Determinants of quality of life in patients with incurable

Original Article

Determinants of Quality of Life in Patients With Incurable
Cancer
1
2
Louise E. Daly, PhD
; Ross D. Dolan, MD, MRCS, MSc, MA
; Derek G. Power, MD, MB, BCh, MRCPI3;
1
2
Éadaoin Ní Bhuachalla, RD, PhD ; Wei Sim, BSc ; Samantha J. Cushen, RD, PhD1; Marie Fallon, MD, MBChB, MRCGP, FRCP4;
2
Claribel Simmons, MD, MBChB, MRCP (UK), MRCGP4; Donald C. McMillan, PhD
; Barry J. Laird, MD, MBChB4;
1
and Aoife M. Ryan, RD, PhD

BACKGROUND: Optimizing quality of life (QoL) remains the central tenet of care in patients with incurable cancer; however, determinants of QoL are not clear. The objective of the current study was to examine which factors influence QoL in patients with incurable
cancer. METHODS: A multicenter study of adult patients with advanced cancer was conducted in Ireland and the United Kingdom
between 2011 and 2016. Data were collected from patients at study entry and included patient demographics, Eastern Cooperative
Oncology Group performance status (ECOG-PS), nutritional parameters (the percentage weight loss [%WL]), muscle parameters
assessed using computed tomography images (skeletal muscle index and skeletal muscle attenuation), inflammatory markers (modified
Glasgow Prognostic score [mGPS]), and QoL data (the European Organization for Research and Treatment Quality-of-Life Questionnaire
C-30). The relation between clinical, nutritional, and inflammatory parameters with QoL was assessed using the Spearman rank correlation coefficient and multivariate binary logistic regression. Components of the European Organization for Research and Treatment
Quality-of-Life Questionnaire C-30 (physical function, fatigue, and appetite loss) and summary QoL scores were mean-dichotomized
for the logistic regression analyses. RESULTS: Data were available for 1027 patients (51% men; median age, 66 years). Gastrointestinal
cancer was most prevalent (40%), followed by lung cancer (26%) and breast cancer (9%). Distant metastatic disease was present in
87% of patients. The %WL, ECOG-PS, and mGPS were significantly correlated with deteriorating QoL functional and symptom scales (all
P < .001). On multivariate regression analysis, >10% WL (odds ratio [OR], 2.69; 95% CI, 1.63-4.42), an ECOG-PS of 3 or 4 (OR, 14.33; 95%
CI, 6.76-30.37), and an mGPS of 2 (OR, 1.58; 95% CI, 1.09-2.29) were independently associated with poorer summary QoL scores. These

parameters were also independently associated with poorer physical function, fatigue, and appetite loss (all P < .05). Low skeletal muscle
attenuation was independently associated with poorer physical functioning (OR, 1.67; 95% CI, 1.09-2.56), but muscle parameters were not
independently associated with fatigue, appetite loss, or QoL summary scores. CONCLUSIONS: The current findings indicate that QoL
is determined (at least in part) by WL, ECOG-PS, and the systemic inflammatory response in patients with advanced cancer. Identifying
early predictors of poor QoL may allow the identification of patients who may benefit from early referral to palliative and supportive care,
which has been shown to improve QoL. Cancer 2020;0:1-11. © 2020 American Cancer Society.
KEYWORDS: incurable cancer, palliative care, performance score, quality of life, systemic inflammation, weight loss.

INTRODUCTION
The European Society of Medical Oncology1 advocates integrating supportive and palliative, patient-centered care into
overall anticancer treatment at all stages of the disease. The European Society of Medical Oncology acknowledges that
oncology patients’ needs are not being adequately met and that oncology care should encompass patient-centered supportive and palliative care from initial diagnosis and throughout the entire trajectory of the disease. Importantly, cancer
care should not only aim to deliver the best quality anticancer treatment, but it should now also consider the effect of a
cancer diagnosis and its treatment on each patient’s life.1
In patients who have an incurable cancer, the fundamental objective of treatment is to optimize quality of life
(QoL). If this can be attained in unison with prolonged survival, then this is clearly desirable; however, if prolonged
survival comes at the expense of impaired QoL, then this may not be in the best interests of patients. Importantly, QoL
Corresponding Author: Louise E. Daly, PhD, Office 135, School of Food & Nutritional Sciences, College of Science, Engineering, and Food Science, University College Cork,
Cork, Ireland ().
1

 School of Food and Nutritional Sciences, College of Science, Engineering and Food Science, University College Cork, Cork, Ireland; 2 Academic Unit of Surgery, University
of Glasgow, Glasgow, United Kingdom; 3 Department of Medical Oncology, Mercy and Cork University Hospital, Cork, Ireland; 4 Edinburgh Cancer Research Centre, Institute
of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
The first two authors contributed equally to this work.
The last two authors contributed equally to this work as joint senior authors.
We acknowledge support from the Health Research Board Clinical Research Facility Cork and from Medical Research Scotland.
Additional supporting information may be found in the online version of this article.
DOI: 10.1002/cncr.32824, Received: April 24, 2019; Revised: September 19, 2019; Accepted: January 24, 2020, Published online Month 00, 2020 in Wiley Online Library
­(wileyonlinelibrary.com)

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Original Article

is increasingly being recognized as an important prognostic indicator, and QoL has been associated with reduced
survival in various cancer sites, even after adjusting for
known prognostic clinical variables.2-5
The current almost routine adoption of patientreported outcome measures (PROMs) of QoL into cancer clinical trials has enhanced our understanding of
this area.6 The European Organization for the Research
and Treatment of Cancer (EORTC) has now developed
over 60 QoL modules, including the universal EORTC
Quality-of-Life Questionnaire C-30 (EORTC QLQC30).7 By using this questionnaire, it has been shown that
both physical function (performance score) and measures
of the systemic inflammatory response (measured with
the modified Glasgow prognostic score [mGPS]) have a
differential association with QoL.8,9 In a large cohort of
2520 patients with advanced cancer, increasing mGPS
and deteriorating Eastern Cooperative Oncology Group
performance status (ECOG-PS) were associated with
deterioration in QoL parameters such as global health;
role, physical, and social functioning; fatigue; pain; and
appetite symptoms (P < .001). The association with increasing systemic inflammation and poorer QoL parameters was independent of PS.8 It has also been reported
that other aspects, including weight loss (WL), body mass
index (BMI), and loss of muscle (sarcopenia) influence

