Research Article
Fatigue, Physical Symptoms, Psychological Distress, and Use of
Integrative Medicine in Patients With Advanced Cancer
Caterina Calderon ,1 M. Mar Muñoz-Sa´nchez ,2 Jesu´s Peña-Lo´pez ,3
M. Helena Lo´pez-Ceballos ,4 Ana Ferna´ndez-Montes ,5 Elena Asensio-Martinez ,6
Rau´l Carrillo-Vicente ,7 Marina Gustems ,1 and Paula Jimenez-Fonseca 8
1Faculty of Psychology, University of Barcelona, Barcelona, Catalonia, Spain
2Department of Oncology, Hospital Virgen de la Luz, Cuenca, Castile-La Mancha, Spain
3Department of Oncology, Hospital Universitario La Paz Hospital General, Madrid, Community of Madrid, Spain
4Department of Oncology, Hospital Universitario Infanta So+a, San Sebastia´n de los Reyes, Community of Madrid, Spain
5Department of Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Galicia, Spain
6Department of Oncology, Hospital General Universitario de Elche, Elche, Valencian Community, Spain
7Department of Oncology, Hospital Universitario General Santa Lucia, Cartagena, Region of Murcia, Spain
8Department of Oncology, Hospital Universitario Central de Asturias, Oviedo, Asturias, Spain
Correspondence should be addressed to Caterina Calderon; ccalderon@ub.edu
Received 25 March 2025; Revised 8 September 2025; Accepted 17 September 2025
Guest Editor: Gabriella Pravettoni
Copyright © 2025 Caterina Calderon et al. European Journal of Cancer Care published by JohnWiley & Sons Ltd.,is is an open
access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in
any medium, provided the original work is properly cited.
Fatigue is a signi1cant challenge for cancer patients, substantially a2ecting their quality of life, physical symptoms, and psy-
chological distress.,is study examined the relationship between fatigue in patients with advanced cancer and sociodemographic,
clinical, and psychological factors. Conducted across 15 oncology departments in Spain, the study included patients with locally
advanced, unresectable, or metastatic cancer eligible for systemic treatment. Participants completed the Fatigue Assessment Scale
(FAS), European Organisation for Research and Treatment (EORTCQLQ-C30), Locus of Control (UWBHS), and Brief Symptom
Inventory (BSI). A total of 512 patients are participated, classi1ed into low-fatigue (55%) and high-fatigue (45%) groups. High
fatigue was associated with lower educational attainment (53% vs. 44%), locally advanced disease (26% vs. 17%), poorer functional
status according to ECOG (70% vs. 30%), and shorter expected survival (< 18months: 51% vs. 37%). Additionally, patients with
high fatigue reported greater use of integrative medicine (24% vs. 14%, p � 0.003) and higher prevalence of symptoms such as
pain, nausea, and memory problems (p< 0.05). ,ey also exhibited poorer quality of life and higher psychological distress. ,ese
1ndings highlight the need to develop multidimensional strategies that address both physical symptoms and quality of life to
enhance the well-being of cancer patients. Clinically, systematic screening for fatigue and psychological distress, alongside tailored
supportive interventions, should be embedded in routine care to optimize outcomes in advanced cancer patients.
Keywords: advanced cancer; fatigue; integrative medicine; psychological distress; quality of life
1. Introduction
Fatigue is a multifaceted and widespread symptom among
cancer patients, particularly those undergoing treatment for
advanced cancer [1]. Cancer-related fatigue refers to
a persistent sense of physical and/or mental exhaustion that
limits daily functioning. It is among the most prevalent
symptoms in oncology, a2ecting 40%–90% of patients
during the course of illness [2, 3]. While some degree of
fatigue is expected as part of the cancer experience, severe or
Wiley
European Journal of Cancer Care
Volume 2025, Article ID 5527075, 9 pages
https://doi.org/10.1155/ecc/5527075
persistent fatigue has been associated with a decreased
quality of life, reduced functional capacity, and poorer
treatment adherence [3, 4]. Additionally, it is linked to
a higher prevalence of physical symptoms, psychological
distress—including depression and anxiety—and increased
utilization of healthcare services [5, 6].
