FATIGUE IN GYNAECOLOGICAL CANCER PATIENTS DURING AND
AFTER ANTI-CANCER TREATMENT
Gillian Prue, PhD1,2 James Allen, PhD2 Jacqueline Gracey, PhD2 Jane Rankin, MSc3
Fiona Cramp, PhD4
1. Institute of Nursing Research, University of Ulster, Newtownabbey, Co. Antrim, BT37
0QB, UK
2. Health and Rehabilitation Sciences Research Institute, University of Ulster,
Newtownabbey, Co. Antrim, BT37 0QB, UK
3. Northern Ireland Cancer Centre, Belfast Health and Social Care Trust, Belfast, BT9
7AB, UK
4. Department of Allied Health Professions, Faculty of Health and Life Sciences,
University of the West of England, Blackberry Hill, Bristol, BS16 1DD, UK
Corresponding Author: Dr. Gillian Prue, Institute of Nursing Research, University of
Ulster, Shore Road, Newtownabbey, Co. Antrim, BT37 0QB, United Kingdom.
Fax: +44 (0)28 9036 8202 Tel: +44 (0)28 9036 8542
Email: ge.prue@ulster.ac.uk
Abstract
Context: Research has indicated that individuals with gynaecological cancer experience
severe fatigue.
Objectives. This longitudinal survey aimed to analyse the fatigue experienced over 12
months by a gynaecological cancer population, to determine if the fatigue was more
severe than that reported by females without cancer and to identify variables associated
with cancer related fatigue (CRF).
Methods. Data were collected over a 12 month period before, during and after anticancer treatment. Fatigue was assessed using the Multidimensional Fatigue Symptom
Inventory-Short Form. Participants with cancer also completed the Rotterdam Symptom
Checklist.
Results. Sixty-five cancer patients (mean age = 57.4, SD 13.9) and 60 control subjects
(mean age 55.4, SD 13.6) participated. Descriptive analysis and Repeated Measurements
Modeling (RMM) indicated that the cancer participants reported worse fatigue than the
non-cancer individuals before, during and after anti-cancer treatment (p < 0.001) and that
the level of fatigue in persons with cancer changed with time (p = 0.02). A forward
stepwise regression demonstrated that psychological distress level was the only
independent predictor of CRF during anti-cancer treatment (p < 0.00), explaining 44% of
the variance in fatigue. After treatment, both psychological distress level (p < 0.00) and
physical symptom distress (p = 0.03) were independent predictors of fatigue, accounting
for 81% of the variance.
Conclusion. Psychological distress level is an important indicator of CRF in
gynaecological cancer. Interventions focused on the reduction of psychological distress
may help alleviate CRF.
Keywords: fatigue; neoplasm; gynaecological; symptoms; adult.
Running title: Fatigue in gynaecological cancer
2
Introduction
Cancer-related fatigue (CRF) is an almost universal symptom in patients receiving anticancer therapy (1). CRF can have a phenomenal impact on a patient’s life (2) and can
hinder the chance of remission or even cure, owing to the direct influence it can have on
the individuals desire to continue with treatment (3). Research has indicated that
individuals with gynaecological cancer experience more severe fatigue than those with
other cancer diagnoses (4). In a UK multi-centre survey of 576 cancer patients with
varying diagnoses, half of which were currently receiving anti-cancer treatment, over
50% reported fatigue as their biggest problem. (5). Furthermore, a pilot study indicated
that fatigue is a significant problem for females with gynaecological cancer at various
stages of their disease and treatment process (6). It was therefore deemed appropriate and
necessary to further examine fatigue in gynaecological cancer.
A number of methodological limitations have been highlighted in the research to date (79). Three main problems have been emphasized, firstly, there is a degree of uncertainty
surrounding the best approach for CRF assessment, thus a variety of self-report measures
exist. Many of these measures are single item, which are therefore inadequate to measure
fatigue, a multidimensional construct. The most appropriate and valid approach would be
to use a multidimensional measure (8). Secondly, a number of investigations are crosssectional in design which has restricted the conclusions that can be drawn with regard to
fatigue as an ongoing symptom. A more methodologically sound approach is to
undertake a longitudinal survey, to enable fatigue to be charted accurately over time.