QoL in patients with cancer.10-12
It has been argued that the host-tumor interaction
and the resulting systemic inflammatory response is key
in the genesis of how symptoms/QoL are influenced in
patients with cancer. Indeed, work to date has supported
this hypothesis, demonstrating that the magnitude of the
systemic inflammatory response influences the magnitude of symptoms in patients with cancer.8 On the basis
of this work, markers of the systemic inflammatory response are now advocated as key assessment criteria for
staging nutritional status13 and as stratification factors
in randomized clinical trials.14 In the same way that the
tumor is staged, it has been argued that the host should be
staged, as inflammatory status is likely to influence treatment outcomes and magnitude of symptoms.15
However, a comparison of all factors known to influence QoL has yet to be done. Elucidation of those factors
that adversely influence QoL may allow the identification of patients who may benefit from early referral to
palliative and supportive care, which has been shown to
improve QoL.16,17 Therefore, the objective of the current
study was to examine the relation between clinical, nutritional, and inflammatory factors and QoL in patients
with incurable cancer.
2

MATERIALS AND METHODS
Study Sample

Data were collected across 18 sites in Ireland and Scotland
(cancer centers, hospitals, and specialist palliative care
units) over a period of 5 years (2011-2016). Patients were
older than 18 years and had a diagnosis of incurable cancer. Incurable cancer was defined as metastatic disease
or locally advanced disease being treated with palliative
intent. Both inpatients and outpatients were recruited,
and a convenience sampling approach was adopted.

Willing participants provided written informed consent.
Exclusion criteria included patients younger than 18 years
and those who were unwilling or unable to participate
because of cognitive impairment. Ethical approval was
given for the data collection at all sites and was conducted
according to good clinical practice and applicable laws.
Procedure and Assessment

Demographic data and clinical data were recorded
and included primary tumor site, stage, and extent of
metastatic disease (if present). The EORTC QLQ-C30
(version 3.0) was used to assess QoL.3 This 30-item,
cancer-specific questionnaire includes 5 functional
scales (physical, emotional, cognitive, social, and role),
3 symptom scales (fatigue, pain, and nausea/vomiting),
a global health/QoL scale, and 6 single items (dyspnea,
insomnia, appetite loss, constipation, diarrhea, and
financial impact of disease). The 28 items measuring
functional and symptom scales use a numeric scale for
scores of 1 (not at all), 2 (a little), 3 (quite a bit), and
4 (very much). The 2 items concerning global QoL
use a scale from 1 (very poor) to 7 (excellent). The raw
scores were linearly transformed to give standard scores
in the range of 0 to 100 for each of the scales and single items, as described by the EORTC.7 Higher scores
for the functional or global QoL scales represent a high
level of functioning or QoL, whereas higher scores on
the symptom scales represent worse symptomatology.
The summary score of the EORTC QLQ-C30, which
is comprised from the mean of 13 of the 15 QLQ-C30
scales (the global QoL and financial impact scales are not

included), was used to assess the overall summary QoL,
with a maximum score of 100.18 The summary score was
only calculated if all of the 13 required scale scores were
available, and the scoring of the QLQ-C30 summary
score was calculated as follows: QLQ-C30 summary
score = (physical functioning + role functioning + social functioning  +  emotional functioning  +  cognitive
functioning  +  100 − fatigue  +  100 − pain  +  100 −
nausea_vomiting  +  100 − dyspnea  +  100 − sleeping
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Quality of Life in Incurable Cancer/Daly et al

disturbances  (insomnia)  +  100 − appetite loss  +  100
− constipation + 100 − diarrhea)/13.18
Nutritional parameters were also assessed. Patient’s
weight, height, and BMI (weight [kg]/height [m2]) were
recorded. Patients were categorized according to their
BMI as underweight (<20  kg/m2), normal weight (2024.9  kg/m2), overweight (≥25-29.9  kg/m2), or obese
(≥30  kg/m2). WL in the preceding 3  months was reported by patients and, when possible, was verified from
patients’ medical records.
C-reactive protein (CRP) (mg/L) and albumin
(g/L) were used as markers of the systemic inflammatory
response and were measured in a venous blood sample
drawn at the time of consent. By using both CRP and
albumin, an mGPS was calculated accordingly.19 Patients
who had both elevated CRP (>10 mg/L) and hypoalbuminemia (<35 g/L) were assigned a score of 2. Patients
with only an elevated CRP (>10  mg/L) and without

hypoalbuminemia (albumin >35  g/L) were assigned a
score of 1. Patients with neither of these abnormalities
(ie, CRP <10  mg/L and albumin >35  g/L) were assigned a score of zero.20 The limit of detection of CRP
was <5 mg/L. An increasing score is related to increasing
systemic inflammation.19
PS was assessed using the ECOG score.21 Scores
were assigned according to patient-reported daily physical
function as follows: 0, fully active with no restrictions; 1,
restricted in physically strenuous activity but ambulatory
and able to perform light work; 2, ambulatory and capable of all self-care but unable to perform any work activities; 3, capable of only limited self-care; and 4, completely
disabled and totally confined to bed or chair.
Body Composition Assessment

Abdominal computerized tomography (CT) images, taken
as part of routine patient care within 12  weeks of QoL
assessment, were used to assess body composition as previously described.22 The third lumbar vertebrae (L3) was
chosen as the standard landmark, and 2 consecutive transverse CT images in which both transverse processes were
clearly visible were analyzed using OsiriX software version
4.1.1 (Pixmeo) for data collected in Ireland  and ImageJ
software (version 1.47; National Institutes of Health)  for
data collected in Scotland. Both imaging software packages have been shown to provide excellent agreement for
body composition measures.23 L3 was used as a standard
landmark because it correlates best with whole body measures of muscle mass.24,25 Skeletal muscle area (SMA) (cm2)
was manually outlined, and segmentation of SMA was
based on Hounsfield unit (HU) thresholds (from −29 to
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+150 HU).26 SMA was normalized for stature to compute

the skeletal muscle index (SMI) (cm2/m2). Mean muscle attenuation (MA) in HU was assessed in all patients with a
contrast-enhanced CT image and was reported for the entire SMA at L3. Sex-specific and BMI-specific cutoff points
were used to define low SMI (sarcopenia) and low MA according to Martin et al.27 Measurements were performed by
2 individuals (R.D. and L.E.D.), and inter-rater reliability
was assessed in a sample of 20 patient images using interclass
correlation coefficients (ICCCs) (SMA ICCC  =  0.986;
SMD ICCC  =  0.964). Investigators were blinded to
patient’s demographic and clinicopathologic status.
Statistical Analysis