,e factors contributing to fatigue in cancer patients are
diverse and multifactorial. Sociodemographic variables—age,
gender, educational background, and employment—have
been consistently linked to fatigue, although results remain
heterogeneous [6–8]. For instance, older patients may ex-
perience higher levels of fatigue due to lower physical reserve;
in contrast, 1ndings regarding gender di2erences in fatigue
levels remain inconclusive. While some studies suggest that
women experience greater fatigue than men, possibly due to
hormonal, psychological, and distress perception di2erences
[9, 10], others report no signi1cant di2erences [11]. Low
educational attainment and unemployment have also been
associated with increased fatigue, potentially due to limited
access to symptom relief resources and support systems [12].
Clinical factors such as cancer stage, functional status,
and prognosis have also been investigated. Fatigue severity
has also been associated with functional impairment as
measured by Eastern Cooperative Oncology Group (ECOG)
and with reduced life expectancy in advanced cancer [5, 9].
Symptom burden, including pain, nausea, and sleep dis-
turbances, further exacerbates fatigue, creating a vicious
cycle that a2ects overall well-being [3, 4]. ,ese symptoms
often coexist and interact, complicating e2orts to e2ectively
address fatigue in oncology settings.
Psychosocial factors also play a fundamental role in
fatigue among cancer patients [10]. Higher levels of psy-
chological distress, including anxiety and depression, have
been shown to strongly correlate with fatigue [10, 11].
Additionally, locus of control can signi1cantly inJuence the
perception and management of fatigue. For instance, an
external locus of control, in which the patient perceives they
have no control over their situation, can exacerbate both
physical and psychological symptoms by increasing feelings
of helplessness and dependency while reducing motivation
to cope with the situation [12, 13]. ,is perceived lack of
control, combined with the absence of adequate care re-
sources, may intensify fatigue, particularly in highly de-
pendent patients [13, 14].
Alongside these well-established psychosocial and
clinical correlates, some patients turn to integrative medi-
cine practices such as acupuncture, meditation, or other
complementary therapies when experiencing high levels of
fatigue. Although the evidence supporting these approaches
remains limited, their use may reJect patients’ e2orts to
regain a sense of control and to cope with the multidi-
mensional burden of symptoms [15, 16]. In the present
study, we included integrative medicine as a secondary
variable of interest, while maintaining our primary focus on
sociodemographic, clinical, and psychological predictors of
fatigue.
Although fatigue has been extensively investigated in
early-stage cancer, its correlates in advanced disease remain
underexplored, particularly regarding the interplay of
sociodemographic, clinical, and psychosocial factors. To
address this gap, the present study analyzed these variables
in relation to fatigue pro1les among patients with advanced
cancer. In addition, it provides novel insights by examining
the understudied role of integrative medicine in this
population.
2. Materials and Methods
2.1. Study Design and Population. From February 2020 to
May 2024, a cross-sectional study was conducted across 15
medical oncology units in various Spanish university hos-
pitals. ,e study included adult patients aged 18 years or
older with a histopathologically con1rmed diagnosis of
unresectable advanced cancer, who were ineligible for
surgical or curative interventions and were candidates for
systemic anticancer treatments.
Exclusion criteria encompassed individuals with phys-
ical or mental conditions identi1ed by the oncologist as
hindering participation. To ensure consistency, oncologists
were trained through online meetings with the study co-
ordinators to exclude patients whose sociodemographic or
clinical circumstances could compromise their un-
derstanding of the study or their ability to participate re-
liably. Patients who had undergone treatment for another
advanced cancer within the past 2 years, or those experi-
encing signi1cant medical, social, familial, or personal
challenges that could interfere with the study, were also
excluded. ,is included patients with cognitive impair-
ments, substantial health deterioration, or those unable to
comprehend or complete the study questionnaires. Re-
cruitment was conducted during the initial oncology con-
sultation, during which patients were informed about their
diagnosis, disease stage, and available systemic treatments.
Participants who agreed to join the study provided written
informed consent and received questionnaires to complete
and return at their next visit.
,e study was approved by the Ethics Review Committee
of each participating hospital as well as the Spanish Agency
of Medicines and Health Products (AEMPS; identi1cation
code: ES14042015). Participation was voluntary, anony-
mous, and ensured no disruption to patients’ standard care.
