains essentially arbitrary and has not been validated, for example, by association with severity of functional impairment such as ability to work. Fourth, we were not able to account for co-morbid illnesses that may have contributed to fatigue such as thyroid disease or transient infection.

Whilst methodological issues make comparison with other studies difficult, the 32% prevalence of CRF we obtained is lower than some other estimates (see Table 1). Possible reasons for this are:

(1) a higher threshold for defining CRF;
(2) an outpatients sample, whereas other studies also included inpatients;
(3) a large proportion of disease-free patients not currently receiving intensive cancer treatment (although approximately a quarter of disease free patients had CRF).
Only two previous studies of mixed cancer samples have examined associations with demographic and cancer-specific factors, as well as with emotional distress: one was restricted to radiotherapy patients [11] and the other did not formally analyse associations with different cancer diagnoses or treatment [4].

This study is therefore the first large enough to: (1) accurately estimate the prevalence of CRF in outpatients with a wide variety of cancer diagnoses and (2) determine the associations of CRF with primary cancer diagnosis, disease extent, type of treatment, demographic factors and emotional distress. It is also the first study to focus specifically on cancer outpatients which constitute the majority of clinician patient contacts.

In summary, this large study of mixed cancer outpatients attending a regional cancer centre has highlighted the high prevalence of CRF and identified risk factors. The finding that a third of cancer outpatients have CRF, emphasizes that this problem merits further attention. Clinicians should especially pay attention to those who have the risk factors we have identified. We also urgently need better evidence-based strategies for treating fatigue in patients with cancer.


   appendix: cancer and treatment status classifications
Top
 Abstract
 introduction
 patients and methods
 results
 discussion
 appendix: cancer and treatment...
Acknowledgements
 References
 
primary cancer at the time of screening
Due to the small numbers of patients in some categories, the primary cancer diagnoses were grouped into seven major categories: breast, testicular, ovarian, prostate, bowel (included rectal, colon and anal sites of origin), other gynaecological (included cervical, uterine, vulva and vaginal sites of origin) and miscellaneous (included lymphoma, head and neck, lung, upper gastrointestinal, melanoma, brain/central nervous system, kidney, adrenal gland, bladder, epididymis, sarcoma, primary peritoneal, basal cell and unknown primary cancers). For the majority of patients, their primary cancer diagnosis was classified according to the site of origin. The only exceptions were:

  • Melanoma. This was classified as melanoma regardless of the site of origin.
  • Germ cell tumour in regions other than the gonads (e.g. mediastinal) was classified in men as testicular and in women as ovarian cancer.

Those patients who had had more than one primary cancer diagnosis were classified according to the cancer they were being treated for at the time of screening. If they were being treated for more than one malignancy concurrently, they were classified according to the cancer diagnosis that was dominating their treatment at the time of screening. Those patients who were disease free and on no treatment for any of their previous cancers were classified according to their most recently diagnosed cancer.

disease extent at time of screening
Patients were classified according to their clinically detectable disease extent at the time of screening. The categories were disease-free, disease present or unknown. Some clinical situations could be classified in more than one way. For clarity these are outlined under the appropriate section.

disease-free

  • Undergoing post-surgical adjuvant radiotherapy/chemotherapy/hormone therapy with no clinically detectable residual disease.
  • After completion of primary radical chemotherapy or radiotherapy given with curative intent and no documented residual disease or recurrence (i.e. early anal cancer after radical chemoradiation and stage 3 ovarian cancer after chemotherapy with normal serum tumour markers).
  • Metastatic cancer that had been surgically removed and no documentation of recurrence (e.g. liver metastases from bowel cancer which were removed after chemotherapy and partial hepatectomy).

disease present (local and metastatic disease categories combined)
local disease

  • Clinically detectable local disease or regional lymph node metastases.
  • Undergoing primary chemotherapy or radiotherapy with curative intent, e.g. early anal cancer.
  • Undergoing neo-adjuvant chemotherapy/radiotherapy/hormone treatment prior to surgery (unless metastatic disease).

metastatic

  • Metastases to organs or distant lymph nodes.
  • Stage 3 ovarian cancer undergoing primary or post-surgical chemotherapy at the time of screening (because it is assumed there is residual disease in the abdominal cavity).
  • Relapsed ovarian cancer.
  • Primary lung cancer with disease in more than one lobe of lung and not treated with curative intent.
  • Breast cancer with supra-clavicular nodes.

unknown
When it was not clear what the cancer status was at the time of screening.

type of cancer treatment at the time of screening
The type of cancer treatment was described according to what treatment had been received within the two months prior to screening: no prescribed treatment, hormone treatment, chemotherapy, radiotherapy, surgery or any combination of these (though this does not automatically imply that they were concurrent). These were collapsed into the three groups presented in the paper:

(1) no prescribed treatment (which included those who had had surgery);
(2) hormone treatment; and
(3) chemotherapy and/or radiotherapy treatment.

Those who had received two treatment modalities within the last two months were allotted to the most clinically dominant category according to the following ranking: chemo/radiotherapy > hormones > surgery, e.g. those who had received both surgery and chemotherapy were assigned to the chemotherapy and/or radiotherapy treatment group.

No distinction was made between the dose and fractionation of radiotherapy administered; patients were classed as undergoing radiotherapy provided at least one fraction of treatment had been administered within the previous two calendar months.

The arbitrary two-month cut-off was made on the basis that patients’ symptoms might still be affected by treatment such as chemotherapy, completed several weeks prior to screening. The authors recognize that possible treatment associated symptoms may resolve before or after this time or be affected by treatments administered more than two months previously.


   Acknowledgements
Top
 Abstract
 introduction
 patients and methods
 results
 discussion
 appendix: cancer and treatment...
 Acknowledgements
References
 
Funding: Cancer Research UK. Thanks to: Elspeth Currie; Helen Swanson, Sarah Humble, Jackie Whigham, Ian MacDonald and Joerg Sigle for their help with data collection; Gordon Murray for statistical advice and Peter Fayers for his comments regarding the analysis of the EORTC QLQc30 fatigue subscale

Received for publication February 6, 2007. Revision received June 8, 2007. Accepted for publication June 8, 2007.


   References
Top
 Abstract
 introduction
 patients and methods
 results
 discussion
 appendix: cancer and treatment...
 Acknowledgements
 References
 
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