Statistical analysis was conducted using SPSS (version
24.0; SPSS Inc). Data are expressed as the mean  ±  SD
or the median with interquartile range (IQR), where
appropriate. Comparisons between groups of patients
­
were assessed using the chi-square test for categorical
variables and the unpaired t test and the Mann-Whitney
U test for differences in continuous variables. Correlations
were investigated using the Spearman coefficient for nonparametric QoL data. The correlation coefficient (ρ) was
used to determine the strength of the correlations. The
Cohen guidelines were used when interpreting effect size
and strength of correlations. These suggest that ρ values
from 0.1 to 0.29 indicate a small effect size or correlation,
ρ values from 0.3 to 0.49 indicate a medium effect size,
and ρ values from 0.5 to 1.0 indicate a strong effect size or
correlation. Components of the EORTC-QLQ (physical
function, fatigue, and appetite loss) and the summary QoL
score were mean-dichotomized for the logistic regression
analyses assessing clinical, nutritional, and inflammatory
predictors of QoL. Patients with a score below the mean

for physical function and QoL summary scores and above
the mean for fatigue and appetite loss scores were given a
score of 1, whereas those with a score above the mean for
physical function and QoL summary scores and below the
mean for fatigue and appetite loss scores were given a score
of zero. Thus, an odds ratio (OR) >1.0 indicate a greater
likelihood of worse QoL. Independent variables that had
significance on univariate analysis were eligible for inclusion in multivariate analysis. All statistical tests were
2-sided, and P values <.05 were considered significant.
RESULTS
Patient Characteristics and Demographics

In total, 1027 patients with advanced cancer were recruited. Baseline demographic, clinical, nutritional, and
QoL characteristics are presented in Table 1. Patients
3


Original Article
TABLE 1.  Demographic and Clinical Characteristics
of the Patients Included in This Study
Variable
Sex
Men
Age, y
<65
65-74
>75
Primary cancer
Gastrointestinal
Lung

Othera
Metastatic disease*
Yes
ECOG PSb
0-1
2
3
4
mGPSc
0
1
2
BMI, kg/m2d
<20.0
20.0-24.9
25-29.9
>30.0
Weight loss, %e
<5
5-10
>10
Sarcopeniaf
Low muscle attenuationg
QoL domains, n = 1000
Functioning scales
Physical functioning
Role functioning
Emotional functioning
Cognitive functioning
Social functioning

Cancer-related symptom scales
Fatigue
Nausea and vomiting
Pain
Dyspnea
Insomnia
Anorexia
Constipation
Diarrhea
Global health status
QoL summary score

No. of Patients
(%) or Mean ± SD
 
524 (51)
 
483 (47)
300 (29)
244 (24)
 
411 (40)
266 (26)
350 (34)
 
862 (87)
 
575 (59)
292 (30)
96 (10)

16 (1)
 
353 (43)
139 (17)
329 (40)
 
122 (13)
348 (37)
299 (31)
180 (19)
 
674 (71)
143 (15)
134 (14)
192 (45)
223 (54)
 
 
68.4 ± 26.2
59.4 ± 35.8
79.4 ± 22.7
79.2 ± 24.7
66.0 ± 31.9
 
42.3 ± 28.6
13.6 ± 21.5
25.3 ± 31.3
24.3 ± 32.1
28.6 ± 33.6
27.3 ± 33.7

21.0 ± 30.4
12.3 ± 23.8
60.6 ± 24.1
73.8 ± 18.1

Abbreviations: BMI, body mass index; ECOG PS, Eastern Cooperative
Oncology Group performance status; mGPS, modified Glasgow prognostic
score; QoL, quality of life.
a
The other cancer group consisted of breast, gynecologic, genitourinary, neurologic, and hematologic cancers, melanoma, unknown primary cancers, and
others.
b
ECOG PS was available for 979 patients.
c
mGPS was available for 821 patients.
d
BMI was available for 949 patients.
e
The percentage weight loss was available for 951 patients.
f
Computed tomography scans were available for muscle mass (sarcopenia)
assessment in 428 patients.
g
Contrast-enhanced computed tomography images were available for muscle attenuation assessment in 413 patients.
*Presence or absense of distant metastatic disease was available for 994 patients.

4

were a median of 4.6  months postdiagnosis when they
entered the study (IQR, 3.0-13.0 months). In brief, 51%

of patients were men, and the median age was 66 years
(IQR, 57-74 years). Gastrointestinal cancer was the most
common type (40%), and metastatic disease was present
in 87% of patients. In total, 830 patients (81%) were actively receiving chemotherapy (chemotherapy in the preceding 4 weeks).
Anthropometry and Body Composition

Patients exhibited a wide variation in BMI (range,
12.3-47.4 kg/m2). One-half (51%) of all patients were
overweight or obese (BMI ≥25  kg/m2), whereas only
13% had a BMI <20.0  kg/m2. WL >5% in the preceding 3 months occurred in 277 patients (29%), with
14% experiencing severe WL >10%. In terms of body
composition, CT scans within 12 weeks of QoL assessment were available in 428 patients (contrast-enhanced
CT images for MA assessment were available in 413
patients). Overall, 192 patients (45%) were considered
to have a low SMI (sarcopenia), and 223 (54%) had
low MA.
Relation Between Clinical, Nutritional, and
Inflammatory Parameters With QoL

The relation between clinical, nutritional, and inflammatory parameters to PROMs is displayed in Table 2.
Within our cohort, female sex was significantly negatively
correlated with poorer physical function (ρ  =  −0.112;
P = .001), emotional function (ρ = −0.071; P = .024),
and summary QoL scores (ρ = −0.080; P = .012) and
positively correlated with more nausea and vomiting
(ρ = 0.123; P = .001) and pain (ρ = 0.068; P = .030).
Overall, the strength of these correlations was small
(ρ < 0.3). Increasing age was negatively correlated with
poorer physical (ρ = −0.143; P = .001), and role function (ρ  =  −0.063; P  =  .047) and was positively correlated with better emotional functioning (ρ  =  0.070;
P = .012). In terms of symptom scales, age was positively

correlated with more fatigue (ρ = 0.70; P = .024), dyspnea (ρ = 0.089; P = .005), and constipation (ρ = 0.073;
P = .020). The presence of distant metastatic disease (vs
locoregional incurable disease) was not statistically significantly correlated with any EORTC functional or symptom scale.
The %WL, ECOG-PS, and mGPS were negatively
correlated with almost all EORTC functional scales
(P  <  .05). Importantly, medium-to-strong correlations
(ρ  >  0.30) were observed between the ECOG-PS and
mGPS with physical function (ρ  =  −0.557 [P  <  .001]
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−0.112
 