3
Fatigue is also a common complaint among the general population which must be taken
into consideration when reporting the prevalence of symptoms among cancer patients (9).
Theoretical Framework
The fatigue model used as the conceptual framework for the study was the Winningham
Psychobiological-Entropy Model (PEM). The PEM describes fatigue as an ‘energy
deficit’ and suggests variables which could contribute to the development and persistence
of the condition (10). This model correlates fatigue, the disease, any anti-neoplastic
treatment, any other symptoms, activity and functional status (11). The model suggests
that fatigue is not only a primary symptom of cancer but it can also occur as a secondary
symptom as a result of the individual’s response to other symptoms, including
psychological symptoms (12). For this study, the PEM was used to identify the
appropriate variables to be examined and measured, specifically fatigue, symptom
experience, activity level and tumour and treatment related variables such as tumour site
and stage and treatment received.
Aims
The study aimed to answer three questions. Firstly, do individuals with gynaecological
cancer experience a more severe fatigue than matched non-cancer volunteers? Secondly,
does the profile of fatigue in gynaecological cancer change over time, and if so in what
way? Finally, which variables (as identified by the PEM) are associated with CRF before,
during and after anti-cancer treatment and which are associated with more severe fatigue
in gynaecological cancer?
4
Methods
A multiple point prospective longitudinal survey was implemented involving
gynaecological cancer patients from the Belfast City Hospital (BCH), Southampton
General Hospital (SGH) and United Bristol Healthcare Trust (UBHT). Ethical approval
was obtained from the Central Office of Research Ethics Committees (COREC) (January
2005). The cancer participants were identified and recruited, via their consultant, at an
outpatient review appointment at either the chemotherapy clinic or radiotherapy planning
clinic before they commenced anti-cancer treatment. The non-probability sampling
technique of consecutive convenience sampling was used; hence every available
individual with a diagnosis of gynaecological cancer attending the BCH, SGH and UBHT
that met the inclusion criteria was approached. This has been described as the best
approach for non-random sampling (13).
The study sample included cancer subjects who were newly diagnosed with any
gynaecological cancer having no treatment except surgery for their disease to date, and
with no previous diagnosis of cancer. They had to be fully informed of their diagnosis, be
18 years or older, be English speaking and have provided informed consent. Individuals
attending a clinical psychologist or psychiatrist, with cognitive impairment or
incompetence, with a chronic disease in which fatigue was a prominent symptom or those
with a serious underlying medical condition were excluded. Written informed consent
was obtained from each participant upon enrolment. Cancer subjects completed three
questionnaires which collected data on (1) fatigue (2) symptom experience and activity
level and (3) demographics and disease-related information.
5
(1) Fatigue
The fatigue questionnaire used for the study was the Multidimensional Fatigue Symptom
Inventory-Short Form (MFSI-SF). The 30 item MFSI-SF has five subscales: general
(GF), physical (PF), emotional (EF) and mental fatigue (MF) and vigor (V). The
respondent indicates the extent to which they have experienced each symptom during the
preceding week (0 = not at all; 4 = extremely) (14). Ratings are summed to obtain scores
for each of the subscales detailed previously. In addition, a total fatigue (TF) score can be
generated by summing the four fatigue subscales and subtracting the vigor subscale (14).
(2) Symptom experience and activity level
The Rotterdam Symptom Checklist (RSCL) was used to provide a measure of other
symptoms experienced and activity level. This is a 30 item cancer-specific tool which
assesses four domains: physical symptom distress, psychological distress, overall
valuation of life and activity level over the past week on a five point Likert scale (15).
According to the PEM, activity level is important variable in the development and
persistence of CRF, thus it was considered to be an essential factor to measure in the
longitudinal survey. For that reason the RSCL was chosen as it provides an indication of
not only symptom experience, but also activity level. Its use would reduce participant
burden by minimising the number of questionnaires to be used in the longitudinal survey.
Despite assessing a number of domains the RSCL takes only eight minutes to complete
(15) and therefore it was anticipated that its completion would not prove too burdensome
for participants.
6
(3) Demographics and disease/treatment-related information
Information on age, marital status, number of dependents, employment status and normal
activity levels was obtained. Relevant medical data such as tumour site and stage, and
information on anti-cancer treatment received were obtained from medical records.