Out of 547 individuals initially recruited, 512 met the eli-
gibility criteria. ,irty-1ve participants were excluded for
various reasons: 9 did not meet the inclusion criteria, 9 met
at least one exclusion criterion, and 17 provided
incomplete data.
2.2. Variable Description. Sociodemographic and clinical
data were collected from patients participating in the study,
including sex (male or female), age (≤ 65 years or > 65 years),
marital status (married or in a relationship vs. single), ed-
ucational level, and employment status (unemployed or
employed).
Regarding clinical data, tumor location (broncho-
pulmonary, colorectal, pancreas, breast, stomach, or other),
histology (adenocarcinoma or other), disease stage (locally
advanced or with distant metastases), type of treatment
2 European Journal of Cancer Care
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received (chemotherapy, immunotherapy, targeted func-
tional therapies, or other), ECOG performance status (0 or 1
vs. 2 or higher), and estimated survival (< 18months or≥ 18months) were recorded. ,is information was uni-
formly obtained from all participating hospitals as part of the
study protocol. Data were managed by medical oncologists
through a centralized digital platform.
,ree months after the initiation of systemic treatment,
when toxicities such as fatigue are often most evident and
treatment decisions are reassessed, patients were asked to
complete the Fatigue Assessment Scale (FAS), the European
Organisation for Research and Treatment of Cancer
(EORTC QLQ-C30), the Locus of Control (UWBHS), and
the Brief Symptom Inventory (BSI). In addition, they were
asked whether they had used any integrative therapies and, if
so, to specify the type, including homeopathy, mind–body
approaches (e.g., yoga, meditation, coaching), biological
therapies, body-based methods (massage, chiropractic),
acupuncture, and energy-based therapies (tai chi, Reiki).
Fatigue was assessed with the 10-item FAS, which covers
both physical and mental aspects but has been validated as
a unidimensional measure of overall fatigue [17]. Items are
rated on a 5-point Likert scale (10–50 total score), with
higher values indicating greater severity [18]. ,e Spanish
version has shown good reliability and validity [19].
Quality of life was measured with the EORTCQLQ-C30,
a widely used 30-item questionnaire in oncology. It provides
three main indices: functional status (physical, role, emo-
tional, social, and cognitive functioning), symptom burden
(pain, fatigue, nausea, sleep problems, appetite loss, among
others), and global health status. Scores are standardized
from 0 to 100, with higher values reJecting better func-
tioning or health, or greater symptom severity depending on
the subscale. ,e questionnaire has been validated across
multiple tumor types, shows strong internal consistency,
requires less than 15min to complete, and has a validated
Spanish version [20].
Perceived control was measured with the Locus of
Control Scale (UWBHS), which captures internal versus
external illness-related control beliefs [21]. Higher exter-
nality scores reJect a perception that outcomes are de-
termined by others or external circumstances. ,e UWBHS
has been validated across diverse populations and has shown
signi1cant associations with psychological outcomes [21].
Psychological distress was assessed using the BSI-18,
which screens for anxiety, depression, and somatization
[22]. Items are rated on a 5-point Likert scale, yielding both
subscale scores and a Global Severity Index, with higher
scores reJecting greater psychological distress. ,e Spanish
version of the BSI has been validated for its reliability and
validity [23].
2.3. Statistical Methods. Descriptive statistics and frequency
distributions were calculated to summarize demographic
and clinical characteristics. A cluster analysis was performed
to identify participants with similar fatigue patterns. Clus-
tering variables included the fatigue items, and participants
with any missing FAS scores were excluded, as this
technique requires complete data for all variables. ,e k-
means method was used with Euclidean distances between
observations to estimate clusters, along with Ward’s hier-
archical clustering method, which de1nes the distance be-
tween two clusters based on the squared error criterion [24].