−0.143
 
−0.013
 
−0.577
 
−0.312
 
−0.208
 

0.020

 
−0.164
 
−0.244

 
1027
 
1027
 
994
 
979
 
821
 
951
 
949

 
428
 
413

ρ
P

 
.001a
 
.001a

 
.001a
 
.001a
 
.691
 
.001a
 
.001a
 
.001a
 
.545

Physical

 
−0.070
 
−0.145

 
−0.028
 

−0.063
 
−0.034
 
−0.494
 
−0.272
 
−0.216
 
0.086

ρ

Role

 
.149
 
.003a

 
.379
 
.047a
 
.286
 
.001a
 

.001a
 
.001a
 
.008a

P

 
−0.078
 
0.009

 
−0.071
 
0.079
 
−0.010
 
−0.255
 
−0.069
 
−0.111
 
0.052

ρ

 
.103
 
.857

 
.024a
 
.012a
 
.766
 
.001a
 
.051
 
.001a
 
.113

P

Emotional

 
−0.026
 
−0.006

 

−0.049
 
−0.011
 
−0.031
 
−0.298
 
−0.163
 
−0.147
 
0.053

ρ
P

 
.592
 
.902

 
.121
 
.724
 
.339
 
.001a

 
.001a
 
.001a
 
.106

Cognitive

 
−0.104
 
−0.072

 
−0.035
 
−0.054
 
−0.008
 
−0.334
 
−0.158
 
−0.135
 
0.085

ρ

Social

 
.034
 
.145

 
.272
 
.089
 
.797
 
.001a
 
.001a
 
.001a
 
.009a

P

 
−0.052
 
−0.175

 
0.027
 
−0.058
 
−0.005
 
−0.410
 
−0.276
 
−0.207
 
0.072

ρ

 
.282
 
.001a

 
.397
 
.065
 
.871
 
.001a

 
.001a
 
.001a
 
.028a

P

Global Health

 
−0.060
 
−0.135

 
−0.080
 
−0.037
 
0.003
 
−0.500
 
−0.267
 
−0.291
 
0.077

ρ

 
.218
 
.006a

 
.012a
 
.247
 
.927
 
.001a
 
.001a
 
.001a
 
.018a

P

Summary QoL

Abbreviations: BMI, body mass index; ECOG PS, Eastern Cooperative Oncology Group performance status; EORTC-QOL, European Organization for Research and Treatment of Cancer Quality-of-Life scales; MA,
muscle attenuation; QoL, quality of life; SMI, skeletal muscle index; ρ, correlation coefficient.
a

These P values indicate statistical significance.

Sex
Men or women
Age, y
<65, 65-74, or >75
Metastatic disease
Yes or no
ECOG PS
0-1, 2, 3, or 4
mGPS
0, 1, or 2
Weight loss, %
<5, 5-10, or >10
BMI, kg/m2
<20, 20-24.9, 25-29.9,
or >30
Low SMI
No or yes
Low MA
No or yes

Variable

No. of
Patients

EORTC-QLQ Functional Scale

TABLE 2.  Relation Between Clinical, Nutritional, and Inflammatory Parameters With European Organization for Research and Treatment of

Cancer Quality-of-Life Functional Scales

Quality of Life in Incurable Cancer/Daly et al

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Original Article

and ρ  =  −0.312 [P  <  .001], respectively) and for the
ECOG-PS with role function (ρ = −0.494; P < .001),
social function (ρ  =  −0.334; P  <  .001), global health
(ρ  =  −0.410; P  <  .001), and, importantly, summary
QoL scores (ρ = −0.500; P < .001). The presence or absence of metastatic disease was not related to any of the
PROMs. Interestingly, reduced EORTC-reported physical functioning was more strongly correlated with low
MA compared with low SMI (ρ = −0.244 vs ρ = −0.164,
respectively). Low SMI was not significantly associated
with any other PROMS, whereas low MA was associated with role function (ρ = −0.145; P = .003), global
health (ρ = −0.175; P < .001), and QoL summary score
(ρ = −0.135; P = .006).
Table 3 depicts the relation between the symptom components of the EORTC-QLQ and clinical,
nutritional, and inflammatory parameters. In line with
we what we observed in the PROMs functional scales,
%WL, ECOG-PS, and mGPS were associated with
increasing symptoms scores (P  <  .05). Medium correlations (ρ  >  0.30) were observed between ECOG-PS
and fatigue (ρ = 0.476; P < .001) and pain (ρ = 0.309;
P < .001) and, as expected, between %WL and anorexia
(ρ = 0.311; P < .001). Low MA was associated with more
fatigue (ρ = 0.150; P = .002) and dyspnea (ρ = 0.150;
P = .002).

In the multivariate logistic regression analyses, the
QoL summary score was dichotomized by the mean
score (73.8). ORs >1.00 were associated with poorer
overall QoL. On multivariate regression analysis, %WL
(WL >5%: OR, 1.59; 95% CI, 1.01-2.51; P  =  .048;
WL >10%: OR, 2.69; 95% CI, 1.63-4.42; P  <  .001),
ECOG-PS (ECOG-PS 2: OR, 3.32; 95% CI, 2.34-4.70;
P  <  .001; ECOG-PS 3-4: OR, 14.33; 95% CI, 6.7630.37; P < .001), and mGPS (mGPS 1: OR, 2.05; 95%
CI, 1.26-3.32; P = .004; mGPS 2: OR, 1.58; 95% CI,
1.09-2.29; P = .0016) were independently predictive of
an overall QoL summary score below the mean (Table 4).
In terms of physical function (scores <68.4), WL
>10% (OR, 1.92; 95% CI, 1.16-3.19; P  =  .039),
ECOG-PS (ECOG-PS 2: OR, 3.93; 95% CI, 2.77-5.58;
P  <  .001; ECOG-PS 3-4: OR, 18.07; 95% CI, 7.9141.28; P  <  .001), an mGPS of 2 (OR, 2.01; 95% CI,
1.39-2.93; P  <  .001), and female sex (OR, 1.56; 95%
CI, 1.10-2.19; P  =  .011) were independent predictors
of poorer physical function on multivariate analysis (see
Supporting Table 1).
Examining predictors of fatigue (scores >42.3),
on multivariate analysis, WL >10% (OR, 2.53; 95%
CI, 1.53-4.19; P  <  .001), ECOG-PS (ECOG-PS 2:
6