Data were collected over a twelve-month period. This commenced following surgical
management if indicated, prior to the initiation of any anti-neoplastic treatment. A
baseline point post surgery was decided upon following a feasibility study, where it
became apparent that an attempt to recruit patients prior to surgery would be fruitless, as
patients at this time were either unaware of their diagnosis, or not emotionally fit to
undertake such a study. During the treatment phase, it was unknown exactly how the
participants’ fatigue would behave. As the chemotherapy cycles were administered either
weekly or every three weeks and radiotherapy lasted approximately five – six weeks, it
was felt most appropriate to invite participants to complete the MFSI-SF weekly based on
each participants own weekly treatment schedule. It was expected that some cancer
participants would receive treatment for a period of up to six months, and it was felt to be
unrealistic to expect the subjects to complete the MFSI-SF every week for this time
period. Therefore a cut off point of twelve weeks was decided upon for weekly
questionnaire completion. Once a participant had completed treatment or reached the
twelve-week cut off point, they moved on to monthly completion of the MFSI-SF until
the twelve-month endpoint. The RSCL was completed by the cancer participants on a
monthly basis for the twelve months. The RSCL was completed monthly and not weekly
7
as it was felt that weekly completion of the RSCL in addition to the MFSI-SF would be
too burdensome for a fatigued individual.
Data for comparison purposes were collected from a group of age matched females, with
no history of cancer. Participants in the non-cancer group were recruited via a peer
nomination process (16,17). This process was chosen as it has been demonstrated in the
literature to be a successful method of recruiting a group of healthy volunteers that are
similar demographically to the cancer participants (17,18,19). The process involved the
cancer subject nominating a suitable friend or relative, that was not their primary carer, to
participate (16,17). Once nominated, and informed of the study by the person with
cancer, the potential recruit was contacted via telephone to obtain consent to participate.
When the cancer subject could not nominate a suitable match within one month of their
own recruitment, a control was assigned to them from a list of eligible volunteers created
before the commencement of the survey. This list was devised as a result of an email
circulated among University of Ulster staff requesting suitable volunteers. Friends and
family of the research team were also invited to participate. This was to ensure that a
diverse list, with respect to age and occupation was available. This approach has been
used in previous research and has been shown to be an adequate method of recruitment
(20,21). Included non-cancer females were 18 years or older and within 5 years of their
matched cancer subject. They had to be English speaking and have provided fully
informed written consent. The exclusion criteria were as for the cancer participants; in
addition the cancer participant’s primary carer was excluded.
8
The non-cancer comparison group was required to complete the initial demographic
questionnaire and the MFSI-SF. The fatigue questionnaire was completed on a monthly
basis for the twelve-month duration.
Any individual that did not wish to participate or withdrew was invited to score their
fatigue verbally on a Numerical Rating Scale (1 – 10) (NRS-F) as a one off record.
Statistical analysis
Data analysis was performed using the Statistical Package for the Social Sciences (SPSS)
Version 11 for Windows.
Repeated Measurements Modelling (RMM) was conducted to address the first two aims
of the study: to determine whether or not those with gynaecological cancer had more
severe fatigue than females with no history of cancer and to examine the change in
fatigue in those with gynaecological cancer with time. RMM computes estimated
marginal means (EMM) of the dependent variable which show the effect being studied
without the error, not the actual observed means (22). The RMM was chosen as it can be
used to describe the temporal changes of a dependent variable in a dataset with missing
data and it is capable of treating time as a categorical variable or a continuous variable
(23).
To address the final aim of the study to examine the variables associated with fatigue in
gynaecological cancer and identify those associated with more severe CRF, a forward
9
stepwise regression with fatigue as the dependent variable was conducted. Initially, a
univariate analysis was undertaken to identify the individual predictors of the dependent
variable. Independent variables included were tumour-related, treatment-related and
demographic. Those that were identified as significant were entered into a forward
stepwise regression with baseline TF as the dependent variable. Independent variables
were entered and removed until the independent variables that remained in the model
were all significant in the presence of each other.