In all cases, distances were computed from raw data to
incorporate the elevation, scatter, and shape of patients’
pro1les [25]. ,e optimal two-cluster solution was de-
termined based on dendrogram inspection, silhouette index
values, and clinical interpretability, distinguishing between
low and high fatigue. Analyses of variance (ANOVA) and
chi-square tests were conducted to examine di2erences in
demographic, clinical, and psychological characteristics
between the fatigue pro1les. Eta-squared ranges between
0 and 1, with η2∼0.01 indicating a small, η2∼0.06 a medium,
and η2 > 0.14 a large e2ect size [25]. Statistical signi1cance
was set at a p-value of < 0.05. All statistical analyses were
performed using the Statistical Package for Social Sciences
(SPSS) software, Version 26.0 (IBM SPSS Statistics for
Windows, Armonk, NY, USA: IBM Corp.).
3. Results
3.1. Sociodemographic and Clinical Characteristics. ,e de-
mographic and clinical characteristics of the 512 study
participants, categorized into low fatigue (55%, n� 280) and
high fatigue (45%, n� 232) groups, are summarized in Ta-
ble 1. ,e cluster analysis identi1ed two distinct pro1les:
a low-fatigue group (M� 21.41, SD� 2.38) and a high-fatigue
group (M� 24.83, SD� 7.16). Signi1cant di2erences were
identi1ed in educational level, disease stage, ECOG per-
formance status, and estimated survival. Participants with
lower educational attainment (primary education) were
more likely to report high fatigue (53%) compared to low
fatigue (44%) (p � 0.042). Similarly, those with locally ad-
vanced disease showed higher levels of fatigue (26%)
compared to participants with metastatic disease (17%)
(p � 0.016). ECOG performance status was strongly asso-
ciated with fatigue pro1les, with participants reporting high
fatigue more frequently having ECOG scores of 2 or higher
(70%) compared to those in the low-fatigue group (30%)
(p � 0.001). Furthermore, an estimated survival of less than
18months was signi1cantly associated with high fatigue
(51% vs. 37%, p � 0.001).
Other variables, such as sex, age, marital status, em-
ployment, tumor site, histology, and type of treatment, did
not show signi1cant di2erences between fatigue groups
(p> 0.05). ,ese results underscore the impact of clinical
and prognostic factors on fatigue, highlighting the impor-
tance of performance status and disease progression in
understanding fatigue pro1les among oncology patients.
3.2. IntegrativeMedicineUse and SymptomsAmongOncology
PatientsWithDi7erent Fatigue Levels. ,e use of integrative
medicine and the prevalence of symptoms among the fatigue
pro1les are presented in Table 2. Participants in the high-
fatigue group were more likely to report the use of in-
tegrative medicine (24%) compared to those in the low-
European Journal of Cancer Care 3
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fatigue group (14%) (p � 0.003). Details of the speci1c
modalities are summarized in Table 3, showing that the most
commonly reported practices were homeopathy (26%) and
mind–body approaches such as yoga, meditation, or
coaching (26%), followed by biological therapies (19%),
body-based methods (15%), acupuncture (10%), and energy-
based therapies such as tai chi or Reiki (4%).
Symptom prevalence was notably higher among par-
ticipants in the high-fatigue group across nearly all cate-
gories. High fatigue was signi1cantly associated with higher
rates of pain (71% vs. 44%, p � 0.001), nausea/vomiting
(51% vs. 20%, p � 0.001), diarrhea (44% vs. 35%, p � 0.043),
skin problems (53% vs. 39%, p � 0.001), infections (29% vs.
8%, p � 0.001), and memory issues (72% vs. 29%,
p � 0.001). Other symptoms signi1cantly more common in
the high-fatigue group included thyroid-related problems
(21% vs. 9%, p � 0.001), sores (47% vs. 28%, p � 0.001), liver
issues (32% vs. 16%, p � 0.001), kidney problems (25% vs.
11%, p � 0.001), and patient-reported scarring (63% vs.
50%, p � 0.002). A small but signi1cant di2erence was also
observed in patient death rates, with a higher proportion in
the high-fatigue group (6%) compared to the low-fatigue
group (3%) (p � 0.042). ,ese 1ndings highlight the com-
plex interplay between symptom burden and fatigue levels in
oncology patients, suggesting a potential role for integrative
medicine in addressing these challenges.