OR, 2.89; 95% CI, 2.06-4.07; P  <  .001; ECOG-PS
3-4: OR, 18.67; 95% CI, 7.79-44.7; P < .001), and an
mGPS of 2 (OR, 1.57; 95% CI, 1.09-2.25; P < .001)
were independent predictors of more fatigue (see
Supporting Table 2).
On multivariate analysis, the factors associated with

more appetite loss (scores >27.3) were WL (WL >5%:
OR, 2.38; 95% CI, 1.51-3.76; P  <  .001; WL >10%:
OR, 2.51; 95% CI, 1.58-3.99; P  <  .001), ECOG-PS
(ECOG-PS 2: OR, 1.86; 95% CI, 1.26-2.74; P = .002;
ECOG-PS 3-4: OR, 2.59; 95% CI, 1.48-4.55; P = .001),
and mGPS (mGPS 1: OR, 1.72; 95% CI, 1.02-2.91;
P  =  .043; mGPS 2: OR, 1.64; 95% CI, 1.09-2.48;
P = .017) (see Supporting Table 3).
On assessment of the relation between muscle parameters and QoL (n  =  428), on univariate analysis,
low SMI was associated with poorer physical functioning (OR, 1.72; 95% CI, 1.27-2.33; P  <  0.001) but
not fatigue, appetite loss, or summary QoL score (all
P  >  .05). However, on multivariate assessment (controlling for WL, ECOG-PS, mGPS, and low MA),
low SMI was no longer associated with poorer physical
functioning (OR, 1.14; 95% CI, 0.74-1.73; P = .555).
On univariate analysis, low MA was associated with
poorer physical function (OR, 2.31;[95% CI, 1.693.18; P < .001), fatigue (OR, 1.66; 95% CI, 1.22-2.25;
P = .001), appetite loss (OR, 1.94; 95% CI, 1.33-2.84;
P = .001), and poorer summary QoL scores (OR, 1.41;
95% CI, 1.03-1.92; P = .032). However, after adjustment for %WL, ECOG-PS, mGPS, and low SMI, low
MA was only independently associated with poorer
physical functioning (OR, 1.67; 95% CI, 1.09-2.56;
P = .018).
DISCUSSION
For the first time to our knowledge, the current study
reports a comprehensive analysis of tumor and host factors and their effect on QoL in a large cohort of patients
with incurable disease. Our findings indicate that QoL is
determined (at least in part) by WL, performance, and
the systemic inflammatory response in patients with advanced cancer. Muscle mass and attenuation were significantly associated with some QoL domains on univariate
analysis; however, on multivariate analysis, there was no
significant independent association with fatigue, appetite loss, or QoL summary score. Our findings suggest

that interventions to mitigate the systemic inflammatory
­response and WL in patients with incurable cancer might
have a positive effect on patients’ QoL.
Cancer  

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Cancer  

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0.042
 
0.071
 
0.008
 
0.476
 
0.248
 
0.232
 
−0.072

 
0.057
 

0.152

 
1027
 
1027
 
994
 
979
 
821
 
952
 
949

 
428
 
413

ρ

 
.243
 
.002a

 

.179
 
.024
 
.794
 
.001a
 
.001a
 
.001a
 
.027a

P

 
−0.040
 
−0.049

 
0.123
 
−0.041
 
−0.009
 
0.206
 

0.147
 
0.198
 
−0.057

ρ

 
.413
 
.323

 
.001a
 
.189
 
.786
 
.001a
 
.001a
 
.001a
 
.081

P

Nausea and
Vomiting

 
0.035
 
0.054

 
0.068
 
−0.012
 
−0.057
 
0.309
 
0.207
 
0.167
 
−0.025

ρ

Pain

 
.473
 

.277

 
.030a
 
.700
 
.076
 
.001a
 
.001a
 
.001a
 
.438

P

 
0.012
 
0.150

 
0.015
 
0.089
 
−0.033

 
0.253
 
0.199
 
0.110
 
−0.006

ρ

 
.806
 
.002a

 
.629
 
.005a
 
.308
 
.001a
 
.001a
 
.001a
 
.853

P

Dyspnea

 
−0.096
 
−0.004

 
0.019
 
−0.060
 
−0.023
 
0.119
 
0.033
 
0.117
 
0.003

ρ

 
.047a
 

.934

 
.539
 
.059
 
.477
 
.001a
 
.346
 
.001a
 
.935

P

Insomnia

 
−0.033
 
0.116

 
0.065
 
0.040

 
−0.012
 
0.277
 
0.210
 
0.311
 
−0.167

ρ

 
.490
 
.019

 
.039
 
.203
 
.710
 
.001a
 
.001a
 
.001a

 
.001a

P

Anorexia

 
0.032
 
0.073

 
0.037
 
0.073
 
0.027
 
0.192
 
0.095
 
0.123
 
−0.049

ρ

 

.513
 
.142

 
.237
 
.020a
 
.396
 
.001a
 
.007a
 
.001a
 
.134

P

Constipation

 
0.020
 
−0.43

 
0.029

 
0.011
 
0.038
 
0.038
 
0.011
 
0.064
 
−0.056

ρ

 
.682
 
.380

 
.360
 
.735
 
.242
 
.244
 
.760

 
.051
 
.084

P

Diarrhea

 
−0.068
 
−0.184

 
−0.022
 
−0.302
 
−0.073
 
−0.017
 
−0.010
 
0.057
 
−0.001

ρ

 
.069
 
.001a

 
.481
 
.001a
 
.023
 
.601
 
.774
 
.082
 
.985

P

Financial Impact

Abbreviations: BMI, body mass index; ECOG PS, Eastern Cooperative Oncology Group performance status; EORTC-QOL, European Organization for Research and Treatment of Cancer Quality-of-Life scales; MA,
muscle attenuation; SMI, skeletal muscle index; ρ, correlation coefficient.
a
These P values indicate statistical significance.

Sex
Men or women
Age, y
<65, 65-74, or >75
Metastatic disease
Yes or no
ECOG PS
0-1, 2, 3, or 4
mGPS
0, 1, or 2
Weight loss, %
<5, 5-10, or >10
BMI, kg/m2
<20, 20-24.9,
25-29.9, or >30
Low SMI
No or yes
Low MA
No or yes

Variable

No. of
Patients

Fatigue

EORTC-QLQ Symptom Scales

TABLE 3.  Relation Between Clinical, Nutritional, and Inflammatory Parameters With European Organization for Research and Treatment of

Cancer Quality-of-Life Symptom Scales

Quality of Life in Incurable Cancer/Daly et al

7


Original Article
TABLE 4.  Clinical, Nutritional, and Inflammatory Parameters Related to Poor Quality-of-Life Summary Scores
(Below the Mean of <73.8) According to Multivariable Logistic Regression Analysis
Univariate Analysis
Variable
Sex
Men
Women
Age, y
<65
65-74
>75
Metastatic disease
No
Yes
ECOG PS
0-1
2
3-4
mGPS
0
1
2