This analysis was conducted three times using baseline TF, month 2 TF (during
treatment) and month 12 TF (end of follow up) as the dependent variables to determine if
the variables associated with CRF differed before, during and after anti-cancer treatment.
To detect selection bias a univariate analysis (t-test) was used to compare the difference
in NRS-F scores in those who agreed to participate and those who did not and for those
who withdrew and those who completed the study.
Results
Participants
Over the course of 12 months 92 individuals with gynaecological cancer were identified
as being eligible to participate. Twenty seven of the 92 declined involvement. There was
no significant difference in NRS-F scores for participants (Mean = 4.13, SD 2.49) and
non-participants (Mean = 3.44, SD 3.65; t = 0.886, p = 0.38). Over the same time frame,
sixty females with no history of cancer were recruited.
10
The demographic characteristics of the 65 participants with gynaecological cancer and
the sixty non-cancer females are summarised in Table 1. The mean age of the cancer
group was 57.4 years (SD 13.9), ranging from 23 – 86 years. The majority of cancer
participants were married (n = 35, 54%), not working (n = 57, 88%) with 28 (49%) citing
their cancer as their reason for not working, the majority of respondents had a low
activity level (n = 46, 71%). Regarding the non-cancer group, the mean age of this
cohort was 55.4 (SD 13.6), ranging from 24 – 86. The majority were married (n = 39,
65%), currently working (n = 38, 63%), and had a subjectively low activity level (n = 34,
57%). There was no significant difference in age (p = 0.43) or marital status (p = 0.26) of
those who had cancer and those who did not (p = 0.43).
Medical oncology data are summarized in Table 2. The most common malignancy was
ovarian cancer (n = 35, 54%), with most tumours being stage 1 (n = 27, 42%). The
sample was heterogeneous regarding antineoplastic treatment received. There was no
significant difference in fatigue between those who had undergone surgery prior to
baseline (Mean = 7.00, SD 15.81) and those who had not (Mean = 9.57, SD 19.97; t = 0.394, p = 0.70).
Completion rates
Of the 65 individuals with gynaecological cancer that agreed to participate, 15 withdrew
over the course of the twelve months. The most common reasons given were that they no
longer wished to participate as they had finished treatment (n = 5), and disease
progression (n = 7). A further 25 failed to complete the final 12 month questionnaire. Of
11
this 25, eight had died, six had disease progression and two had been admitted to hospital.
Consequently only 25 individuals completed the final questionnaire. A comparison of the
final NRS-F for those who completed the study, and the last available NRS-F for those
who dropped out indicated that there was no significant difference in NRS-F scores
between those who completed (Mean = 4.57, SD 2.12) and those who did not (Mean =
5.64, SD 2.41; t = -1.82, p = 0.07). Forty two of the sixty healthy volunteers completed
the study.
(1) Do individuals with cancer have a higher level of fatigue than non-cancer
females?
The monthly TF scores for the cancer and non-cancer participants are presented in Table
3. Descriptively, the scores for the non-cancer participants were much lower than those
reported by the individuals with gynaecological cancer, indicating the females with
gynaecological cancer suffered a higher level of fatigue. This was reflected statistically
through the RMM. The RMM concluded that there was a significant difference in GF,
PF, EF, MF, V and TF scores between those who had cancer and those who did not, those
with cancer had significantly higher fatigue (p < 0.001).
(2) How does fatigue in gynaecological cancer change with time.
The change in CRF over time is summarised in Figure 1. The level of GF and PF peaked
during treatment and returned to approximately baseline level by the twelve month
endpoint. The level of EF declined with time. The level of MF remained relatively stable.
TF peaked during treatment and gradually declined after anti-cancer treatment. The first
12
and last TF measurements were similar. The RMM validated this finding statistically.
With GF (p = 0.038) and PF (p < 0.00) time was significant as a factor, which indicated
that there were peaks and/or troughs in fatigue with time. Time was significant as a
covariate for EF and TF (p = 0.03; p = 0.02 respectively) which was indicative of a linear
downward trend, that is, an improvement in fatigue levels with time. The level of both
MF and V remained constant at all timepoints.