3.3. Psychosocial Characteristics Related to Patients’ Fatigue
Pro+les. When examining the relationships between fatigue
pro1les and psychosocial characteristics using the scales
(EORTC, UWBHS, BSI), signi1cant di2erences were ob-
served between the low-fatigue (n� 280) and high-fatigue
(n� 232) groups. Participants in the high-fatigue group
reported lower functional quality of life (M� 49.3 vs.
Table 1: Di2erences in demographic and clinical characteristics among the fatigue pro1les (n� 512).
Variable
Total n
(%) 512
(100%)
Low fatigue
n (%)
280 (55%)
High fatigue
n (%)
232 (45%)
X2 p -value
Sex
Male 286 (56) 161 (57) 125 (54) 0.675 0.411
Female 226 (44) 119 (43) 107 (46)
Age≤ 65 years 204 (40) 103 (37) 101 (44) 2.411 0.120> 65 years 308 (60) 177 (63) 131 (56)
Marital status
Married or partnered 361 (70) 191 (68) 169 (73) 1.303 0.254
Not partnered 151 (30) 89 (32) 63 (27)
Educational level
Primary 244 (48) 122 (44) 122 (53) 4.133 0.042
High school or more 268 (52) 158 (56) 110 (47)
Employment
Unemployed 298 (58) 162 (58) 137 (59) 0.075 0.785
Employed 214 (42) 118 (55) 95 (41)
Tumor site
Broncopulmonary 144 (28) 77 (28) 67 (29) 6.721 0.242
Colorectal 98 (19) 62 (22) 36 (16)
Pancreas 50 (10) 21 (8) 28 (12)
Breast 69 (14) 37 (13) 32 (14)
Stomach 27 (5) 17 (6) 10 (4)
Others 124 (24) 66 (24) 59 (25)
Histology
Adenocarcinoma 348 (68) 195 (70) 154 (66) 0.623 0.430
Others 164 (32) 85 (30) 78 (34)
Stage
Locally advanced 108 (21) 48 (17) 60 (26) 5.795 0.016
Dis. metastases (IV) 404 (79) 232 (83) 172 (74)
Type of treatment
Chemotherapy 245 (48) 130 (46) 115 (50) 1.469 0.832
Immunotherapy 32 (6) 19 (7) 13 (6)
Targeted therapies 31 (6) 16 (6) 15 (7)
Others 204 (40) 115 (41) 89 (38)
ECOG
0 or 1 302 (59) 139 (50) 69 (30) 20.147 0.001
2 or more 210 (41) 138 (50) 158 (70)
Estimated survival< 18months 208 (41) 104 (37) 119 (51) 10.333 0.001≥ 18months 296 (59) 176 (63) 113 (49)
4 European Journal of Cancer Care
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iley Online Library on [19/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W
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M� 72.5; η2 � 0.372), higher symptom burden (M� 38.8 vs.
M� 16.8; η2 � 0.290), and worse overall health status
(M� 47.3 vs. M� 57.3; η2 � 0.039).
Additionally, those in the high-fatigue group scored
signi1cantly lower on locus of control (M� 15.4 vs.M� 16.6;
η2 � 0.018) and reported greater psychological distress
(M� 70.6 vs. M� 62.4; η2 � 0.312). ,ese 1ndings highlight
the considerable psychosocial disparities associated with
fatigue levels in cancer patients (Table 4).
4. Discussion
Fatigue is highly prevalent in oncology and has substantial
consequences for daily functioning, treatment adherence, and
overall quality of life [1]. ,is study explored sociodemo-
graphic, clinical, and psychosocial factors associated with
fatigue, classifying participants into low- and high-fatigue
pro1les. ,e 1ndings partially support the inJuence of var-
iables such as educational level, disease stage, functional
status, and overall health. Whereas most research has focused
on early-stage cancer, our study sheds light on fatigue in
advanced disease, revealing distinct patterns and providing
clinically meaningful contributions to an underexplored area.
In this study, patients with high fatigue not only reported
higher levels of psychological distress but also showed
a greater tendency to use integrative medicine (24% vs. 14%).