BMI, kg/m2
20.0-24.9
<20
25-29.9
>30.0
Weight loss, %
<5
5%-10%
>10%

Multivariate Analysis

No. of Patients

OR

95% CI

P

OR

95% CI

P

 
510
490
 

476
289
235
 
127
842
 
572
283
97
 
349
132
313
 
348
122
299
180
 
671
140
126

 
1.00
1.35
 
1.00
0.95

1.01
 
1.00
1.11
 
1.00
4.22
16.56
 
1.00
3.03
2.73
 
1.00
1.95
0.81
1.25
 
1.00
2.17
4.85

 
 
1.05-1.73
 
 
0.71-1.27
0.74-1.38
 

 
0.76-1.61
 
 
3.11-5.72
8.42-32.58
 
 
1.99-4.61
1.99-3.75
 
 
1.28-2.98
0.59-1.12
0.86-1.79
 
 
1.50-3.15
3.11-7.54

 
 
.019a
 
 
.730
.956
 
 
.597

 
 
<.001a
<.001a
 
 
<.001a
<.001a
 
 
.002a
.205
.242
 
 
<.001a
<.001a

 
 
 
 
 
 
 
 
 
 
 
1.00

3.32
14.33
 
 
2.05
1.58
 
 
 
 
 
 
 
1.59
2.69

 
 
 
 
 
 
 
 
 
 
 
 
2.34-4.70
6.76-30.37

 
 
1.26-3.32
1.09-2.29
 
 
 
 
 
 
 
1.01-2.52
1.63-4.42

 
 
 
 
 
 
 
 
 
 
 
 
<.001a
<.001a
 
 

.004a
.016a
 
 
 
 
 
 
 
.048a
<.001a

Abbreviations: BMI, body mass index; ECOG PS, Eastern Cooperative Oncology Group performance status; mGPS, modified Glasgow prognostic score; OR, odds ratio.
a
These P values indicate statistical significance.

As expected, better ECOG-PS (scores of 0-1) correlated with better physical, role, emotional, and social functioning; better global heath scores; and less
fatigue, pain, anorexia, and constipation (all P < .001).
Considering that ECOG-PS is designed to determine a
patient’s ability to perform activities of daily living and
general well being, it is no surprise that the ECOG-PS is
associated with items of the EORTC QLQ-C30, and this
relation has been reported previously.8,28,29
Our findings also demonstrate that the systemic inflammatory response, as evidenced by mGPS scores ≥1, is
correlated with almost all EORTC functional and symptom scales. Furthermore, the mGPS was independently
associated with physical functioning, fatigue, appetite
loss, and the QoL summary score. Our findings echo
those previously reported in advanced cancer. Laird et al
reported that CRP was significantly associated with all of
the functional components of the EORTC QLQ-C30

and several the symptoms, including appetite loss, pain,
and fatigue.30
In some instances, individual cytokines implicated in
the proinflammatory response have been associated with
8

clinical symptoms, eg, interleukin-6 (IL-6) and CRP with
anorexia,31 IL-1ra with fatigue,31 and IL-6 with major
depression.32,33 However, whether these cytokines exert
their impact on symptoms in isolation or in combination is unclear. The reasons why systemic inflammation
worsens QoL in patients with cancer has recently been
reviewed,34 and evidence from various preclinical and
clinical studies suggest that the systemic inflammatory
response has a direct role in the development of cancerassociated symptom clusters, including pain, fatigue,
mood, anorexia, and physical function.34 Importantly, the
effect of systemic inflammation on QoL was independent
of ECOG-PS, consistent with previous reports indicating
that the systemic inflammatory response (mGPS) is associated with poorer QoL, even in those with a good performance score.8 Research is warranted to determine whether
attenuating the systemic inflammatory response is capable
of producing clinically relevant improvements in symptoms that may represent a new therapeutic approach to
symptom management in patients with advanced cancer.
We report herein that WL was associated with
poorer QoL in almost all functional and symptom
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Quality of Life in Incurable Cancer/Daly et al

domains. In particular, WL in excess of 10% in the
preceding 3 months was independently associated with
poorer physical function, fatigue, and appetite loss and
overall poorer QoL summary scores. WL is a frequent
manifestation of malnutrition and is an important criterion for the diagnosis of cancer cachexia, a multifactorial syndrome characterized by a negative protein
and energy balance driven by a variable combination
of reduced food intake and abnormal metabolism.35 In
patients with cancer, cancer cachexia is often defined
based on a single criterion: WL >5% over a period of
6 months. The adverse impact of WL on QoL has long
been recognized in patients with cancer, and WL has
been associated with deterioration in patients’ performance status and psychosocial well being.36-38 In a recent systematic review examining the impact of WL and
QoL, a negative relation between %WL and QoL was
reported in 23 of 27 studies included in the analysis.11
However, the mode by which WL exerts its influence
on QoL is not fully understood but may relate to muscle atrophy associated with cachexia and WL leading to
fatigue or reduced functional capacity.39 Importantly,
interventions aimed at targeting nutritional status and
attenuating WL have proven successful in improving
aspects QoL in patients with cancer.40 In addition,
novel cachexia treatments, such as anamorelin, an
oral ghrelin-receptor agonist with appetite-enhancing
and anabolic activity, have shown a favorable clinical
­response in alleviating anorexia-cachexia symptoms.41,42
When examining the effect of muscle parameters
and QoL outcomes, low SMI was associated with poorer
physical function and more insomnia, whereas low MA
was correlated with poorer physical function, role function, global health, and summary QoL scores and also
with more fatigue and dyspnea (all P  <  .05). Low MA
was independently associated with poorer EORTCreported physical functioning (hazard ratio, 1.67; 95%

CI, 1.09-2.56; P = .018), whereas low SMI was not. This
is consistent with previous reports that low MA is associated with physical functional impairments, as evidenced
by improvements in timed-up-and-go, stair-climb, and
walking tasks.43 Inconsistent reports on this relation between muscle parameters and QoL have been published
in the literature.10,12,44,45 Parsons and colleagues reported
no significant associations between low SMI and symptom burden or functional life domains assessed by the
MD Anderson Symptom Inventory in a cohort of 104
patients with advanced cancer.44 However, in a study of
734 patients with advanced lung cancer, low SMI was
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Month 0, 2020

nonlinearly associated with lower global QoL, physical
function, and role function and was associated with more
symptoms (fatigue and pain), whereas low MA was associated with poor physical function and more dyspnoea.10
An explanation for our findings may be that low SMI, at
a single time point, is not reflective of a dynamic measure
of loss and may be influenced by a patient’s intrinsic level
of muscularity. Within our study, the composition of WL
that influenced QoL was unknown, and perhaps losses of
muscle over time may better reflect poor QoL. A growing body of evidence favors measures of muscle loss over
time as prognostic of poor survival in patients with cancer
compared with single-point measurements.46,47
The strengths of this study include the collection of numerous variables measured with appropriate
methods simultaneously in a relatively large sample of
patients with incurable cancer. In addition, using the
QoL summary score to examine differences in QoL can
avoid problems that may arise with multiple testing
when otherwise making comparisons based on the 15

outcomes generated by the EORTC-QLQ questionnaire.18 However, study limitations are also present.
The etiology of QoL is extremely complex given the
web of determinants that influence it; and, although we
accounted for several clinical and nutritional parameters, the list of variables examined was not exhaustive.
Given the convenient recruitment strategy, patients
may have been at different time points in their disease
trajectory when QoL was assessed (81% received had
chemotherapy in the previous 4  weeks). In addition,
­patients may have received prior treatments, and this
may have influenced QoL scores.
Conclusion