As a heterogeneous sample with regard to anti-cancer treatment was recruited, it was
possible to compare descriptively the impact of treatment received on the pattern of
fatigue during and after therapy. During chemotherapy TF peaked at the time of each
infusion (Figure 2a). However, during radiotherapy, there was a gradual increase in the
level of CRF with time (Figure 2b). After treatment, in both chemotherapy and
radiotherapy, a drop in the level of TF was noted.
(3) Which variables are associated with CRF before, during and after anti-cancer
treatment?
Before anti-cancer treatment
The independent variables included in the univariate analysis were: demographics,
disease and treatment-related variables, and indications of baseline psychological distress
level, baseline physical symptom distress level, baseline overall valuation of life and
baseline activity level as measured by the RSCL. Significant variables were subsequently
included in a forward stepwise regression with baseline TF as the dependent variable.
These were baseline psychological distress level (t = 7.83, p < 0.00), baseline overall
13
valuation of life (t = 6.62, p < 0.00), baseline physical symptom distress level (t = 8.15, p
< 0.00), and baseline activity level (t = 2.21, p = 0.03). Following the forward stepwise
regression baseline psychological distress level, baseline physical symptom distress level
and baseline overall valuation of life were revealed as the three independent predictors of
baseline TF, explaining 68% (adjusted r square) of the variance.
During anti-cancer treatment
The independent variables considered in the univariate analysis were: Baseline TF,
demographics, disease and treatment related variables and indications of month 2
psychological distress level, month 2 physical symptom distress level, month 2 overall
valuation of life and month 2 activity level as measured by the RSCL. The variables that
were significant and thus included in the forward stepwise regression were baseline
fatigue (t = 3.78, p < 0.00), month 2 psychological distress level (t = 6.19, p < 0.00),
month 2 overall valuation of life (t = 3.26, p < 0.00), month 2 physical symptom distress
level (t = 3.30, p < 0.00), and month 2 activity level (t = 2.08, p = 0.04). Following the
forward stepwise regression month 2 psychological distress level as measured by the
RSCL was the only independent predictor of month 2 TF, explaining 44% (adjusted r
square) of the variance.
After anti-cancer treatment
The independent variables considered in the univariate analysis were: Baseline TF,
demographics, disease and treatment related variables and indications of month 12
psychological distress level, month 12 physical symptom distress level, month 12 overall
14
valuation of life and month 12 activity level as measured by the RSCL. The variables
entered into the forward stepwise regression were baseline TF (t = 3.24, p < 0.00), month
12 psychological distress level (t = 8.33, p < 0.00), month 12 overall valuation of life (t =
4.20, p < 0.00) and month 12 physical symptom distress level (t = 6.17, p < 0.00).
Following the forward stepwise regression month 12 psychological distress level and
month 12 physical symptom distress level were the independent predictors of month 12
TF, explaining 81% (adjusted r square) of the variance.
Discussion
A longitudinal survey accumulating fatigue data from a group of newly diagnosed
gynaecological cancer patients before, during and after anti-cancer treatment was
conducted. The methodology permitted the investigation of the pattern of fatigue both
during and after treatment and facilitated this level of fatigue to be compared to that
reported by females with no history of cancer. Without this comparison it would be
unknown what proportion of the fatigue experienced by the individuals with cancer was a
result of having cancer and receiving cancer treatment.
(1) Do individuals with cancer have a higher level of fatigue than non-cancer
females?
The gynaecological cancer participants included in the study had more severe fatigue
than the non-cancer females before, during and after anti-cancer treatment.
These
findings are reflected in the CRF literature (19,24-30). The raised baseline fatigue could
be attributed to undergoing surgery (19), however, in this sample, there was no
significant difference in the level of fatigue reported by those who had undergone surgery
15
and those who had not. The increase in baseline fatigue could be due to the effects of the
tumour itself and the psychological impact of receiving a cancer diagnosis (19). To
investigate this issue further, it would be useful to assess fatigue levels before surgery.
However, as demonstrated in an earlier pilot study, it is difficult to obtain fatigue scores
at this stage, as the individual may not be emotionally fit to participate and may be
unaware of their diagnosis (6).
(2) How does fatigue in gynaecological cancer change with time.