,is suggests that while distress is a central correlate and
should be addressed primarily through evidence-based
psychological interventions, some patients additionally
seek complementary approaches to cope with their symp-
toms and improve quality of life. ,is 1nding is consistent
with meta-analyses indicating that more than half of cancer
patients experience fatigue, a prevalence signi1cantly higher
than that observed in the general population and individuals
with other diseases [26, 27]. In our study, participants with
only primary education reported higher levels of fatigue
compared to those with higher education. ,is aligns with
previous studies, such as Schmidt et al. [28] in breast cancer,
where fatigued patients had lower educational attainment,
and Wang et al. [29] in colorectal cancer, which showed
better fatigue management among patients with university
education. ,ese 1ndings suggest that lower educational
levels may limit access to or understanding of information
on symptom management, exacerbating fatigue.
Disease stage also inJuenced the perception of fatigue.
Participants with locally advanced disease reported higher
fatigue levels compared to those with metastatic disease.
Although this result may seem counterintuitive, it could be
explained by several factors. Patients with metastatic disease,
facing a worse prognosis, may receive less aggressive pal-
liative treatments and have had more time to psychologically
adapt to their diagnosis and develop coping strategies. On
the other hand, patients with locally advanced disease are
often undergoing more active and intensive treatment,
which leads to more severe side e2ects and greater un-
certainty about the disease course, potentially increasing the
perception of fatigue.,ese results are similar to those found
by other authors, who have observed that disease progres-
sion can directly inJuence the intensity of fatigue [30, 31].
,e ECOG performance status was strongly associated
with fatigue, with higher ECOG scores (≥ 2) being more
Table 2: Di2erences in the use of integrative medicine in oncology among the fatigue pro1les (n� 512).
Variable
Total n
(%) 512
(100%)
Low fatigue
n (%)
280 (55%)
High fatigue
n (%)
232 (45%)
X2 p -value
Medicine integrative
No 407 (82) 236 (86) 171 (76) 9.014 0.003
Yes 91 (18) 37 (14) 54 (24)
Symptoms
Fever 70 (14) 24 (9) 46 (20) 13.502 0.001
Pain 288 (56) 123 (44) 165 (71) 37.641 0.001
Loss of appetite 276 (54) 107 (38) 169 (73) 60.675 0.001
Nausea/vomiting 175 (34) 57 (20) 118 (51) 52.095 0.001
Diarrhea 198 (39) 97 (35) 101 (44) 4.103 0.043
Skin problems 231 (45) 108 (39) 123 (53) 10.468 0.001
Infections 89 (17) 22 (8) 67 (29) 38.815 0.001
Scars 285 (56) 138 (50) 147 (63) 9.921 0.002
,yroid 74 (15) 25 (9) 49 (21) 15.124 0.001
Sores 187 (37) 77 (28) 110 (47) 21.435 0.001
Liver 119 (23) 44 (16) 75 (32) 19.438 0.001
Kidney 88 (17) 30 (11) 58 (25) 18.037 0.001
Memory 249 (49) 82 (29) 167 (72) 91.975 0.001
Patient’s death 21 (4) 7 (3) 14 (6) 4.140 0.042
Table 3: Types and frequencies of integrative medicine modalities
used by patients (n� 91).
Modality n %
Homeopathy 24 26
Mind–body approaches (yoga, meditation, coaching) 24 26
Biological therapies 17 19
Body-based methods (massage, chiropractic) 14 15
Acupuncture 9 10
Energy-based therapies (tai chi, Reiki) 4 4
European Journal of Cancer Care 5
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iley Online Library on [19/10/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W
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frequent in the high-fatigue group. ,is 1nding highlights
the crucial role of functional status in understanding fatigue.
Patients with limited physical functioning often report
greater fatigue due to the combined impact of disease burden
and reduced capacity for daily activities [28, 31]. Similarly,
estimated survival emerged as a signi1cant predictor, as
participants with a prognosis of less than 18months re-
ported higher levels of fatigue. ,is association may be
linked to the psychological distress associated with a shorter
life expectancy and the greater physical burden of advanced
disease [29]. Fatigue is recognized as a prognostic factor in
advanced cancer [32], reducing survival time by approxi-
mately 39%–44% [33].
On the other hand, variables such as the type of treat-
ment did not show signi1cant di2erences between fatigue
pro1les in our cohort. ,is lack of association suggests that
fatigue may be more strongly inJuenced by clinical and
prognostic factors than by broader demographic
characteristics.