In summary, the current findings provide evidence of the
independent role of WL, ECOG-PS, and systemic inflammation (mGPS) in predicting poorer physical functioning,
more fatigue and appetite loss, and poorer overall QoL summary scores in patients with incurable cancer. Our findings
indicate potential targets for interventions aimed at safeguarding the QoL of patients with advanced cancer. Future
work should focus on targeting the systemic inflammatory
response, attenuating WL, and improving performance status in patients with incurable cancer as a means of improving PROMs and reducing symptom burden.
FUNDING SUPPORT

This work was funded in part with the financial support of Science
Foundation Ireland (SFI) under grant SFI/12/RC/2273.

9


Original Article

CONFLICT OF INTEREST DISCLOSURES

Claribel Simmons reports grants from Medical Research Scotland, during
the conduct of the study. The remaining authors made no disclosures.

AUTHOR CONTRIBUTIONS

Louise E. Daly: Conceptualization, data curation, formal analysis,
investigation, methodology, project administration, visualization, writing–original draft, and writing–review and editing. Ross D. Dolan:
Conceptualization, data curation, formal analysis, investigation, methodology, project administration, visualization, writing–original draft,
and writing–review and editing. Derek G. Power: Data curation, methodology, project administration, resources, supervision, and writing–
review and editing. Éadaoin Ní Bhuachalla: Data curation, investigation, methodology, project administration, and writing–review and
editing. Wei Sim: Data curation, investigation, methodology, project
administration, and writing–review and editing. Samantha J. Cushen:
Data curation, investigation, methodology, project administration, and
writing–review and editing. Marie Fallon: Conceptualization, data curation, methodology, project administration, resources, supervision, and
writing–review and editing. Claribel Simmons: Data curation, investigation, methodology, project administration, and writing–review and
editing. Donald C. McMillan: Conceptualization, data curation, formal
analysis, methodology, project administration, resources, supervision,
and writing–review and editing. Barry J. Laird: Conceptualization, data
curation, formal analysis, funding acquisition, methodology, project
administration, resources, supervision, visualization, writing–original
draft, and writing–review and editing. Aoife M. Ryan: Conceptualization,
data curation, formal analysis, funding acquisition, methodology, project
administration, resources, supervision, visualization, writing–original
draft, and writing–review and editing.

REFERENCES
1.Jordan K, Aapro M, Kaasa S, et al. European Society for Medical
Oncology (ESMO) position paper on supportive and palliative care.
Ann Oncol. 2018;29:36-43.
2. Qi Y, Schild SE, Mandrekar SJ, et al. Pretreatment quality of life is

an independent prognostic factor for overall survival in patients
with advanced stage non-small cell lung cancer. J Thorac Oncol.
2009;4:1075-1082.
3. Yang CJ, Roh JL, Kim MJ, et al. Pretreatment quality of life as a prognostic factor for early survival and functional outcomes in patients with
head and neck cancer. Qual Life Res. 2016;25:165-174.
4. Gotay CC, Kawamoto CT, Bottomley A, Efficace F. The prognostic
significance of patient-reported outcomes in cancer clinical trials. J Clin
Oncol. 2008;26:1355-1363.
5. Kypriotakis G, Vidrine DJ, Francis LE, Rose JH. The longitudinal relationship between quality of life and survival in advanced stage cancer.
Psychooncology. 2016;25:225-231.
6. Cherny NI, Sullivan R, Dafni U, et al. A standardised, generic, validated approach to stratify the magnitude of clinical benefit that can be
anticipated from anticancer therapies: the European Society for Medical
Oncology Magnitude of Clinical Benefit Scale (ESMO-MCBS). Ann
Oncol. 2015;26:1547-1573.
7.Aaronson NK, Ahmedzai S, Bergman B, et al. The European
Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology.
J Natl Cancer Inst. 1993;85:365-376.
8.Laird BJ, Fallon M, Hjermstad MJ, et al. Quality of life in patients with advanced cancer: differential association with performance status and systemic inflammatory response. J Clin Oncol.
2016;34:2769-2775.
9. Velikova G, Coens C, Efficace F, et al. Health-related quality of life in
EORTC clinical trials—30 years of progress from methodological developments to making a real impact on oncology practice. Eur J Cancer
(Suppl). 2012;10:141-149.
10. Bye A, Sjoblom B, Wentzel-Larsen T, et al. Muscle mass and association to quality of life in non-small cell lung cancer patients. J Cachexia
Sarcopenia Muscle. 2017;8:759-767.

10

11. Wheelwright S, Darlington AS, Hopkinson JB, Fitzsimmons D, White
A, Johnson CD. A systematic review of health-related quality of life
instruments in patients with cancer cachexia. Support Care Cancer.

2013;21:2625-2636.
12.Nipp RD, Fuchs G, El-Jawahri A, et al. Sarcopenia is associated

with quality of life and depression in patients with advanced cancer.
Oncologist. 2018;23:97-104.
13. Arends J, Bachmann P, Baracos V, et al. ESPEN guidelines on nutrition
in cancer patients. Clin Nutr. 2017;36:11-48.
14. Dolan R, Laird BJA, Horgan PG, McMillan DC. The prognostic value
of the systemic inflammatory response in randomised clinical trials in
cancer: a systematic review. Crit Rev Oncol Hematol. 2018;132:130-137.
15. McMillan DC. Cancer and systemic inflammation: stage the tumour
and stage the host. Br J Cancer. 2013;109:529.
16. Temel JS, Greer JA, El-Jawahri A, et al. Effects of early integrated palliative care in patients with lung and GI cancer: a randomized clinical
trial. J Clin Oncol. 2017;35:834-841.
17. Bakitas M, Lyons KD, Hegel MT, et al. Effects of a palliative care intervention on clinical outcomes in patients with advanced cancer: the
Project ENABLE II randomized controlled trial. JAMA. 2009;302:
741-749.
18.Giesinger JM, Kieffer JM, Fayers PM, et al. Replication and validation of higher order models demonstrated that a summary score for the
EORTC QLQ-C30 is robust. J Clin Epidemiol. 2016;69:79-88.
19. McMillan DC. The systemic inflammation-based Glasgow prognostic
score: a decade of experience in patients with cancer. Cancer Treat Rev.
2013;39:534-540.
20.Proctor MJ, Morrison DS, Talwar D, et al. An inflammation-based
prognostic score (mGPS) predicts cancer survival independent of
tumour site: a Glasgow Inflammation Outcome Study. Br J Cancer.
2011;104:726-734.
21. Oken MM, Creech RH, Tormey DC, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol.
1982;5:649-655.
22.Heymsfield SB, Wang Z, Baumgartner RN, Ross R. Human body
composition: advances in models and methods. Annu Rev Nutr.