Banthia and colleagues (2006) recommended that it was important to identify which
dimensions of CRF were problematic and more sensitive to change over time in order to
effectively guide treatment interventions (31). In this survey, the level of general and
physical fatigue reported by the cancer participants changed over the course of the 12
months, and was highest during anti-cancer treatment. In comparison, the MF subscale
remained at a constant level over the course of the 12 months. The different profiles of
the MFSI-SF subscales over time underscores the importance of measuring the different
dimensions of fatigue, as it would appear that each dimension behaves differently over
time. A number of studies have reported that CRF increases significantly during
treatment (24,32-39), but this is not verified by all investigations (40-42). This
inconsistency could be the result of methodological flaws, such as fatigue not being
assessed frequently enough to detect fluctuations.
16
(3) Which variables are associated with CRF before, during and after treatment?
Before commencement of anti-cancer treatment, the regression analysis suggested that
surgery and tumour related variables such as tumour site and stage were not related to
fatigue. Increased psychological distress level was associated with raised baseline fatigue,
which is likely to be a result of receiving a diagnosis of cancer and feeling anxious about
starting anti-cancer treatment. Reduced quality of life and a raised physical symptom
distress level were also related to fatigue, indicating that suffering other symptoms leads
to an increase in fatigue. During treatment, psychological distress level was the sole
independent predictor of CRF. A strong relationship has been noted in the literature
between CRF during treatment and anxiety and depression (5,9,16,24,37,38,42-55). In
this longitudinal survey demographic variables and factors associated with the tumour
and anti-cancer treatment were unrelated to the fatigue. A large body of evidence exists
to support the finding that CRF during anti-cancer treatment is not associated with
tumour
stage
(16,17,32,34,39,44,48,56-58)
(16,17,24,32,37,43,44,48,50,52,54-59)
or
or
treatment-related
any
demographic
variables
(16-
18,32,34,39,42,43,48,52,56-59). After treatment, psychological distress level was again
an independent predictor of fatigue as was physical symptom distress level. Tumour and
treatment related variables were not associated with the persistence of fatigue after anticancer therapy. Previous research has also indicated strong relationships between anxiety
and depression and CRF in cancer survivors (20,24,26,27,29,60-74). In agreement with
the current findings the majority of previous research has found no relationship between
diagnosis and fatigue (19,20,29,30,60-72,75-77). Studies investigating CRF in survivors
of cancer have also reported no association between treatment related variables and
17
fatigue (19,26-30,60-66,69-72,74,76-79) which concurs with the current findings. These
findings, in conjunction with the outcome of this longitudinal survey, leads to the
conclusion that in cancer survivors, psychological factors are related to CRF whereas
tumour and type of treatment are not.
Psychological distress level was an independent predictor of fatigue before, during and
after anti-cancer treatment. Throughout this survey, fatigue has been demonstrated as a
symptom of cancer, but it is also reported to be a symptom of depressive disorders (80).
The symptoms associated with fatigue are similar to the symptoms reported by
individuals with depression (81). As a result of this some items included in an assessment
scale for CRF, would be incorporated into an assessment scale for psychological
impairment. It would be acceptable to assume some level of correlation between the two
phenomena, and thus they would appear related in a regression analysis. A relationship
between depression and fatigue has frequently been reported. However, there is evidence
that CRF may increase during treatment with no concurrent increase in anxiety and
depression (44,82). Furthermore Jacobsen et al (80) reported a correlation between
fatigue and depression that remained even when items included in both assessment scales
were removed. This indicated that a relationship might exist that was not due to the
overlap in the two assessment scales (80). The causal relationship between the two
phenomena remains to be determined. In an attempt to combat the overlap in
measurement, a clinical syndrome approach has been suggested as a more appropriate
method of assessing CRF (80,81).
18
Limitations
The problem of attrition affected the study as only 25 of the original 65 cancer
participants completed the final assessment. However, the comparison of the fatigue
levels, as measured by the NRS-F, of those who completed the study and those who
dropped out demonstrated that there was no difference in the level of fatigue between the
two at the time of withdrawal. It cannot however be presumed that the level of fatigue
reported by those who withdrew stayed at a similar level as those who completed the
study. Every attempt was made to minimise the attrition rate, however due to the nature
of the disease and the severity of treatment, drop-outs, as in many studies, were inevitable
(83).