In our study, patients with high fatigue showed a greater
tendency to use integrative medicine compared to those with
low fatigue (24% vs. 14%). Among the most common
practices were homeopathy and mind–body approaches,
used by 26% of users. Other methods included biological
therapies (19%), body-based approaches (15%), acupuncture
(10%), and energy-based therapies such as tai chi or Reiki
(4%). ,is increased use of integrative medicine suggests
that patients with high fatigue seek complementary ap-
proaches to alleviate their symptoms and improve their
quality of life, aligning with existing literature on the
multidimensional impact of fatigue in cancer care.
Psychological interventions such as cognitive-behavioral
therapy, psycho-oncological support, and mindfulness-
based programs have demonstrated robust evidence in re-
ducing cancer-related fatigue and distress and should be
considered 1rst-line strategies. Several studies support the
e2ectiveness of integrative therapies in managing fatigue,
particularly in cancer patients [15, 16]. Digital interventions,
such as IM@Home, have been shown to signi1cantly reduce
fatigue [34], while holistic approaches like Integrated-pathy
have improved quality of life and reduced cancer-related
pain [35]. Additionally, mind–body therapies such as
mindfulness and exercise have demonstrated bene1ts for
both physical and emotional well-being [36]. However, some
patients do not experience suRcient relief with these
methods, underscoring the need for further research to
optimize treatments and better understand individual
responses [37].
Our 1ndings con1rm that fatigue is strongly associated
with a higher symptom burden in cancer patients, aligning
with previous studies that have identi1ed its relationship
with multiple physical symptoms and systemic factors [38].
In our study, patients with high fatigue exhibited signi1-
cantly higher rates of pain (71% vs. 44%), nausea/vomiting
(51% vs. 20%), and memory problems (72% vs. 29%),
highlighting its multidimensional impact and the need for
a comprehensive approach to its management.
Additionally, the higher incidence of thyroid dysfunc-
tion (21% vs. 9%) and infections (29% vs. 8%) in this group
suggests that fatigue may be inJuenced by systemic alter-
ations a2ecting the patient’s overall health status. Likewise,
mortality was higher in the high-fatigue group (6% vs. 3%),
suggesting that fatigue could serve as a prognostic marker in
disease progression. Recent studies also indicate that severe
fatigue is linked to a higher risk of toxicity in cancer
treatments, reinforcing its clinical relevance [39].
On the other hand, some studies have suggested that
lifestyle-related factors, such as physical activity prior to
diagnosis, may mitigate fatigue severity [38]. ,is un-
derscores the importance of designing personalized in-
terventions that not only address fatigue as a symptom but
also consider its underlying causes and modi1able factors to
improve patients’ quality of life.
In our study, fatigue showed a signi1cant association
with quality of life, health status, and psychological distress.
Patients with high fatigue exhibited a notable reduction in
functional quality of life and a higher symptom burden.
Likewise, this group showed signi1cantly higher levels of
psychological distress, as evidenced by elevated scores in
anxiety, depression, and somatic symptoms. ,ese 1ndings
align with previous studies that have identi1ed a correlation
between fatigue and impairment in both physical and
psychological domains, such as in hemodialysis patients,
where fatigue is associated with a lower quality of life [40],
and in cancer survivors, who report signi1cantly reduced
quality of life when experiencing severe fatigue [41, 42].
,ese results underscore the interconnectedness of physical
and emotional well-being, suggesting that fatigue not only
intensi1es symptom burden but also exacerbates psycho-
logical distress and compromises overall quality of life. From
Table 4: Di2erences in psychosocial characteristics and fatigue pro1les.
Low fatigue n (%)
280 (55%)
High fatigue n (%)
232 (45%) F p Eta-squared
Mean SD Mean SD
Quality of Life (EORTC)
Functional scale 72.5 11.9 49.3 18.1 296.87 0.001 0.372
Symptom scale 16.8 13.1 38.8 20.6 205.25 0.001 0.290
Health status 57.3 28.5 47.3 19.7 20.18 0.001 0.039
Locus of Control (UWBHS) 16.6 4.4 15.4 3.8 9.12 0.03 0.018
Psychological distress (BSI) 62.4 5.3 70.6 6.9 228.08 0.001 0.312
Note: UWBHS, Locus of Control.