1997;17:527-558.
23. van Vugt JL, Levolger S, Gharbharan A, et al. A comparative study of
software programmes for cross-sectional skeletal muscle and adipose tissue measurements on abdominal computed tomography scans of rectal
cancer patients. J Cachexia Sarcopenia Muscle. 2017;8:285-297.
24. Mourtzakis M, Prado CM, Lieffers JR, Reiman T, McCargar LJ, Baracos
VE. A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired
during routine care. Appl Physiol Nutr Metab. 2008;33:997-1006.
25.Shen W, Punyanitya M, Wang Z, et al. Total body skeletal muscle
and adipose tissue volumes: estimation from a single abdominal crosssectional image. J Appl Physiol (1985). 2004;97:2333-2338.
26. Mitsiopoulos N, Baumgartner RN, Heymsfield SB, Lyons W, Gallagher
D, Ross R. Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography. J Appl Physiol
(1985). 1998;85:115-122.
27. Martin L, Birdsell L, Macdonald N, et al. Cancer cachexia in the age
of obesity: skeletal muscle depletion is a powerful prognostic factor,
independent of body mass index. J Clin Oncol. 2013;31:1539-1547.
28. Zimmermann C, Burman D, Swami N, et al. Determinants of quality of life in patients with advanced cancer. Support Care Cancer.
2011;19:621-629.
29.Lam K, Chow E, Zhang L, et al. Determinants of quality of life in
advanced cancer patients with bone metastases undergoing palliative
radiation treatment. Support Care Cancer. 2013;21:3021-3030.
30.Laird BJ, McMillan DC, Fayers P, et al. The systemic inflammatory
response and its relationship to pain and other symptoms in advanced
cancer. Oncologist. 2013;18:1050-1055.
31.Paulsen O, Laird B, Aass N, et al. The relationship between proinflammatory cytokines and pain, appetite and fatigue in patients with
advanced cancer. PLoS One. 2017;12:e0177620.
32. Breitbart W, Rosenfeld B, Tobias K, et al. Depression, cytokines, and
pancreatic cancer. Psychooncology. 2014;23:339-345.
33.Du YJ, Zhang HY, Li B, et al. Sputum interleukin-6, tumor necrosis factor-α and salivary cortisol as new biomarkers of depression in

Cancer  

Month 0, 2020


Quality of Life in Incurable Cancer/Daly et al

lung cancer patients. Prog Neuropsychopharmacol Biol Psychiatry.
2013;47:69-76.
34. McSorley S, Dolan R, Roxburgh C, McMillan DC, Horgan PG. How
and why systemic inflammation worsens quality of life in patients with
advanced cancer. Expert Rev Qual Life Cancer Care. 2017;2:167-175.
35.Fearon K, Strasser F, Anker SD, et al. Definition and classifica
tion of cancer cachexia: an international consensus. Lancet Oncol.
2011;12:489-495.
36.Bachmann J, Heiligensetzer M, Krakowski-Roosen H, Buchler MW,
Friess H, Martignoni ME. Cachexia worsens prognosis in patients with
resectable pancreatic cancer. J Gastrointest Surg. 2008;12:1193-1201.
37. Blum D, Omlin A, Baracos VE, et al. Cancer cachexia: a systematic literature review of items and domains associated with involuntary weight
loss in cancer. Crit Rev Oncol Hematol. 2011;80:114-144.
38. Ravasco P, Monteiro-Grillo I, Vidal PM, Camilo ME. Cancer: disease
and nutrition are key determinants of patients’ quality of life. Support
Care Cancer. 2004;12:246-252.
39.Fearon KC, Voss AC, Hustead DS; Cancer Cachexia Study Group.
Definition of cancer cachexia: effect of weight loss, reduced food intake, and systemic inflammation on functional status and prognosis.
Am J Clin Nutr. 2006;83:1345-1350.
40. Baldwin C, Spiro A, Ahern R, Emery PW. Oral nutritional interventions in malnourished patients with cancer: a systematic review and
meta-analysis. J Natl Cancer Inst. 2012;104:371-385.

Cancer  

Month 0, 2020

41.Temel JS, Abernethy AP, Currow DC, et al. Anamorelin in patients
with non–small-cell lung cancer and cachexia (ROMANA 1 and
ROMANA 2): results from two randomised, double-blind, phase 3
trials. Lancet Oncol. 2016;17:519-531.
42.Advani SM, Advani PG, VonVille HM, Jafri SH. Pharmacological
management of cachexia in adult cancer patients: a systematic review of
clinical trials. BMC Cancer. 2018;18:1174.
43. Williams GR, Deal AM, Muss HB, et al. Skeletal muscle measures and
physical function in older adults with cancer: sarcopenia or myopenia?
Oncotarget. 2017;8:33658-33665.
44.Parsons HA, Baracos VE, Dhillon N, Hong DS, Kurzrock R. Body
composition, symptoms, and survival in advanced cancer patients
referred to a phase I service. PLoS One. 2012;7:e29330.
45.Neefjes ECW, van den Hurk RM, Blauwhoff-Buskermolen S, et al.
Muscle mass as a target to reduce fatigue in patients with advanced
cancer. J Cachexia Sarcopenia Muscle. 2017;8:623-629.
46.Daly LE, Ni Bhuachalla EB, Power DG, Cushen SJ, James K, Ryan
AM. Loss of skeletal muscle during systemic chemotherapy is prognostic of poor survival in patients with foregut cancer. J Cachexia
Sarcopenia Muscle. 2018;9:315-325.
47.Blauwhoff-Buskermolen S, Versteeg KS, de van der Schueren MA,
et al. Loss of muscle mass during chemotherapy is predictive for poor
survival of patients with metastatic colorectal cancer. J Clin Oncol.
2016;34:1339-1344.

11