Not all cancer participants had a matched control, largely due to the fact that they were
elderly participants, and it was difficult to source a match that met the inclusion/exclusion
criteria. However, the fact that over 90% of cancer participants were matched would
indicate that the results are more than likely the true outcome.
The data on CRF was only recorded up to 12 months from baseline. It is therefore
unknown how long CRF persists for in survivors of gynaecological cancer. Future
research should focus on investigating this fatigue persistence.
Although the change in MFSI-SF scores over time was statistically significant, the
increase in fatigue may not have been substantial enough to have a negative impact on
quality of life. Including the non-cancer group of females provided an indication that the
19
fatigue was worse than the ‘norm’, but a more suitable method for determining clinical
significance is the use of Minimal Clinically Important Differences (MCIDs) (84).
Unfortunately there are currently no MCIDs available for the MFSI-SF. The National
Comprehensive Cancer Network (NCCN) recommendations for the management of CRF
suggest that anyone scoring 4 or more on an NRS should have their fatigue investigated
further (1). In this survey, the overall mean NRS score for the all of the cancer
participants was 4.6. This would suggest that the majority of gynaecological cancer
patients in this study had fatigue that was severe enough to warrant further investigation.
Implications for practice
This study suggests that all females with a diagnosis of gynaecological cancer, regardless
of their tumour site, tumour stage or treatment regime should be informed that they may
experience CRF during their treatment and that it may persist for many months once their
treatment is complete (85). This would enable the individual to provide fully informed
consent to treatments such as chemotherapy. Research has also suggested that if an
individual is told what to expect, they are not as likely to experience the stress of
unexpected problems (86).
To fulfill the National Institute of Health and Clinical Excellence (NICE)
recommendations that all patients should be offered optimal symptom control should they
require it (87), individuals with gynaecological cancer should be screened for high
fatigue levels before commencement of anti-cancer treatment. This screening should
become a routine part of each clinical visit for the duration of the anti-cancer treatment,
20
and continue at regular intervals once treatment is complete. Frequent assessment at each
clinical visit will help to ensure that appropriate interventions are made available to the
patient as soon as they require them.
The outcomes of this longitudinal survey demonstrate that the various dimensions of CRF
behave differently. This confirms that the ideal approach for the measurement of CRF is
with a multidimensional assessment tool. Clinically however it is acknowledged that due
to time restrictions it may not be possible for each individual to complete a lengthy
multidimensional fatigue questionnaire. Where this is not achievable, it is suggested that
individuals are screened with a single item scale such as a NRS-F, to identify those that
require more complete CRF assessment. The subsequent in depth assessment with those
persons who have shown to be suffering from a raised level of fatigue, should measure all
the dimensions of CRF with a multidimensional assessment tool. This comprehensive
assessment should identify the source of the fatigue thereby ensuring it is managed
appropriately. This recommendation has been discussed further by the NCCN (1).
The apparent association between fatigue in individuals with gynaecological cancer and
psychological distress would indicate that managing actual and potential psychological
distress may pre-empt a degree of fatigue. A number of pharmacological and nonpharmacological approaches aimed at alleviating psychological distress have been
discussed in the literature. Pharmacological interventions such as anti-depressants have
been used for fatigue that is related to depression, but there is currently minimal research
evidence to support their use (88,89). Non-pharmacological interventions for example,
21
exercise, support groups, psychotherapy, relaxation therapy, cognitive behavioural
therapy and distraction techniques such as reading and listening to music have also been
investigated and shown to be beneficial (89-92). A recent Cochrane review however
concluded that there was limited evidence that psychosocial interventions are effective in
reducing fatigue (93).
Conclusions
Fatigue is a problem for gynaecological cancer patients both during and after anti-cancer
treatment. Fatigue should therefore be assessed before (to establish baseline fatigue
levels), during, and after anti-cancer treatment, and routinely following end of treatment.
From this longitudinal survey it would appear that tumour and treatment related variables
are not associated with CRF in gynaecological cancer. Individuals with gynaecological
cancer should be reassured that the experience of severe fatigue is not indicative of
disease progression (1). They should be offered education regarding effective fatigue
management, for example energy conservation techniques such as delegation, pacing and
prioritising, as recommended by the NCCN (1).