Abbreviations: BSI, Brief Symptom Inventory; EORTC, European Organisation for Research and Treatment of Cancer; SD, standard deviation.
6 European Journal of Cancer Care
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a clinical perspective, this highlights the importance of
systematically screening for distress in patients with high
fatigue and integrating evidence-based psychological sup-
port as a core component of fatigue management.
4.1. Limitations. ,is study has some limitations that should
be considered when interpreting the 1ndings. First, patients
with di2erent tumor types were included without making
comparisons between them, limiting the generalizability of
the results to speci1c metastatic neoplasms. Second, the
sample consists exclusively of cancer patients in Spain,
a country with universal access to public healthcare, meaning
the resultsmay not be directly applicable to healthcare settings
with di2erent care models and resources, particularly in non-
Western countries. Another limitation is the cross-sectional
design, which prevents establishing causal relationships be-
tween fatigue, emotional distress, and other clinical factors, or
analyzing their evolution over time. Exclusion criteria were
based on clinical judgment without standardized tools, which
may introduce selection bias and limit representativeness,
despite investigators being trained to apply them consistently.
Finally, integrative medicine use was considered only as an
exploratory variable, and no causal role can be inferred.
Fatigue was analyzed dichotomously using an empirical
clustering approach, which, while consistent with conven-
tional thresholds, inevitably reduced variability compared
with continuous analyses. Assessments were also conducted
3months after treatment initiation, which may not capture
trajectories detectable at other time points. Future longitu-
dinal studies should explore the course of fatigue, psycho-
logical distress, and quality of life and directly compare the
impact of psychological interventions and complementary
therapies to inform clinical practice.
Despite these limitations, the study highlights signi1cant
associations between fatigue severity, the use of integrative
medicine, and symptom burden in cancer patients. ,e
results indicate that patients with severe fatigue are more
likely to turn to integrative approaches such as homeopathy,
yoga, and biological therapies, suggesting a potential unmet
need for complementary strategies in symptom manage-
ment. Furthermore, these patients reported a signi1cantly
higher prevalence of physical symptoms, including pain,
nausea, and memory problems, reinforcing the multidi-
mensional nature of fatigue and its impact on quality of life.
5. Conclusions
From a clinical perspective, these 1ndings emphasize the
importance of fatigue as a critical factor in the cancer patient
experience. Systematic screening could facilitate the early
identi1cation of patients at risk of a high symptom burden
and allow for more personalized interventions. Given the
strong association between fatigue and psychological dis-
tress, evidence-based psychological support should be pri-
oritized in routine care. Complementary therapies may also
contribute as useful adjuncts; however, further research is
warranted to establish their eRcacy, applicability, and role in
alleviating symptom-related distress.
Data Availability Statement
,e datasets generated and/or analyzed during the current
study are not publicly available due to patient con1dentiality
restrictions but are available from the corresponding author
on reasonable request.
Ethics Statement
,is study was conducted in accordance with the Decla-
ration of Helsinki. Approval was obtained from the Research
Ethics Committee of the Principality of Asturias (May 17,
2019) and by the Spanish Agency of Medicines and Medical
Devices (AEMPS) (identi1cation code: L34LM-MM2GH-
Y925U-RJDHQ). ,e study was observational and non-
interventional. All participants provided written informed
consent.
Consent
Please see Ethics Statement.
Disclosure
,e funders had no role in the design of the study, in the
collection, analysis, or interpretation of the data, or in the
writing of the manuscript.
Conflicts of Interest
,e authors declare no conJicts of interest.
Funding
,is study was supported by the Spanish Society of Medical
Oncology Foundation (FSEOM) through grants for Col-
laborative Groups Projects (FSEOM2018; FSEOM2023) by
AstraZeneca (AZ2020; AZ2024) and by PID2022-
137317OB-100 funded by MCIN/AEI/10.13039/
501100011033/ and cofunded by the European Union
(FEDER, “A way to make Europe”).
Acknowledgments
,e authors gratefully acknowledge the patients and their
families for their participation in this study.
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