The strong association presented
between CRF and psychological distress in gynaecological cancer is an important finding
and indicates that interventions focused on the amelioration of psychological distress may
reduce the perception of CRF in this patient population. Future research should focus on
the investigation of the optimum management strategy for CRF in gynaecological cancer.
Acknowledgements:
Statistical advice was provided by Dr Ian Bradbury.
22
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30
Table 1
Cancer and non-cancer participant demographics
Cancer
N
65
Non-cancer
N
60
57.38 (13.85)
55.41 (13.60)
Married
Living with partner
Single
Divorced
Widowed
Unknown
35
1
13
2
12
2
39
3
3
4
9
2
Working
Not working
Unknown
6
57
2
38
20
2
Due to illness
Not due to illness
Unknown
28
28
2
-
Low
Moderate
High
Unknown
Have activity levels changed since
diagnosis?
Increased
Decreased
Stayed the same
Unknown
46
11
2
4*
34
13
4
3**
4
50
8
1*
-
Total number of participants
Age
Mean (SD)
Marital Status
Employment status
Reason for not working
Activity level
* Totals 63 as two participants did not consider themselves to be an active person
** Does not total 60 as six participants did not consider themselves to be an active person
31
Table 2
Gynaecological cancer oncology data (n = 65)
N
65
Total number of participants
Tumour type
Ovarian
Endometrial
Cervix
Uterus
Ovarian and Uterine
Endometrial and Ovarian
Vulva
Fallopian Tube
35
16
7
1
1
3
1
1
1
2
3
4
Unknown
27
10
18
4
6
Yes
No
Unknown
56
8
1
Chemotherapy
Radiotherapy
Chemotherapy, radiotherapy
Surgery, chemotherapy
Surgery, radiotherapy
Surgery, chemotherapy, radiotherapy
Chemotherapy Regime
Taxol/Carboplatin
Carboplatin
Carbocockcroft
Cisplatin/5FU
CFU
Weekly Cisplatin (short course of chemo)
Unknown
5
1
3
34
16
6
Tumour Stage
Did patient have surgery?
Treatment
28
9
2
1
2
4
2
32
Table 2
Gynaecological cancer oncology data (cont.)
N
Number of chemotherapy cycles
1
2
4
5
6
Unknown
1
2
2
2
40
1
45gy;23fr
50.4gy;28fr
45gy;25fr
60gy;33fr
Unknown
5
3
15
1
2
3 weeks
4.5 weeks
5 weeks
5.5 weeks
6 weeks
6.5 weeks
1
2
13
2
7
1
Radiotherapy Dose
Duration of radiotherapy
33
Table 3
Cancer and non-cancer participants’ monthly TF scores
Baseline
Month 1
Month 2
Month 3
Month 4
Month 5
Month 6
Month 7
Month 8
Month 9
Month 10
Month 11
Cancer
TF mean (SD)
7.30 (16.03)
16.91 (22.40)
15.89 (23.62)
14.85 (21.77)
12.34 (24.94)
10.60 (22.67)
7.79 (17.58)
8.03 (19.55)
7.26 (19.29)
5.70 (19.55)
2.96 (17.74)
6.52 (19.09)
Non-cancer
TF mean (SD)
-1.21 (10.69)
0.44 (13.97)
-0.63 (13.09)
-0.17 (13.78)
0.13 (14.06)
0.65 (15.36)
-0.58 (14.51)
-3.04 (12.14)
-2.06 (13.75)
0.12 (16.05)
-0.63 (14.33)
0.19 (13.64)
34
Figure 1
Monthly fatigue scores for cancer participants
18
16
14
Mean Score
12
GF
PF
10
EF
8
MF
TF
6
4
2
0
0
1
2
3
4
5
6
7
8
9
10
11
Time (Months)
35
Figure 2a
Mean weekly TF scores during the first three cycles of chemotherapy
25
Mean Score
20
15
TF
10
5
0
0
1
2
3
4
5
6
7
8
9
10
11
12
During (w eekly)
Figure 2b
Mean TF score during and after radiotherapy
16
14
Mean Score
12
10
8
TF
6
4
2
0
0
1
2
3
4
During (w eekly)
5
1
2
3
4
5
6
7
8
After (m onthly)
36